Report No. 21103 - LSO Lesotho The Development Impact of HIV/AIDS Selected Issues and Options October 18, 2000 Macroeconomic Technical Group Africa Region iP p nt o th Wr'-. B;'-LLs,i- ~an ' '' - '- ; ' ' ; - ' . .. . _ ,~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~b. .4 .' . . , ,'' ' } . ' .. ," #,- 444 41 "4'. ' ¼ 4 ; . . 4 4 r 4 ' 4 ;''-. ' .4".,. Document of the nW.orld Bank -:.--- .-:-.:- CURRENCY EQUIVALENT (October 16, 2000) Currency Unit = Maloti (M) Maloti 1 = US$ 0.13 US$ 1.00 = M 7.43 (Maloti) ABBREVIATIONS AND ACRONYMS AIDS Acquired Immune Deficiency Syndrome ANC Ante Natal Clinics CT HIV Confirmnatory Test FLE Family Life Education HIV Human Immunodeficiency Virus HSA Health Services Area IEC Information , Education, and Communication LBTS Lesotho Blood Transfusion Services LENASO Lesotho Network of AIDS Services Organization MOH Ministry of Health MCT Mother to Child Transmission NAC National AIDS Committee NAPCP National AIDS Prevention and Control Program PLWHA People Living With HIV/AIDS RSA Republic of South Africa RT HIV Rapid Test SSS Sentinel Surveillance System STD Sexually Transmnitted Disease TB Tuberculosis UNAIDS United Nations AIDS Agency WHO World Health Organization Vice President Callisto E. Madavo Country Director Fayez Omar Sector Manager Philippe Le Houerou Task Team Leader James Sackey Lesotho: The Development Impact of HIV/AIDS - Selected Issues and Options Table of Contents Page No. Executive Sumnuary ...................... .................................... i Chapter I Introduction: HIV/AIDS in Lesotho ..1............... A. HIV Prevalence ............................................. 1 B. AIDS Statistics .............................................. 7 C. Factors Exacerbating HIV/AIDS Spread in Lesotho 8 D. Conclusions ............................................. 11 Chapter II Selected Impact of HIV/AIDS ....................................... 13 A. The Demographic Impact ........................................ 13 B. Effect on Labor and Human Resource Development ......... 17 C. Macroeconomnic Impact ........................................... 22 D. Conclusions ............................................. 24 Chapter III Options for Action ............................................. 26 A. Ongoing Response to HIV/AIDS in Lesotho ......... ......... 26 B. Proposals to Strengthen Ongoing Initiatives ......... .......... 28 C. The Need for Further Research .................... .............. 36 Bibliography . ............................................................................ 38 Annexes I The Result of the Lesotho Hospital Based HIV Sero-prevalence Survey .40 II Modeling the Impact of HIV/AIDS .51 III Assumptions Used in the Calculation of Prevention and Mitigation Programs for HIV/AIDS .................................. 55 List of Tables 1.1: HIV Surveillance Data by Site ........................................ 1 1.2: HIV Prevalence in Selected Sample of STDITB Patients ........ 4 1.3: Gender and Age Perspective of HIV Positive STD Patients (in Percentage) ............................................. 5 1.4: HIV Prevalence Rates for Lesotho by District .......... ............ 6 1.5: Reported Non-regular Sexual Partnership, 1989 ......... .......... 10 2.1: Lesotho - Mortality Impact of AIDS .................. .............. 15 2.2: Under 5 Mortality Rates: with and without AIDS per 1000 population .16 2.3: Lesotho -Estimates of Life Expectancy .17 2.4: HIV/AIDS and the Public Sector .................................... 20 2.5: Staffing Cost of HIV/AIDS to the Public Sector .21 2.6: Lesotho - Indicators of Macroeconomic Impact of HIV/AIDS 23 3.1: Draft Budget for National AIDS Strategy and Action Plan (In Thousands of Maloti) .28 3.2: Strategies and Options.............................................. 29 3.3: Summary of Estimated Costs of Selected Policy Interventions .36 List of Figures 1.1: HIV Positive Rates for ANC Sample for 1996/97 ............... 2 1.2: HIV Prevalence Rates Based on Blood Transfusion Services Data: 1998 ............................................ 3 1.3: HIV Prevalence by Occupation .................................... 6 1.4 Estimated Course of H1V Incidence in Lesotho: 1985-2000.... 7 1.5: New and Cumulative AIDS Cases in Lesotho ......... ........... 7 1.6: Age/Sex Composition of New AIDS Cases in 1998 ............. 8 1.7: Factors Exacerbating HIV/AIDS Spread in Lesotho ............. 9 1.8: Reported AIDS Cases by Occupation of Patient: 1998 .......... 10 2.1: Population Size With and Without AIDS ............ ............. 14 2.2: Growth Rate of Population With and Without AIDS 16 2.3: The Size of the Labor Force - With and Without AIDS ....... 17 2.4: Employees by Major Occupational Groups .......... ............. 18 2.5: Public Sector Employment by Age and Gender: 1999/2000 .... 19 2.6: Estimated HIV Prevalence by Age and Gender by 2010 ........ 21 2.7: Growth Rate of GDP (With and Without AIDS) .................. 23 3.1: Hospital Bed Days Needed for AIDS Patients ......... ........... 34 List of Boxes 1.1: Denial of HIV/AIDS in Lesotho ........................1............ 11 This report was prepared by James Sackey and Tejaswi Raparla (AFTM1). The report team received substantial support from the authorities in Lesotho, especially Dr. Givans K. Ateka (WHO), Mr. Thabo Thulo (Ministry of Finance) and the staff of the Bureau of Statistics who participated in the demographic and economic modeling exercise. Bala Rajaratnam (Consultant) contributed to the analysis in Annex I and the projections for HIV/AIDS impact on public sector staffing. Valuable comments were received from colleagues at AFTM1, members of Lesotho Country Team, the peer-reviewers, Messers. Mead Over (DECRG) and Rene Bonnel (AFRHV), and from participants at a workshop held in Maseru in August, 2000. Secretarial assistance was provided by Felicidad Santos. EXECUTIVE SUMMARY Introduction Overview: The objective of this report is to provide an overview of selected likely development impact of HIV/AIDS for Lesotho. The purpose is to engage in a dialogue with Government, relevant stakeholders and the donor community on the appropriate actions to pursue in support of the Government's recently developed strategy on the epidemic. The review at this stage does not provide a detailed costing of the impact of HIV/AIDS on various sectors of the economy because of limitations of data. Detailed costing and policy design alternatives should be the focus of subsequent analysis. This report was initiated as an exercise to assist policy makers in Lesotho in their effort to incorporate HIV/AIDS into the planning process on a regular basis. As such, it is directed at officials at the ministries of finance and development planning. It employs conventional demographic and economic models to analyze selected development impacts of HIV/AIDS on the economy, thereby providing an illustration of how these impacts can be incorporated in the regular planning processes (including annual budgeting) in the finance and development ministries of Government. It points out the need for monitoring the progression of the epidemic through further research and improvements in existing instruments. Status of HIV/AIDS in Lesotho: Like in other African countries, HIV/AIDS is emerging as a major health and development concern in Lesotho. The UNAIDS estimates that about 23.6 percent of adults (15 - 49 years), that is an estimated 240,000 persons out of Lesotho's population of about 2 million, are living with HIV (excluding those with AIDS) in Lesotho in 1999. In view of the weaknesses inherent in existing data on prevalence in Lesotho, the official UNAIDS adult HIV prevalence rate is likely to either underestimate or overestimate the actual level of HIV incidence but it provides a reasonable baseline for analytical work and it is used in the discussion and projections in this report. On average, one in every four adult Basotho is likely to have been infected with the HIV. The HIV prevalence rates, based on a 1999 survey of hospitals, differ by district with Maseru (the major urban area) yielding the highest prevalence rate of 39.5 percent. Only two districts recorded HIV prevalence rates of less than 20 percent. The estimated number of deaths due to AIDS by end-December 1999 was 16,000. As in the case of HIV infection, this is likely to be an underestimate of the actual number of AIDS cases for the following reasons: (a) inadequate diagnosis, especially because of the relationship between opportunistic diseases like TB and AIDS; (b) failure on the part of some AIDS patients to seek hospital services, particularly in remote rural areas with no health facilities; and (c) poor maintenance of diagnostic AIDS data at health units, especially at the onset of the epidemic. Nevertheless, the pattern of AIDS cases is also a cause for concern because: * The reported AIDS cases are primarily clustered in the 20 - 39 years age groups, which accounted for 57 percent of all cases in 1998. With the rise of new infections increasingly concentrated in this age group, the HIV/AIDS epidemic is likely to have substantial impact on the demographics of Lesotho during the next 10 years. * Consistent with the rate of progression from HIV infection to full blown AIDS being faster in women than men, female AIDS cases are much higher than male cases in the 20 - 39 years age group (child-bearing age group) while lower in other age groups. In 1998, about 55 percent of all reported cases was female. * Of the 47 percent of the AIDS patients who indicated their marital status, 69.5 percent was married. Similarly, of the 43.5 percent who indicated their occupation, 29 percent was i housewives and 23 percent miners/former miners. Therefore, the relationship between marital status and occupation, in particular, housewives and migrant miners becomes important in focusing on mitigation and preventive methods. * Twelve percent of reported AIDS cases in 1998 was attributed to children under 4 years of age. Mother to child (MTC) transmission may be a significant mode of infection and needing further study. Available information on the risk factors contributing to the exacerbation of HIV/AIDS in Lesotho pointed to two key characteristics: multiple sexual partnership for contributing to the spread of HIV, and STD as an opportunistic disease in promoting the increase of AIDS. Based on a sample of 3,242 AIDS cases in 1998, 30 percent indicated a history of multiple partnership; 28 percent had a history of STD over the past 12 months and less than 1 percent of the cases could be attributed to blood transfusion. There were no reported cases of AIDS due to drug use. In reviewing the mode of transmission of IHV/AIDS in Lesotho, two key hypotheses therefore stand out: * Women may be identified as particularly vulnerable because of biological and cultural predispositions that place them at a greater risk of transmission, social disempowerment, and inability to make decisions about sexual issues. * Large numbers of male Basotho workers migrate to mines in the South Africa, spending extended periods of time away from home and spouses. Wide spread poverty and the large migrant labor community associated with those areas may have contributed in the export of HIV to Lesotho in an environment in which multiple sexual partnership is common. Selected Development Impact This section deals with selected development impact of HIV/AIDS on the economy of Lesotho, focusing on the likely demographic effect of the epidemic and its implications for the overall availability of labor in the economy, the demand for and supply of manpower in the public sector, and the potential costs to the public sector of its response to deal with these effects. The objective is to outline the key factors that could contribute to reducing both private and public savings with likely negative impact on domestic investment and growth. Demographic Impact: The reduction in population due to AIDS, unlike programs for population control, is unusually damaging to the economy in two fronts. First, while planned parenthood and population programs support the increase of social capital, AIDS death does essentially the opposite. It reduces the size of the economically active population. Second, AIDS mortality tends to impose a "shock" to the household's economic structure since the death of an economically active individual could force changes in size, composition and socio-economic status of the household and in the use of time devoted to building human capital. In the presence of HIV/AIDS, long term planning could suffer when social contracts fail, i.e. sharing of work, human capital development (through schooling) etc. The estimates suggest that the long-term demographic impact of AIDS is likely to be significant. The population in Lesotho is estimated at 2.8 million by 2015, about 644,000 or 23 percent lower than it would have been in the absence of AIDS. This compares to the estimates by the UN (1998) which shows that by 2015, the population of Botswana and Namibia is expected to be 20 percent lower that it would have been in the absence of AIDS. The results indicate annual AIDS deaths increasing from 1 in 1986 to over 44,000 in 2015. Closer examination of the data reveals that by the 2010, the number of AIDS deaths may exceed the number of estimated adult . . deaths in the absence of AIDS. Majority of the AIDS deaths are expected to fall on the 15-49 years age group, the most sexually active and in the prime of their productive years. Along with the decline of population growth, life expectancy in Lesotho is projected to decline on account of AIDS. Life expectancy at birth measures the average number of years that a newborn child would live if mortality remained constant through out his/her lifetime. As a result of the increasing mortality due to AIDS, life expectancy has already stagnated in Lesotho and the trend is likely to continue through 2015. Life expectancy is estimated at 52.4 years for 2001, instead of 66.0 years in the absence of AIDS, a loss of almost 13.6 years over the past decade. By 2015, the difference in life expectancy, with and without AIDS, is projected to reach a staggering 31.4 years. Implications for the Public Sector: Apart from directly reducing life expectancy, and through it the size of the overall labor force over time, AIDS also affects the dynamics of skills accumulation in the labor market. AIDS tends to kill prime-age adults, many of whom are skilled and at the peak of their economic productivity. Preliminary analysis of the impact of HIV/AIDS on the labor force, and the likely effect on public sector staffing by skill level was undertaken. The 1996/97 Employment and Earnings Survey (UNDP) estimated that the public sector (excluding parastatals and referred to as civil service) accounted for about 43 percent of the total formal sector employment of about 72,000 at the end of 1996. The survey also indicated that public sector workers received higher monthly average earnings than workers of the private and parastatal sectors. If wage levels are a reflection of skill composition, then the public sector accounts for a higher percentage of the skilled labor in the economy. Two main implications may be envisaged for the civil service sector. First, there will be reduced productivity resulting from higher absenteeism and morbidity due to FHV; and second, the cost of running the public sector is likely to increase as a result of the higher demand for pensions due to early retirement and death and the cost for replacement and training of new staff. Productivity losses resulting from absenteeism and morbidity is estimated at M 10 million in FY1999/2000, constituting about 1.3 percent of total wage bill. If it is assumed that real wages do not increase through 2015 and the civil service to total population ratio is kept constant, the cost of absenteeism and morbidity associated HIV/AIDS could increase from 1.3 percent of total wage bill to about 1.8 percent by 2015. Estimating the direct cost of AIDS deaths on the civil service sector is more complicated. The direct cost of staff death may be decomposed into three components: pension or gratuity payments to spouse and dependents, hiring costs, and retraining costs. The pensions rule in the public sector in Lesotho identifies different categories of staff according to the type of contract, number of years in service and the level of emoluments. For the purposes of analysis, we assume that all officers who have AIDS die while in service and have successfully completed the period of probation. Under these circumstances, the gratuity payment to spouse or dependents is calculated as the last month's salary multiplied by the years of service divided by two. This yields estimated gratuity/pension payments rising from about M 340, 000 in 2000 to M 6 million by 2015 at constant 1999/2000 prices. Thus, the direct cost of AIDS deaths in the public sector could increase from 0.1 percent of the total wage bill in 2000 to about 2 percent by 2015. In sum, both the productivity loss and the direct cost of HIV/AIDS could amount to close to 5 percent of the total annual wage bill. Macroeconomic Impact: The impact of HIV/AIDS on macroeconomic fundamentals is much more complex than with the foregoing. From the macroeconomic perspective, HIV/AIDS is likely to affect the savings/investment relations. Expenditures for mitigating the impact of HIV/AIDS at both the household and public sector levels are likely to reduce the amount of iii capital (both public and private) available for more productive investment; thus higher the proportion of care financed from savings, larger the reduction in growth resulting from the epidemic. The report uses a growth model extended to incorporate the increase in morbidity and mortality resulting from HIV/AIDS. The model incorporates, among other parameters, labor productivity losses and AIDS costs met from reduced savings. Using estimates of AIDS deaths, reduced migrant remittances and lower government revenues, it is estimated that the presence of AIDS in Lesotho would reduce the average real GDP growth rate during the period 1986 - 2015 from 4.4 percent without AIDS to 3.6 percent with AIDS. This implies that the economy will grow eight tenths of a percentage point smaller (or 29 percent smaller) by 2015 because of the epidemic. This constitutes a projected income loss of about one percent of per capita income per year for 2000-15 in part because of population decline. The model assumes that the baseline growth rate will be positive on the basis of past experience and the possibility of other shocks have not been incorporated. The estimates are thus conservative in view of ongoing structural changes in Lesotho that have tended to dampen growth performance. Although the macroeconomic effects of HIV/AIDS do not appear devastating, the impact is not uniformly felt across households. At the household level, HIV/AIDS morbidity and death exacerbates poverty and social inequality. Lower income households will be less able than others to cope with the medical expenses and other impacts, including loss of income. The loss of social capital and the resilience level of the house are two key areas requiring policy focus. Options for Action Overview: Developing a policy response to the epidemic in Lesotho requires cognizance of ongoing public, donor and private activities to mitigate its impact. Following the first AIDS case in Lesotho in 1985, a National AIDS Prevention and Control Program (NAPCP) was established in the Ministry of Health by July 1987, which ultimately became part of the ministry's Division Sector for Disease Control and Environmental Health. The unit has been supported by the WHO, UNDP and several other donors. Furthermore, several coordinating groups have been organized to assist the NAPCP in carrying out its program. While the institutional framework is largely appropriate and in place, program development and execution have had mixed results since the early 1 990s: * Considerable progress has been achieved in the decentralization of activities, largely because of the efforts of WHO, which worked directly with other arms of MOH and the government. Focal persons in the Health Service Areas (HSA), including counselors have been trained, and health personnel have received STD/HIV/AIDS information. * Although the success of information, education, and communication (IEC) activities for AIDS prevention is difficult to assess, they appear to have been able to raise the awareness of the general population concerning AIDS. However, since the 1989 Knowledge, Attitudes, Behavior and Practices (KABP) study, no recent baseline levels of knowledge, risk awareness and prevention practices have been defined against which progress could be measured. The other most noticeable gap has been the failure to intensify the education of patients being treated for STD. Overall, the direction and strategy for IEC activities in Lesotho appeal inadequate. * The establishment of the HIV sentinel surveillance sites (SSS) is providing program planners with prevalence data from two population groups: ANC and STD patients. However, the program has yet to perform special sero-prevalence surveys on target groups found to be of high risk: migrant workers, commercial workers and their clients, etc. Ascertaining HIV and iv STD prevalence levels and behavior profiles among risk groups could provide important infornation in defining core and non-core groups in Lesotho, as well as base-line data for monitoring intervention effectiveness. * All donated blood for transfusion, handled by the Lesotho Blood Transfusion Service (LBTS), has been regularly screened. Surveillance data suggests that HIV transmission due to contaminated blood is minimal. Of major concern, however, is the lack of counseling services and follow-up provided for individuals giving blood, and especially for those identified as HIV positive. Proposals to Strengthen Ongoing Initiatives: The potential for increased HIV infection levels in Lesotho can be attributed to four factors: (i) high prevalence of STD among migrant workers and teenagers; (ii) large number of migrant workers returning from South Africa; (iii) increasing prevalence of HIV in surrounding countries, particularly in South Africa where most migrant workers work; and (iv) increasing urbanization which weakens cultural norms in sexual behavior. With the exception of programs directed at youth, specific strategies to address these important variables have not been adequately developed as yet. In view of the above, and building upon ongoing initiatives to deal with the impact of HIV/AIDS in Lesotho, the report proposes that Government's focus should be directed at: (a) reducing the transmission of HIV; (b) prolonging life and reducing AIDS morbidity; and (c) mitigating the negative impact of AIDS on the economy, especially by initiating prograns for skills replacement. The report outlines the key areas of action on prevention and mitigation and provides some cost estimates for several components/programs, as reflected in the following table: Policy Framework for Prevention and Mitigation Programs Category Cost per year % % GNP (Million GDP Maloti in 1999/2000 prices) I. Selected Prevention Support for MTC transmission 5 0.1 0.1 (Age cohort: 0-5 years) Sex Education, & Community Programs 32 0.6 0.5 (Age cohort: 6-15 years) Sex Education for Teenagers 56 1.1 0.8 (Age cohort: 15-19 years) Increased Condom Use 121 2.4 1.8 (Age cohort: Adults) IECNVoluntary testing/Counseling 96 1.9 1.4 II. Selected Mitigation Orphan care 67 1.3 1.0 Hospital care for AIDS patients 708 13.6 10.6 Old age pension for AIDS patients 21 0.4 0.3 v The preliminary estimates suggest that the various elements of prevention could amount to between 0.1 to 2.4 percent of GDP per year. In terms of mitigation, orphan care is estimated at about an average of 1.3 percent of GDP per year. The largest single cost element is hospital care, which is estimated at about 13.6 percent of GDP per year on average during 2000-2015. The latter points to the need for alternative programs for handling AIDS and terminal care. Although these may underestimate the likely cost of prevention/mitigation activities, they point to the likely magnitudes and suggest that such programs can be accommodated by existing resources of Government. The loss of GDP associated with HIV/AIDS is estimated at, on average, M560 million per year in constant terms, or about 10 percent of GDP in the absence of HIV/AIDS during 2000-15. If the country is loosing such a magnitude in potential GDP, it should be able to contain these losses by appropriate prevention programs that amounts to less than about 6 percent of GDP per year. On the other hand, since mitigation costs are substantially higher than the loss of GDP, it is prudent that Government intensify preventive measures. Finally, policies to reduce the cost of both preventive and mitigation programs are warranted. Finally, the report notes that a key limitation of the ongoing study on the development impact of HIV/AIDS is the constraints posed by existing data. Dealing with the data constraints will require identifying areas where the impact is severe and conducting appropriate studies. Three areas may be identified: * The impact of HIV/IAIDS on the household: Existing studies on the microeconomic basis for the development impact of the epidemic indicate substantially more damaging implications at the household level. Nevertheless, initiating prevention and mitigation programs require more information than currently available. A household level survey focusing on impact of HIV/AIDS on household consumption (expenditures), labor supply, and coping mechanisms could provide valuable information for designing appropriate response to the epidemic. Furthermore, such a survey can provide behavior indicators that may be useful for developing preventive messages. * The impact of HIV/AIDS on the public sector: This will be required to deal with programs for recruitment and personnel management. Such analysis will not only need to deal with the skill profile of the public service, but will also provide the opportunity to revisit the role of the public sector and to redefine it to accommodate the effects of HIV/AIDS. It may require a public sector comprehensive census with a possibility for selective testing. * Integration of HIV/AIDS into Planning Models and Decision Making: This will require building capacity at two levels. Thefirst level may require the application of user friendly impact models at both the macro and sectoral levels. Such models, as planning tools, will provide estimates of the impact of AIDS on the supply of inputs (or resources) into production activities at various levels and sectors of the economy. It will deal with the training needs, recruitment, sick-leave, deaths, health expenditures, life insurance and benefit packages for each sector (and unit) within the economy. The analysis would essentially be a costing process which could ultimately be incorporated into the annual budget process. This process may need to be supplemented by a general equilibrium type modeling. The second level of capacity building will involve equipping each agency within a sector to integrate HIV/AIDS prevention and mitigation efforts into its operations. This activity should be within the operational budget of each agency and involves the development of workplace voluntary counseling systems and information sharing. vi Chapter I Introduction: HIV/AIDS in Lesotho Like in other African countries, HIV/AIDS is emerging as a major health and development concern in Lesotho. Lesotho is in a very vulnerable position because of its large migrant population, which is typically in the prime of their working life. The prospects for high HIV/AIDS incidence are thus increased as is the likelihood of a major development disaster attributable to the epidemic. This chapter deals with the status of the epidemic, discusses some of the factors which could contribute to the estimated high prevalence rates, found in the sample, and highlights the key concerns for dealing with the epidemic. A. HIV Prevalence Partly because of the stigma associated with HIV/AIDS and partly because of weak instruments for monitoring the epidemic, HIV/AIDS data are woefully inadequate in Lesotho as in other countries at a similar stage of development. In Lesotho, the principal sources of data are: survey data at antenatal clinics (ANC) collected as part of the sentinel surveillance system (SSS), data from blood transfusion services, data from blood tests at STD/TB wards, and occasional reviews of sampled blood at selected hospitals. The surveillance at antenatal clinics, which forms the basis of the SSS, is the best available method for estimating HIV prevalence among the adult population. Such surveys have been conducted at five hospitals in Lesotho during 1991 - 1994 and for 1996/97.1 These sites were chosen to capture regional differences. QEII hospital in Maseru represents an urban area, Leribe and Mafeteng a peri-urban area; Maluti a rural area and Quthing a mountain area. Subjects enter the sample as they come until the expected number of 200 sample per ANC clinic is attained.2 Table 1.1 assembles the results of the surveys for 1991-94, which indicates IV prevalence rates for pregnant women ranging from 0.7 percent in Quthing in 1991 to 31.3 percent in Maseru in 1994. The wide variation in prevalence rates is partly a reflection of the timing of the first HIV incidence at different locations in the country, and partly the state of poor reporting. Table 1.1: HIV Surveillance Data by Site Area 1991 1992 1993 1994 Peri-Urban Leribe 2.3 1.8 11.4 8.7 _Mafeteng 3.5 5.0 4.0 10.8 Rural-Hill Maluti 1.8 1.4 4.2 5.0 Quthing 0.7 8.4 3.4 9.1 Urban Maseru 5.5 5.1 6.1 31.3 Source: UNAIDS: Lesotho Epidemiological Fact Sheet on HIV/AIDS and Sexually Transmitted Diseases, November 1999. After a break in the systematic reporting of the outcome of the SSS, the sample for ANC during September 1996 to March 1997 was analyzed. They show markedly sharp increases in HIV prevalence in all sites (Figure 1.1). Unfortunately, substantial differences between the HIV rapid test (RT) performed at site and the confirmiatory test (CT) done at the National laboratory in Maseru make it difficult to both interpret the results and compare them to those of previous 1 While the sampling continues to be undertaken on an annual basis at the selected sites, analyses stopped in 1994 and except for 1996/97, has not been undertaken since. Reviewing the analysis of ANC data is a critical component of the monitoring system. 2 ANC sampling is thus not necessarily random and deals with only pregnant women. 1 years.3 Furthermore, because RT is highly sensitive it should indicate higher positive findings than those by CT. In so far as these results are reversed in certain circumstances casts doubt on the overall outcomes of the 1996/97 survey. Figure 1.1: HIV Positive Rates for ANC Sample for 1996/97 40' 30 | X 25 20. _||_ EFRT 10 Maseru Lerlbe Mafeteng Maluti Quthing Souice: Kingdom of Lesotho: September 1996-March 1997 HIV Sentinel Surveillance Report, Ministry of Health and Social Welfare, December 1999. In general, the ANC data are biased as a result of the method of data collection (focused mainly on pregnant women) and its extrapolation to the general population could be problematic. First, attendance at ANC does not include those who use private facilities (typically the higher and medium income groups although this may be insignificant) and those with no access to such facilities (poor rural residents). The former could have high-risk behavior because of mobility, while the latter are more likely to have less access to information (especially the role of migration in HIV spread) and are prone to high rate of infection. Second, ANC attendees are a sexually active group and it can neither be assumed that all women of child bearing age are sexually active nor those outside the child bearing age not sexually inactive. Analysis of data from blood transfusion services provides for screening of a more diversified sample relative to ANC for the level of H1V prevalence, although the sampling is not necessarily random. Every year, the Lesotho Blood Transfusion Services (LBTS) collects 3,000- 6,000 units of blood from voluntary blood donors made up of government and non-government officers, armed forces and security personnel (AM/SO), high school, college and university students, and the general public. Every unit of the blood is screened for syphilis (VDRL), hepatitis (HbsAg) and HIV. In 1998, the latest for which collated data are available, 2,948 blood samples were screened, of which 1.2 percent were found VDRL positive; 2.4 percent were Hepatitis B positive; and 12.3 percent were HIV positive (indetermninate and positive). No inforination on age and gender was available but the sources of collection provided insight into the occupational groups (Figure 1.2). 3 The difference between RT and CT would be the result of blood contamination due to poor handling in transition to Maseru (the testing point for CT) and weak reporting and testing at site. 2 Figure 1.2: HIV Prevalence Rates Based on Blood Transfusion Services Data: 1998 Overall WI xn ; General _ _ _ - . > i 4oj , ....................... CollUniv WW.- High S c h U> > . | I Prev. Rate (%) AMWSO Gov/Non-Gov 0 5 10 15 20 25 Source: Ministry of Health and Social Welfare: AIDS Epidemiology in Lesotho, 1998. Note: AM/SO: Armed Forces and Security Officers. The following conclusions could be derived from these results: * The levels of HIV prevalence in the samples for armed forces and security officers (AM/SO) (20.2 percent) and government and non-government employees (19.6 percent) are substantially above the national average. They reflect higher mobility and secure income sources associated with these groups, and also probably the failure of the national AIDS prevention program in its advocacy role since these are the most accessible groups. * The prevalence rates for the sample of high school and tertiary students could also be reflective of both higher sexual activity at a younger age, and probably the failure or the lack of preventive educational programs in the educational institutions in the country.4 Blood sample from STD/TB wards provides further information about the pervasiveness of HIV in Lesotho (Table 1.2). Like the data from ANC, blood samples of STD and TB patients are routinely analyzed for HIV infection. The procedure is similar to the methodology used for ANC in that a target of 200 samples are collected in the selected clinics in Maseru (QEII), Leribe, Mafeteng, Maluti, Quthing and occasionally, at Bokong (LHDA is a clinic and not a regular sentinel site). Unlike the ANC, the sample includes both sexes and it is collected on first-come basis until the target is reached. A wide and variable range of prevalence rates are reported, even for a single site, among the samples collected and analyzed since 1988. Since reporting and testing instruments were limited during the early stages of HIV in Lesotho, data up to 1995 are likely to be highly flawed, resulting in difficulty in making useful inference about trends. Consequently, the focus of discussion will be on the TB data for 1995 and the STD data for 1996/97. The information indicates that HIV prevalence rate among the selected STD/TB patients ranges from 22 percent in Quthing to 49.5 percent in Mafeteng. The high prevalence rates do not seem to be influenced by location (urban rural factors are not quite influential) and may differ most probably on account of sampling error. In general, the figures suggest that HIV prevalence rates are higher for STD and TB patients than that of the general population, reflective of TB as opportunistic diseases. 4 Since participants of blood transfusion services appear rather healthy, the high prevalence in this group (above the national average to be discussed below) may be a cause for concern. 5 The high rate of TB incidence in recent years provided the first indication of the high prevalence of HIV in Lesotho; consequently, past mortality data are likely to reflect TB as the main cause of death instead of AIDS. 3 Table 1.2: HIV Prevalence in Selected Sample of STD/TB Patients 1988-89 1991 1992 1993 1995 1996/97 STD Maseru a/ 1.0 5.8 13.6 11.1 40.1 Bokong b/ 5.8 _ Leribe a/c/ 4.8 9.6 16.2 38.3 Mafeteng a/c/ 7.1 11.3 15.2 36.7 Maluti a/ c/ 5.2 15.0 21.3 43.9 Quthing a/ c/ 14.6 11.7 12.3 22.2 TB Maseru d/ . 29.4 Leribe d/ 49.5 Mafeteng d/ 40.3 Not Specified e/ 23.0 Sources: a/ SSS data involving both sexes are derived from Lesotho Ministry of Health, HIV Sentinel Surveillance Reports for the specified years. b/ Data from STD sentinel clinic at Katse for both sexes, quoted by Kravitz, J.D.; R. Mandel, et.al (1995), Human Immunodeficiency Virus Seroprevalence in an Occupational Cohort in a South African Community, Archives of Intemal Medicine, vol.155, no. 15, pp. 1601 - 1604. c/ 1991 data derived from Lazzari, S and M. Lekometsa (1991), Report on Implementation of HIV Sentinel Surveillance: 1991, National AIDS Prevention and Control Program, WHO/MOH Lesotho. d/ Data from both sexes, derived from: Ministry of Health and Social welfare, STD/AIDS Unit, Country Focus - Lesotho, Southem Africa AIDS Information Dissemination Service Bulletin, vol. 4, no. 3, pp.9 -10, 1995. e/ Corcoran B. (1994), HIV/TB in Lesotho - Epidemiology and Control, Southem Africa TB/HIV Co- Infection Conference, Gaborone, Botswana, 11/7-11, pp.13-14. Analysis of information on age, sex and marital status for the HIV positive STD patients highlights a number of concerns: * HIV infection for the STD patients is higher generally among married individuals than among single or separated/widowed/divorced individuals (Table 1.3). For example, about 86 percent of HIV positive STD patients in Maluti District reported married, compared to 14 percent that were classified as single. * Among the STD patients that tested HIV positive, a higher proportion of the females were in the younger age group. For example, except for Maluti District, more than 10 percent of the female HIV positive STD patients were below 20 years of age compared to under 10 percent for their male counterparts (except for Quthing). In general, for all sites, a higher percentage of younger women (under 29 years) were infected relative to their male counterparts. The gender aspect of the HIV infection process is a theme that needs a special focus (see below) since understanding the role played by Basotho migrant miners in the spread of the epidemic is critical in devising preventive programs. A higher level of infection among married women in rural areas may also be attributed to the role played by migrant workers, although this requires further investigation. 4 Table 1.3: Gender and Age Perspective of HIV Positive STD Patients (In Percentage) ------------------Gender ---------------- --------------------- Age --------------------- Area Female: Female Male: Male: <20 <20 20 - 24 20 - 24 :__________ _________ years: years: years: years: Married Single Married Single Male Female Male Female Leribe - - - - 6.7 10.1 26.7 38.3 Quthing 73.8 23.8 50.0 48.5 11.9 15.5 26.9 29.8 Mafeteng 80.9 16.9 73.3 26.7 4.4 9.0 26.7 28.1 Maluti 91.9 8.1 75.3 24.5 7.3 4.8 16.4 25.0 Maseru 69.0 46.3 4.1 10.6 39.2 40.9 Source: Kingdom of Lesotho: September 1996-March 1997 HIV Sentinel Surveillance Report, Ministry of Health and Social Welfare, December 1999. Hospital Survey: In 1999, with the assistance of WHO, the Government conducted a hospital based HIV survey, covering all Health Service Areas (HSA) in Lesotho (Annex I). Pre- specified sample sizes were allotted to the different HSA according to patient turnout at different collection points. A random sample of patients at different collection points was not possible; instead unlinked anonymous serum testing was used. The only information required was the name of the HSA, the patient's age, sex, occupation and the provisional diagnosis. This ensured confidentiality for the individual patients. Part of blood already taken from patients for investigation for other conditions was used. The need for pre-test counseling was therefore obviated. Of the 11,200 sample size earmarked, there were 7,058 responses, yielding on average, 63 percent response rate. Although the objective was to get at least 200 samples per HSA, four HSAs did not satisfy the minimum sample requirement. The sampling limitation also led to an under- representation of children (0 - 14 years) and the elderly (70 years or more) and over- representation of women, who accounted for 77 percent of the sampled patients. Weights that were derived from the Lesotho National Population Census of 1999 were used to correct the design weaknesses and to reconstruct a random sample of about 5,928 responses. Table 1.4 provides HIV prevalence estimates for Lesotho by district, yielding a national rate of 26.5 percent (with the corresponding adult prevalence rate of 35.3 percent4. The 95 percent confidence interval for this estimate is (26.42%- 26.54%), implying that, on average, one in every four Basothos is infected with the HIV virus. The HIV prevalence rates differ by districts with Maseru yielding the highest prevalence rate of 39.5 percent. Qacha's Nek follows with a prevalence rate of 37.2 percent, but this result should be interpreted with caution because of the small sample size for this district. HIV prevalence rates in other districts are generally in mid to upper 20 percent range. Only two districts recorded H1V prevalence rates of less than 20 percent. 6 It needs to be emphasized that, despite the corrections made to the sample, prevelence rates based on hospital patients are like to be biased upward. 5 Table 1.4: HIV Prevalence Rates for Lesotho by District District Overall Adult Adult Female Adult Male Berea 27.1 38.6 34.7 42.8 Butha-Buthe 24.4 30.9 31.8 29.9 Leribe 18.4 30.7 25.2 36.4 Mafeteng 15.4 27.6 28.1 26.2 Maseru 39.5 41.2 34.6 48.5 Mohale's Hoek 22.3 34.8 28.4 41.5 Qucha's Nek 37.2 57.7 26.3 32.0 Quthing 24.9 29.4 Thaba-Tseka 24.5 32.5 19.5 46.1 National 26.5 35.3 29.7 39.4 Prevalence rates are higher for men than women. It is estimated at 30 percent for women and close to 40 percent for men. Except for Butha-Buthe and Mafeteng, the prevalence rates for men are higher than their female counterparts in all districts. The results also further confirm the high prevalence rates among miners (47 percent), housemaids (50 percent) and farmers (44 percent). While the occupational classifications cannot be verified and could lead to some misinterpretation, they point to the high risk groups in the society. Figure 1.3: HIV Prevalence by Occupation 60 30 | - 1111 10 >,;, § S +SP~~~0<0g 0P°Ci 0P< No Estimated Number of HIVInfections in Lesotho: In order to derive the national prevalence rate of HIV infection, the UNAIDS/WHO working group on Global HIV/AIDS Surveillance in collaboration with national and regional experts, adopted the following approach: * All previous data from sentinel surveillance in Lesotho were reviewed and median rates were calculated for "Major Urban Areas" and "Outside Major Urban Areas". The figures were then applied to the official urban-rural population distribution in Lesotho. * The WHO Epimodel 2 was applied to the derived data to yield estimates for HIV and AIDS incidence by age and gender.8 7 The differentiation between the two geographical areas: "Major Urban Areas", and "Outside Major Urban Areas" is not based on strict criteria, such as the number of inhabitants. Major Urban Areas were considered to be the capital city and other metropolitan areas, while Outside Major Urban Areas considers that most sentinel sites are not located in strictly rural areas, even if they are located in somewhat rural districts (UNAIDS). a The Epimodel version 2. 6 On the basis of the above, the UNAIDS estimated that about 23.57 percent of adults (15 - 49 years), that is an estimated 240,000 persons, are living with HIV+ (excluding those with AIDS) in Lesotho in 1999 (Figure 1.4)9. In view of the weaknesses inherent in the data on prevalence in Lesotho, the official UNAIDS adult HIV prevalence rate in Lesotho is likely to be an underestimate of the actual level of HIV incidence but it provides the base-line for analytical work and it is used in the discussion and projections in Chapter II. Efforts to derive an improved prevalence rate must await improvements in the SSS and the conduct of a base-line survey. Figure 1.4: Estimated Course of WIV Incidence in Lesotho: 1985-2000 140000 20000 0~~~~~~~~~~~~~~~~~~~~~~~~~~ 100000 B AISSatistics y g' i wj - The ST/I/ISPeeto n otrlUiAfteDsaeCnrldiviio otHeV em000 inumer of d due o ANew HIV 20000 9 . s _ A4 lb O 9 N ql 'b 0 A b At b 9s '41 9V9t9V9, "-, '49 N-9 '4' '-, q. , '49 97 , PI Source: Ministry of Health and Social Welfare: AIDS Epidemiology in Lcsothio, 1998. B. AIMS Statistics The STD/HIV/AlDS Prevention and Control Unit of the Disease Control Division of the Ministry of Health maintains statistics on full-blown AIDS cases from hospitals in Lesotho. The estimated number of deaths due to AIDS by end-December 1999 is 16,000 (UNAIDS). This number is likely to be an underestimate of the actual number of AIDS cases for the following reasons: (a) inadequate diagnosis, especially because of the relationship between opportunistic diseases like TB and AIDS; (b) failure on the part of some AIDS patients to seek hospital services, especially in remote rural areas with no health facilities; and (c) poor maintenance of diagnostic AIDS data at health units, especially at the onset of the epidemicl° Figure 1.5: New and Cumulative AIDS Cases in Lesotho 8000 7000 . . N 6000 - 5000 .-~ 3000 ' > -' F-' I ti~1IaCumulative 2000 . m: . ;rt .Y 1000 . ' . "- __ 0 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 Source: Ministry of Health and Social Welfare: AIDS Epidemiology in Lesotho, 1998 9 Refer to http://www.unaids.org and http://www.who.ch/emc/diseads/hiv. 10 Until recently, it was likely that many AIDS deaths might have been attributed to opportunistic diseases such as TB, as in other parts of Africa. See Whitehead, et.al. (1995) with respect to AIDS reporting in KwaZulu in South Africa. 7 Despite the shortcomings of the reported AIDS statistics, the pattern of evolution reflects the exponential growth characteristic of the epidemic (Figure 1.5). It is also reflective of the high rate of HIV infection in sexually active adults in Lesotho. Although only a few early AIDS cases were reported among expatriates living in Lesotho, since 1990 almost all new cases have been Basothos. The pattern of AIDS cases is also a cause for concern: * The reported AIDS cases are primarily clustered in the 20 - 39 years age groups accounting for 57 percent of all cases in 1998. With the rise of new infections increasingly concentrated in this age group, HIV/AIDS epidemic is likely to have substantial impact on the demographics of Lesotho during the next 10 years. * Consistent with the rate of progression from HIV infection to full blown AIDS being faster in women than men, female AIDS cases are much higher than male cases in the 20 - 39 age group (child-bearing) while lower in other age groups. In 1998, 54.9 percent of all reported cases was female. * Of the 47 percent of the AIDS patients who indicated their marital status, 70 percent was married. Similarly, of the 44 percent who indicated their occupation, 29 percent was housewives and 23 percent miners/former miners. Therefore, the relationship between marital status, housewives and migrant miners becomes important in focusing on mitigation and prevention methods. * Twelve percent of reported AIDS cases in 1998 were attributed to children under 4 years of age, thus pointing to the likelihood that mother to child transmission (MTC) may be a significant mode of infection and needing further study. Among pediatric AIDS cases, failure to thrive (with appropriate therapy), recurrent infection, diarrhoea and oral candidiasis are the most common symptoms. Figure 1.6: Age/Sex Composition of New AIDS Cases in 1998 600 300 200 smales1 S I Too S 3 44 £ Female Source: Ministry of Health and Social Welfare: AIDS Epidemiology in Lesotho, 1998 C. Factors Exacerbating HIV/AIDS Spread in Lesotho Available information on the factors contributing to the exacerbation of HIV/AIDS in Lesotho pointed to two key sources: multiple partnership for contributing to the spread of H1V, and STD risk factor in exacerbating the increase of AIDS (Figure 1.7). Based on the sample of 3,242 AIDS cases in 1998, 30 percent indicated a history of multiple partnership; 28 percent had a history of STD over the past 12 months and only less than one percent of the cases could be attributed to blood transfusion." There were no cases of AIDS due to drug use in this sample. l Since April 1987, all blood products in Lesotho are screened for HIV. 8 Figure 1.7: Risk factors for HIV Infection in Lesotho (Based on Analysis of AIDS Cases in 1988) IV Drug Use STD S i 13No Multiple Partners Yes Blood Transfusion 0 200 400 600 800 1000 1200 1400 1600 Source: Ministry of Health and Social Welfare: AIDS Epidemiology in Lesotho, 1998. In reviewing the mode of transmission of HIV/AIDS in Lesotho, two key hypotheses stand out: * Women could be identified as particularly vulnerable because of biological and cultural predisposition that places them at a greater risk of infection because of social disempowerment, and the inability to largely make decisions about issues related to sex. - Large numbers of male Basotho workers migrate to mines in the South Africa, spending extended periods of time away from home and spouses. Widespread poverty and the large migrant labor community associated with those areas may have contributed in the importation of HIV to Lesotho in an environment in which multiple sexual partnership is common. The Gender Perspective: The review of the reported AIDS cases indicated that the number of female cases were much higher than those of men in the critical 20 - 39 age group (within the child-bearing age). Furthermore, most of those with HIV infections in the 15 - 19 years olds were female. Apart from possible biological factors, two factors in Lesotho contribute to the disproportionate risk of young women in acquiring HIV infection: * The vulnerability of young women to STD: The review of SSS data indicated that a larger proportion of females, relative to their male counterparts, in the 15 - 19 years category were HIV positive among the STD patients. This could be both a reflection of sexual activity at an early age and the higher propensity for women to be infected. * The tendency for women to get married at much younger age than men, and for young women to have sex with older men in exchange for financial and other benefits.'2 For many women, the main risk factor for HIV is the problem of multiple and frequent changes in partnership. In a survey cQnducted in 1989, about 52 percent of the men, who were 15 years and older, claimed of having at least one sex partner other than a regular partner during the last 12 months. A comparable proportion for the female respondents was 28 percent (Table 1.5). While the proportion of multiple partnership was higher for men aged 15 - 49 years, at 50 year and above the proportion of female with multiple partnership was comparable to that of men. This tends to support the hypothesis that the society condones the practice. 12 Refer to survey results by Kalilani (1999). 13 Lesotho was predominantly a polygamous society until the influence of Christianity enforced monogamy with its consequential multiple partnership outside the marital status. 9 Table 1.5: Reported Non-regular Sexual Partnership, 1989 (In Percentage) Age Group (Years) 15-19 20-24 25-39 40-49 15+ 50+ Male 57.4 62.5 54.1 59.3 52.6 32.1 Female 25.0 25.3 26.2 30.5 28.4 33.3 Source: KABP Study NAP: KABP/Behavioral Studies - GPA, 1992 (Quoted by UNAIDS, 1999). On the basis of the above analysis, two policy recommendations emerge: * The high rate of HIV infection among young people, especially women under 20 years of age may require a strong educational program, focussed at the onset of sexual activity at the elementary level. * For many women, a major risk may be the multiplicity and frequent change in sexual partnership on the part of their male partners, highlighting the need for a campaign supporting responsible sexual behavior, including the use of condoms, targeted at the adult males. Role of Migrant Labor: The risk factors posed by migrant labor are not limited to the migrants alone but apply to their spouses as well. Analysis of the occupation of reported AIDS cases for 1998 indicated that 23 percent of the sample was miners or former miners, while 29 percent was housewives (Figure 1.8). Although the data do not provide a direct correlation between migrant miners and their spouses, it may be inferred that the high level of AIDS among housewives could be attributed to their spouses (assuming limited multiple partnership among married women). Most migrant workers return home periodically. Since sex outside primary relationship is accepted as almost inevitable in separated families, the likelihood of HIV spread under these circumstances is very high. The situation is further exacerbated by the rise of internal migration resulting from urbanization. Urbanization is also associated with increasing unemployment as employment opportunities in Lesotho have become limited in recent years. A key policy conclusion from the review will thus be: * Since almost half of the reported AIDS cases and new I[V infection may be traced to migrant labor, there is the need to focus on the migrant labor and their farnily with appropriate HIV/AIDS counseling and special support to deal with the implications of the epidemic. Figure 1.8: Reported AIDS cases by Occupation of Patient: 1998 (In Percentage) 10 HIV/AIDS and Denial: A study conducted in 1998 provides an ambivalent perception of HIV/AIDS among the respondents (Box 1.1). The study by Otti and Rasekoai (1998) was undertaken in four districts of Maseru, Quithing, Mafeteng and Thaba Tseka over a period of two months. The selection of the four districts was based on their relatively high incidence of HIV/AIDS. The objective of the study was a qualitative analysis of secondary data, in-depth interviews with respondents, stakeholder analysis and focus group discussion. One of the conclusions of the study was that the widespread denial of AIDS as a health threat in Lesotho calls for an intense information, education and communication (IEC) targeting, while the insensitivity of some health workers towards AIDS patients and the sexual health of the youth needed to be addressed. Box 1.1: Denial of HIV/AIDS in Lesotho One of the surprising findings was, though aware of AIDS, the respondents' knowledge level of HIV/AIDS was very low and to them AIDS was a myth. None of the respondents admitted knowing, seeing or hearing of any Mosotho dying of AIDS - not in their family or in the immediate community but perhaps elsewhere. They all believed AIDS to be a disease of foreigners, which originated from other African countries, among white men and monkeys. The source of information was mainly from the media and peers. The respondents viewed with suspicion government figures on the AIDS situation in the country. They also doubted the validity of the claim by a Mosotho AIDS patient, then involved in the AIDS education campaign, that he was HIV positive. One of the reasons given by the respondents for their doubts, pointed to the healthy appearance of the affected young man, which did not fit with the typical thin and deteriorating profile depicting an AIDS condition in an individual, usually observed on posters and leaflets. For the majority of the respondents, since they were yet to know or see a Mosotho with AIDS, the fear of contracting HIV was almost non-existent. To a few, the threat of AIDS was being exaggerated and at worst AIDS could be another STD and was usually curable. Otti & Rasekoai (1998, p16). D. Conclusions A number of conclusions may be derived from the foregoing analysis on the prevalence and incidence of HIV/AIDS in Lesotho: First, the estimated HIV prevalence rate of 23.6 percent for adults (15 - 49 years) for 1999 may be considered an underestimate of the real incidence of the epidemic in Lesotho. Similarly, the reported AIDS cases of 16,000 by end-December, 1999 may be substantially below the actual cases of AIDS on account of inadequacy in the reporting procedures, limited diagnostic facilities and failure of the health care system to be accessible to all, especially those in the rural mountainous areas. Second, analysis of the characteristics of HIV and AIDS cases from various sources reveals that the epidemic is taking an increasing toll on young people (under 25 years), especially young women. The implications of this factor could be devastating for the labor force and the economic development of Lesotho which depended on supplying labor to South Africa. Third, the gender bias in HIV/AIDS in Lesotho is very damaging. High mobility related to migrant labor, economic hardship and limited employment opportunities, and urbanization have all led to survival strategies that can lead to increased practice of unsafe sex, with young women being most vulnerable. The factors which facilitate the spread of STD and HIV require an 11 enhanced surveillance and preventative programs that address the specific needs of a mobile population. Finally, the surveillance and monitoring system in Lesotho needs improvement. The frequency, randomness and types of surveillance need to improve. For instance, the number of sites for SSS should be increased and the surveys be undertaken on a regular basis. In addition to the sampling methodology being random, information on age, gender, marital status, occupation, and place of abode should be solicited on a regular basis. The data from antenatal and STD clinics should be complemented by periodic surveys with targeted purposes in which much more policy orientated data could be gathered. Improved reporting, both time and quality, would also be required. 12 Chapter II Selected Impact of HIV/AIDS The main and obvious impact of 14IV and AIDS, like all health-related epidemics, is their likely effect on the demography and factor productivity of a country. But unlike other diseases or conditions, HIV/AIDS mainly occurs in the sexually active population, which is also the economically active age group and it is fatal. It is this characteristic that makes AIDS of great concern to economists and planners because it has the potential to reduce the human resources available for production as well as affecting their productivity. Furthermore, under certain circumstances, the demographic changes could also affect savings and investment relations in various sectors of the economy, which could lead to a reduced economic growth. The reduction in population due to AIDS, unlike programs for population control, is unusually damaging to the economy in two fronts. First, while planned parenthood and population programs support the increase of social capital, AIDS death does essentially the opposite. It reduces the size of the economically active population. Second, AIDS mortality tends to impose a "shock" to the household's economic structure since the death of an economically active individual could force changes in size, composition and socio-economic status of the household and in the use of time devoted to building human capital. In the presence of HIV/AIDS, long term planning could suffer when social contracts fail, i.e. sharing of work, human capital development (through schooling) etc. (Menon, et.al, 1998). This chapter deals with selected development impact of HIV/AIDS on the economy of Lesotho, focusing on the likely demographic effect of the epidemic and its implications for the overall availability of labor in the economy, the demand for and supply of manpower in the public sector, and the potential costs to the public sector in its response to deal with these effects. The objective is to outline the key factors that could contribute to reducing both private and public savings, with resulting negative impact on domestic investment and growth. A. The Demographic Impact The following section assesses the impact of HIV/AIDS by considering the demographic variables such as total population size, additional deaths due to AIDS, crude death rate, life expectancy at birth and infant mortality. The impact of HIV/AIDS on the demography of Lesotho is assessed by comparing the projections that make allowance for the impact of AIDS with estimates and projections that hypothetically exclude AIDS. The discussion uses the infornation generated by the SpFectrum Models, with comparative reference to the results generated by other studies (Annex II). Two scenarios are provided, the With-AIDS scenario, which is the basis of discussion, and a hypothetical No-AIDS scenario which is used for the purposes of comparison. Population Size: Figure 2.1 presents the projected population size from 1986 to 2015 taking into account the demographic impact of AIDS as well as the hypothetically projected population excluding the impact of AIDS! The absolute difference between the projected population, with and without AIDS, indicates the cumulative impact of AIDS. The population in Lesotho is estimated at 2.8 million by 2015, about 644,000 fewer or 23 percent lower than it ' The Spectrum Models were developed by the Policy Project, a United States Agency for International Development (USAID) - funded project implemented by the Futures Group International. Two sub-routines, DemProj and the AIDS Impact Model (AIM), were used for the projections discussed in this section. 2 1986 was used as the base year because the population census was undertaken in that year, thus providing adequate demographic information for purposes of analysis at a time when there was very little impact of HIV/AIDS. 13 would have been in the absence of AIDS3. This compares to the estimates by the UN (1998) which shows that by 2015, the population of Botswana and Namibia is expected to be 20 percent lower than it would have been in the absence of AIDS. The projections thus indicate that AIDS is likely to have a very serious relative effect on the population size over the long term, as it is expected that given current parameters, population could decline very rapidly during the projected period.4 The reasons for the expected decline in population growth are the projected rapid rise in new AIDS cases, the limited time from full blown AIDS to death, and the relative low fertility associated with AIDS (Gregson and Zaba, 1998). Figure 2.1: Lesotho - Population Size With and Without AIDS Total Population Size 3,500,000 3,200,000 2,900,000 ,. 2 M600t000 liith I AiDSb 2,300,000 ~ ~ 1,700,000 1,400,000 Mortality Impact of AIDS: The number of deaths from 1986 through 2015 attributable to HIV/AIDS is presented in Table 2.1. Also shown is the projected number of deaths for adults (15-49), infant mortality (infant deaths per 1,000 live births) and under 5 year mortality (deaths of 0-4 year olds per 1,000 live births). The results indicate annual AIDS deaths increasing from 1 in 1986 to over 44,000 by 2015. A closer examination of the data reveals that by 2015, the number of AIDS deaths could exceed the number of adult (15 - 49 years) deaths in the absence of AIDS. Majority of the AIDS deaths is expected to fall on the 15-49 years age group, the most sexually active and in the prime of their productive years. Without AIDS, the annual number of adult deaths is estimated to go up from under 3,857 in 1986 to about 4,699 in 2015; with AIDS, this may increase to 43,569 in 2015, an annual rise of 8.4 percent. AIDS related deaths, on the other hand, may increase from around zero in 1986 to 44,062 by 2015 and exceeds normal deaths by about 493. The likely devastating effect of this phenomenon on the labor market is discussed below. 3 Comparable estimates for Lesotho by the US Census Bureau (March, 1999), indicate a similar lower population by 2010, with a population of 2.445 million compared to 2.745 in the current study. 4The projections do not assume major behavioral changes which is likely to alter the trend in the long term population growth. 14 Table 2. 1: Lesotho - Mortality Impact of AIDS 1986 1991 1996 2001 2006 2015 AIDS Deaths 1 64 2,623 10,148 19,178 44,062 Cu.umAIDS Deaths 1 83 5,966 40,212 117,296 409,421 Adult Deaths a/ WAIDS 3,857 3,325 5,697 12,008 20,509 43,569 NAIDS 3,857 3,231 3,152 3,024 3,565 4,699 Infants b/ WAIDS 90.2 69.7 62.7 56.2 58.0 61.7 NAIDS 90.2 69.7 62.7 55.9 57.2 59.1 Under 5 years c/ WAIDS 132.0 97.2 87.8 83.1 90.4 103.1 NAIDS 132.0 96.8 82.3 68.4 68.4 68.4 Crude Death Rate WAIDS 13.6 11.1 10.7 12.3 15.3 23.4 NAIDS 13.6 11.0 9.2 7.7 7.5 7.4 Crude Birth Rate WAIDS 39.8 39.0 36.9 33.6 30.9 28.0 NAIDS 39.8 39.1 37.5 34.9 32.8 30.8 Notes: a/ Adults defined as 15 - 49 years. b/ Infant mortality rate (infant deaths per 1 000 live births). c/ Under 5 mortality rate (deaths to 0-4 years per 1000 live births) WAIDS = With-AIDS NAIDS = No-AIDS. Crude Death Rate and Infant Mortality: The impact of AIDS on the crude death rate is usually severe in countries with high HIV prevalence. The crude death rate for Lesotho is projected to decline from 13.6 per 1,000 in 1986 to 7.4 in 2015 in the absence of AIDS, whereas with AIDS the crude death rate is projected to reach 23.4 in 2015. That is, by 2015, the crude death rate is projected at approximately 216 percent higher than it would have been in the absence of AIDS. Because of AIDS, the crude death rate is estimated to be 10.9 per 1000 in 1990-1995 and is projected to rise to 13.2 in 2000-2005 and a further 16.5 deaths per 1,000 in 2005-2010. AIDS is thus expected to account for about a one and a half-fold increase in the crude death rate of Lesotho between 2005-15. A contributory factor to the expected high crude death rate is the expected increase in infant mortality. It is estimated that approximately 20 to 30 percent5 of the children born to HIV- positive women is likely to acquire the infection from their mothers. During the period under review, the infant mortality rate is projected to rise much faster than without AIDS. A key reason for this is the assumption that much of the expected decline in the mortality rate for the under 5 years attained over the past decade through public health care programs may not be realized. Figure 2.2 presents the mortality rate for the under 5 years in Lesotho, taking into account the impact of AIDS and in the absence of it.6 A slight decline expected during 1986-92 is negated by the rapid rise in subsequent years as a result of AIDS. It is estimated that mother-to-child (MTC) transmission in Zimbabwe was 20 percent during pregnancy. While 30 percent of the transmission took place during delivery and another 30 percent occurred during breast-feeding (Source: Herald from Zimbabwe July 20, 2000 ). 6 We have assumed no change in the mortality rate for the under 5 years in the No-AIDS scenario. 15 Table 2.2: Projected Under 5 Mortality Rates: with and without AIDS per 1000 population 1986 1991 1996 l 2001 2006 2011 2015 With-AIDS 132.0 97.2 87.8 83.1 90.4 96.0 103.1 No-AIDS 132.0 96.8 82.3 68.4 68.4 68.4 68.4 Population Growth: In view of the above, it is expected that the rate of population growth will decline mainly because of the increase in mortality brought about by the HIV/AIDS epidemic. An increased use of condoms to prevent the spread of HIV could contribute to the decline but this has not been factored into the analysis. In the absence of AIDS, it is projected that Lesotho's population would have declined from the 2.9 percent growth rate in 1986 to 2.7 percent in 1996 (the census year), with further decline to about 2.4 percent by 2015 resulting from sociological changes in the family structure7. With AIDS, the decline is likely to be staggering. Estimated at 2.7 percent per annum in the early 1990s, the growth rate is likely to be 0.5 percent by 2015 in a worse case scenario. Much of the dismal outcome is derived from a higher projected AIDS deaths and a declining crude birth rate, which is projected to decline from 39.8 per 1,000 in 1986 to 28.0 in 2015, on account of AIDS related complications.8 Life Expectancy at Birth: Along with the decline of population growth, life expectancy in Lesotho (which is a basic measure of human welfare) is expected to decline on account of AIDS. Life expectancy at birth measures the average number of years that a newborn child would live if mortality remained constant throughout his/her lifetime. As a result of the increasing mortality due to AIDS, life expectancy has already stagnated in Lesotho and the trend is likely to continue through 2015. Life expectancy is estimated at 52.4 years for 2001, instead of 66.0 years in the absence of AIDS, a loss of almost 13.6 years over the past decade. By 2015, the difference in life expectancy, with and without AIDS, is projected to reach a staggering 31.4 years. This compares with estimates by the US Census Bureau (1999) which suggest that by 2025, life expectancy in Lesotho would be 53 (using a lower prevalence rate than this study). Figure 2.2: Annual Rate of Population Growth With and Without AIDS Annual Population Growth Rate 3.0% 2.8% . 2.6% 2.4% 2.2% I~ ~ ~ ~ ~ ~ ~~~~~~~~~~~~~~~~AD 2.0% s .8% The AIDS it 0.6% 1 0.4% 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 7The US census bureau has lower estimates for population growth in Lesotho than are in this report because a higher adult prevalence rate of 25 percent is employed in this report (see Appendix II). S The projected impact of AIDS on the growth rate in Lesotho is comparable to that for Zimbabwe, where it is estimated that at 3.3 percent annually in the early 1980s, the growth -rate fell to nearly 2 percent per year in 1990-95 and it is expected to decline to less than 1 percent in 2000-2005 (UN, 1998, pg. 34). 1 6 Table 2.3: Lesotho - Estimates of Life Expectancy 1986 1991 1996 2001 2006 2011 2015 With AIDS 55.4 60.4 58,2 52.4 45.8 39.1 34.6 No AIDS 55.6 61.0 63.5 66.0 66.0 66.0 66.0 B. Effect on the Labor and Human Resource Development Apart from directly reducing life expectancy, and through it the size of the overall labor force over time, AIDS also affects the dynamics of skill accumulation in the labor market. AIDS tends to kill prime-age adults, many of whom are skilled and at the peak of their economic productivity. This section focuses on the impact of HIV/AIDS on labor supply and human resource development in Lesotho by estimating how it affects the supply of labor. It focuses on the impact on the public sector staffing. Effects on the Labor Force: Fi ure 2.3 presents the total economically active population in the AIDS and no-AIDS scenarios. The definition for labor employed in the following simulations applies to the economically active population, which includes the employed and the unemployed. Because the economically active group tends to be almost the same as the sexually active group in society, the relative effect of WIV/AIDS is larger among this group than the general population. This is consistent with Table 2.1, which shows that AIDS deaths peak in the 15-49 years age group. Although the growth rate of the economically active population remains positive in the AIDS scenario, it grows slower than in the no-AIDS scenario. This is in part because the estimated infection rate among the economically active population peaks at almost 29 percent in year 2015, compared to an estimated infection rate peak around 18 percent for the total population. In an environment where skilled labor is limited, WIV/AIDS is likely to exacerbate the situation. It is not possible with existing data to analyze the likely magnitude of the skills gap but the next section attempts to highlight the likely impact on the civil service with available data. Figure: 2.3: The Size of the Labor Force - With and Without AIDS Size of Labor Force 1,1o0,000 11000.000 800,000 g 700,000 700,000 , _* .v -> g X i D S~~~~~~~~~~~~~~~~N AIDS 600,000 400,000 . . 300,000 .i ... . Ct . ' 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 20062008 2010 2012 2014 9 The economically active population in the No-AIDS scenario is obtained by adding back the AIDS deaths among the economically active and applying fertility and mortality rates of the total population. 17 Impact on Public Sector Staffing: The 1996/97 Employment and Earnings Survey (UNDP, Undated), estimated that the public sector (excluding parastatals) accounted for about 43 percent of the total formal sector employment of about 72,000 by end December 1996. The survey also indicated that public sector workers received higher monthly average earnings than workers of the private and parastatal sectors.10 If wage levels are a reflection of skill composition, then the public sector accounts for a higher percentage of the skilled labor in the economy. Public sector demand for skills is also greater than other sectors, as illustrated in Figure 2.4. The impact of HIV/AIDS on the staffing of the public sector is therefore likely to provide some insight of the magnitude of the skills gap. Because of the public sector's heavy dependence on institutional memory and establishment-specific training, rapid reduction in its staffing could be devastating. Figure:2.4 Number of Employees by Major Occupational Groups 20000 10000 5U || Private 1000 N ~- Paratatal 5000 ~~~~~~~~~~0 Public 10000-11 A B C D E F G H I J A: Legislators, senior officials and managers. B: Professionals. C: Technicians and associate professional. D: Clerks. E: Service workers and shop and market workers. F: Skilled agricultural and fishery workers. G: Craft and related trade workers. H: Plant and machine operators and assemblers. 1: Elementary occupations. J: Not elsewhere stated. Source: UNDP (Undated), Employment and Earnings Survey 1996/1997 In the Formal Sector, Maseru: ILO, MLE, BOS (Bureau of Statistics). The effect of HIV/AIDS on the public sector is likely to manifest itself in terms of increased morbidity, associated with reduced productivity; and higher mortality which could be reflected in higher pension costs to the public sector. Increased mortality would result in high turnover and loss of continuity. Besides the productivity losses associated with high turnover, the public sector may incur increased recruitment and training costs. Staffing Structure: The Lesotho public service was made up of 36,425 employees in fiscal year 1999/2000, operating in 42 agencies. The sector is dominated by males, which constitutes about 72 percent of the total. Figure 2.5 illustrates the number of public sector staffing by age and gender. It indicates a relatively aging public sector, with close to 40 percent above 55 10 The monthly earning per employee in the public sector was M 2,837, while in the private and parastatal sectors, the average monthly earnings were M 977 and M2,498 respectively. 18 years of age, a structure which is perplexing and may reflect weakness in the existing data. Nevertheless, the aging of the public service may have substantial implications for likely management shortage in the next few years, as well as a sharp demand on the pension system. This is likely to be exacerbated by the negative impact of AIDS as the large share of the remaining public sector employees fall between the 30-45 years age group, which is usually associated with high HIV prevalence rates. Figure 2.5: Public Sector Employment by Age and Gender: 1999/2000 9000 . O s i$ 0e i t>X -+,j$ Xi§4 8000- 7000- _2d" 6000- : 5000- f!aX.: ieRif:f y E 1 n 1 Female 4000- ' f ma 300Q0 *Ml 2000o 0E r Z i I I I I I I C ' Ln~~~~~~d `1O Ln OLn O _ cD -nC Lr,) CD L - (N (N zi L LCn 4N .Jn rl n Estimating the Impact of HIV/AEI)S: In order to examine the impact of HIV/AIDS on the public service, age and gender specific prevalence rates of the national population were super- imposed on the age and gender cohorts of the public service." This approach assumes that the HIV incidence in the public service for these age and gender cohorts is similar to that of the population. This was the best approximation in the absence of HV prevalence data on the public sector. In addition, it was assumed that employment in the public sector will remain constant at the current level of just under 36,500. The public sector population has also been kept stationary in terns of age and gender structure to facilitate the calculation. Table 2.4 summarizes the projected overall impact of HIV/AIDS on the public service. Using the national prevalence rates as a guide, HIV prevalence rates in the public service are expected to rise steadily in the next few years and by 2006 one in every five public service staff is expected to be HIV positive. The projected level of HIV positive in the public sector, although is very high, is nevertheless lower than the projected HIV prevalence rate in the general population. This is because of the skewed age distribution for the staff of the public sector in favor of the 50 years and over age group. The projections indicate that the number of deaths in the public sector that could be attributed to AIDS as a proportion of total deaths is expected to increase from 6 percent in 2000 to almost 60 percent by 2015. This implies that almost two thirds of deaths in the public sector might be due to AIDS by 2015. Nevertheless, reduction in the public sector staffing as a result of AIDS deaths accounts for less than 2 percent of total public sector staff per year. While the displaced staff seems relatively insignificant, the cumulative effect of this over 20 years could wipe out over a third of the Lesotho's existing public service staff in the absence of preventive measures. Potential replacements of skills through the domestic labor market may not be feasible in the short term because of inherent shortages of skilled labor in Lesotho and the likelihood that HIV/AIDS will exacerbate the situation. ' The ASSA model has been used to examine the impact of HIV/AIDS on the public service. This model allows for disaggregation of the population by gender and age. 19 Table 2.4: HIV/AIDS and the Public Sector Year HIV HIV+ Number AIDS AIDS Deaths/ Replacement Positive /Public Staff of Deaths Deaths Public Staff (%) Factor due to (%) AIDS 2000 5,408 15 529 34 6 0.09 2001 5,801 16 542 51 9 0.14 2002 6,179 17 562 76 14 0.21 2003 6,503 18 591 109 19 0.30 2004 6,807 19 629 153 24 0.42 2005 7,079 19 681 209 31 0.57 2006 7,300 20 740 273 37 0.75 2007 7,486 21 807 343 42 0.94 2008 7,617 21 871 413 47 1.13 2009 7,699 21 930 478 51 1.31 2010 7,730 21 980 533 54 1.46 2011 7,707 21 1,016 571 56 1.57 2012 7,671 21 1,035 597 58 1.64 2013 7,602 21 1,040 605 58 1.66 2014 7,524 21 1,032 601 58 1.65 2015 7,439 1 20 1,018 591 58 1.62 It is possible to project the likely level of HIV prevalence in the future. Figure 2.6 examines HIV prevalence rates by age category in ten years time (2010). It is estimated that by the end of the decade the age categories 30-34 years and 35-39 years for males and 25-29 years, 30-34 years and 35-39 years for females will have prevalence rates of over 40 percent. Since these age groups constitute the most productive period in public service, the projected negative impact of HIV/AIDS on these groups will likely to have severe implications for productivity of the public sector. Implications for the Public Sector: Two main implications may be envisaged for the public sector. First, there will be reduced productivity resulting from higher absenteeism and morbidity due to HIV; and second, the cost of running the public sector is likely to increase as a result of the higher demand for pension due to early retirement and death and the cost of rehiring and retraining. With respect to productivity losses resulting from absenteeism and morbidity, it is assumed that for each HIV positive public servant there would be about two staff weeks lost from absenteeism and a week lost for productivity associated with discomfort at work. By applying the weighted average wage for the public sector, it is estimated that cost of absenteeism and morbidity could amount to M 10 million in FYI 999/2000. This constitutes about 1.3 percent of total wage bill (Table 2.5). If it assumed that real wages do not increase through 2015 and the civil service to population ratio is kept constant, the cost of absenteeism and morbidity associated could increase from 1.3 percent of total wage bill to about 1.8 percent by 2015. 20 Figure 2.6: Estimated HIV Prevalence by Age and Gender by 2010 HIV prevalence for the year 2010 by age and gender 50% 40% 30% _ _ _ _ _ _ _ _ _ _ _ 20% 10% 15-iS 2 0-24 2 5-29 30.34 35-39 4 0-44 45-49 50-54 505-59 60 end over Ag e Table 2.5: Staffing Cost of WIV/AIDS to the Public Sector 2000 2005 2010 2015 Reduced Productivity (RP): __________ Total Weeks Lost 21,632 28,316 30,920 29,756 Total Cost (Million Maloti) 10.08 13.20 14.41 13.87 Share of RP to Total Wage Bill ()1.31 1.72 1.88 1.81 Direct Manpower Cost - DMC (M million): Pension Cost 0.34 2.11 5.38 5.97 Rehiring/Retraining Costs 0.48 2.95 7.53 8.35 Share of DMC Total Wage Bill ()0.11 0.66 1.68 1 1.86 Estimating direct costs of AIDS deaths of the public sector is on the other hand more complicated. The direct cost of staff death may be split into three components: pension or gratuity payment to spouse and dependents, hiring costs, and retraining costs. The pensions rule in the public sector in Lesotho identifies different categories of staff according to the type of contract, number of years in service and the level of emoluments. For purposes of analysis, we assume that all officers who have AIDS remain in service until death in order to get benefits for themselves and later on to their families. Under these circumstances, the gratuity payment to spouse or dependents is calculated as the last months salary multiplied by number of years of service divided by two. It is assumed that the average years in service is ten and applying the weighted average salary of M 24,234, we obtain the gratuity/pension payments in Table 2.5. In estimating the cost of replacing deceased staff, it-is assumed that one month's salary would be needed for resettlement. Similarly, it is assumed that six months salary would be required in training costs to bring the competence of new staff at par with deceased staff.12 On the basis of the above, the direct costs of AIDS deaths in the public sector could increase from 0.1 percent of the total wage bill in 2000 to about 2 percent by 2015. In general, both the 12 This is based on estimate by Loewenson, et. al. (1997) for Zimbabwe in 1994 in which training new employees until skills base is replaced is estimated to cost up to six months income per worker. 2 1 productivity loss and the direct cost of HIV/AIDS could amount to close to 5 percent of the total annual wage bill. C. Macroeconomic Impact The impact of HIWV/AIDS on macroeconomic fundamentals is much more complex than the foregoing. Because HIV/AIDS is associated with major transformation of the demographics of a country, including skilled labor configuration, it may be concluded that high and rising HIV prevalence rates and AIDS deaths are likely to have significant effect on production and productivity in the productive sectors and subsequently on growth (Anderson, 1991and others). However, because of the presence of surplus labor and differential wage rate changes, in various labor categories as a result of the epidemic, the choice of techniques in production may likely shift the relative prices of the factor of production and thus the effect on growth becomes ambivalent. From the macroeconomic perspective, HIV/AIDS is likely to affect the savings/investment relations. Since expenditures for mitigating the impact of HIV/AIDS at both the household and public sector are likely to reduce the amount of capital (both public and private) available for more productive investment, the higher the proportion of care financed from savings, the larger the reduction in growth resulting from the epidemic. Modeling the Macroeconomic Impact: In recognition to the above, two approaches have been adopted in the literature. Thefirst uses a growth model extended to incorporate the increase in morbidity and mortality resulting from IWV/AIDS (Cuddington, 1992; Over, 1992, and others). The model incorporates, among other parameters, labor productivity losses and AIDS costs met from reduced savings. The second uses a Computable General Equilibrium (CGE) model in which the labor market incorporates various labor skill categories (Kambou, Devarajan and Over, 1992). Adopting the growth model approach for Lesotho'3, the following factors were considered: * AIDS deaths lead directly to a reduction in the number of workers available by 38,870 in 2015. These deaths occur among workers in their most productive years; as younger and less experienced workers replace experience workers, worker productivity is reduced. It is not clear that the shortage of workers (accentuated by migration to South Africa of skilled labor), will lead to higher wages and hence higher domestic costs. * Lesotho receives a considerable inflow of money from migrant workers in South Africa. This will also decline as migrants become ill and return home. Recruitment of new miners may also be affected as the pool of skilled labor shrinks. * There is the likelihood of lower government revenues and reduced private savings (because of loss of migrant income that fuels imports and greater health care expenditures). This can cause a significant drop in savings and capital accumulation, resulting in a slower employment creation in the formal sector. Based on the above, it is estimated that the presence of AIDS in Lesotho reduces the average real GDP growth rate during the period 1986 - 2015 from 4.4 percent without AIDS to 3.6 percent with AIDS (Figure 2.7)'". This implies that the economy will grow eight tenths of a percentage point percent smaller (or 29 percent smaller) by 2015 because of the epidemic. The 3 It is not possible to construct a CGE model for Lesotho because of data limitations. 4 The assumptions underlying the model are discussed in Appendix II. 22 model assumes that the baseline growth rate will be positive on the basis of past experience and the possibility of other shocks have not been incorporated. The estimates are thus conservative in view of ongoing structural changes in Lesotho that have tended to dampen growth performance' 5 Figure 2.7: Lesotho - Growth of Domestic Product in Constant Prices (With and Without AIDS) Gross Domestic Product 7,500 7,000 - 6,500 V' 6,000 = |NoADS o 5,000 t ;= 2sWIth AlES 0 : 4,500 = _ 3,500 >3,000 2,500 2,000 Comparable estimates for Tanzania suggest that the economy will be between 15 to 25 percent smaller in 2010 because of the epidemic (Cuddington, 1992). Furthermore, a study of 30 sub-Saharan countries (Over, 1992) concluded that the net effect of the HIV/AIDS epidemic is likely to be a reduction of the annual growth rate of GDP of 0.8 to 1.4 percentage points per year and a 0.3 percentage reduction in the annual growth rate of GDP per capita. Table 2.6 summarizes the net effect of HIV/AIDS in Lesotho with respect to GDP growth, per capita income, and investment rates for both the With-AIDS and No-AIDS scenarios. Although the macroeconomic effects of HIV/AIDS do not appear devastating, the impact is not uniformly felt across households. At the household level, HIV/AIDS morbidity and death exacerbates poverty and social inequality. Lower income households will be less able than others to cope with the medical expenses and other impacts, including loss of income. The loss of social capital and the resilience level of the house are two key areas requiring policy focus. Table 2.6: Lesotho - Indicators of Macroeconomic Impact of HIV/AIDS (in Percentage) 2001 2005 2010 2015 GDP Growth Rate With-AIDS 3.4 3.1 2.4 1.3 No-AIDS 4.0 4.0 4.0 4.0 Investment/GDP With-AIDS 29.0 27.9 25.0 19.2 No-AIDS 30.0 30.0 30.0 30.0 GDP Per capita Growth With-AIDS 1.2 1.3 1.2 0.8 _ No-AIDS 1.2 1.3 1.4 1.5 15 Three ongoing developments have substantial implications on medium to long-term growth prognosis for Lesotho. They are: a). continuing decline in migrant workers remittances, b). a fall in the Southern African Customs Union (SACU) receipts and c). reduced scope for Lesotho Highland Water Project (LHWP). Refer to the World Bank (1998). 23 E. Conclusions The following conclusions are arrived at from the analysis of the second chapter: * Long-term demographic impact of AIDS is likely to be significant, for example it is estimated that by 2015, Lesotho's population would be about 644,000 or 23 percent lower (total population 2.8 million) than it would have been in the absence of AIDS. The results indicate annual AIDS deaths increasing from I in 1986 to over 44,000 in 2015. Closer examination of the data reveals that by the 2010, the number of adult (15 - 49 years) AIDS deaths may exceed the number of normal deaths. Majority of the AIDS deaths are expected to fall on the 15-49 years age group, the most sexually active and in the prime of their productive years. As a result of the increasing mortality due to AIDS, life expectancy has already stagnated in Lesotho and the trend is likely to continue through 2015. Life expectancy is estimated at 52.4 years for 2001, instead of 66.0 years in the absence of AIDS, a loss of almost 13.6 years over the past decade. By 2015, the difference in life expectancy, with and without AIDS, is projected to reach a staggering 31.4 years in the absence of preventive programs. * Preliminary analysis of the impact of HIV/AIDS on the labor force, and the likely effect on public sector staffing by skill level was undertaken. Two main implications may be envisaged for the public sector. First, there would be reduced productivity resulting from higher absenteeism and morbidity due to HIV; and second, the cost of running the public sector is likely to increase as a result of the higher demand for pensions due to early retirement and death and the cost for replacement and training of new staff. Productivity losses resulting from absenteeism and morbidity is estimated at M 10 million in FY1999/2000, constituting about 1.3 percent of total wage bill and, the cost of absenteeism and morbidity associated HIV/AIDS could increase from 1.3 percent of total wage bill to about 1.8 percent by 2015. The estimated gratuity payments is also estimated to rise from about M 340, 000 in 2000 to M 6 million by 2015 in real 1999/2000 constant prices. Thus, the direct cost of AIDS deaths in the public sector could increase from 0.1 percent of the total wage bill in 2000 to about 2.0 percent by 2015. In sum, both the productivity loss and the direct cost of HIV/AIDS could amount to close to 5 percent of the total annual wage bill. * The impact of HIV/AIDS on macroeconomic fundamentals is much more complex than with the foregoing. From the macroeconomic perspective, HIV/AIDS is likely to affect the savings/investment relations. Expenditures for mitigating the impact of HIV/AIDS at both the household and public sector levels are likely to reduce the amount of capital (both public and private) available for more productive investment; thus higher the proportion of care financed from savings, larger the reduction in economic growth resulting from the epidemic. It is estimated that the presence of AIDS in Lesotho would reduce the average real GDP growth rate during the period 1986 - 2015 from 4.4 percent without AIDS to 3.6 percent with AIDS. This implies that the economy will grow eight tenths of a percentage point lower (or 29 percent smaller) by 2015 because of the epidemic. This constitutes a projected income loss of about one percent of per capita income for 2000-15. A number of caveats should be in place in assessing the impact of HIV/AIDS: * First, it is important to bear in mind that although the epidemic is already having a clear substantial effect on the demography and economy of Lesotho, its precise magnitude is difficult to determine as there is a general lack of information on many factors that determine the ultimate progression from HIV infection to AIDS and from AIDS to death. Small changes in the assumptions made regarding the progression time would have important effects on the nature of impact expected through mortality. 24 * Second, an area of considerable uncertainty is the level of prevalence among men, since most data on seroprevalence surveillance are obtained from antenatal clinics serving pregnant women. Even with respect to women, data from ANC SSS, which is the basis of national estimates of HIV prevalence, need to be improved to permit a more solid estimation of HIV prevalence at the national level. Despite the uncertainties surrounding any measure of the impact of HIV/AIDS, it is important to underscore that all available data on Lesotho (the ANC surveillance, HIV in STD patients, Hospital surveys, reported AIDS deaths, etc.) buttress the case for concem. The epidemic seems to be spreading rapidly, at least over the past three years. According to the estimates and the projections discussed in this chapter, HIV/AIDS is expected to have a major detrimental impact on the population dynamics in Lesotho, and its impact might turn out to be even worse than expected if effective measures to prevent its continued spread are not undertaken. The development of such measures is the objective of the next chapter. 25 I Chapter III Options for Action Developing a policy response to the epidemic in Lesotho requires cognizance of ongoing public, donor community and private sector activities to mitigate its impact. This approach will permit consistency in action plans to support ongoing interventions and assist to define areas where adequate response is lacking. Section A will review the existing Government policies and programs as well as donor and private sector responses to complement those efforts. Section B outlines proposals to strengthen Governments efforts in three key areas: (i) reducing and containing the transmission of HIV; (ii) prolonging life and reducing AIDS morbidity; and (iii) developing programs for skills replacement. Finally, section C will define areas for further socio- economic research to support HIV/AIDS policy formulation. A. Ongoing Response to HIVIAIDS in Lesotho Institutional Framework: Following the first AIDS case in Lesotho in 1985, a National AIDS Prevention and Control Program (NAPCP) was established in the Ministry of Health (MOH) in July 1987, which ultimately became part of the Ministry's Division for Disease Control and Environmental Health. The unit has been supported by a team of WHO consultants since 1989 and a grant from the UNDP. The program of NAPCP has included epidemiological surveillance of HIV, research on the factors that contribute to the spread of the disease and risk factors, the design and dissemination of health education (materials and messages), training of personnel, improved laboratory diagnosis of HIV, and improved clinical management of persons living with HIV and AIDS. Several coordinating groups have been organized to assist the NAPCP in carrying out its program. A National AIDS Committee (NAC) has been established as a broad-based multisectoral agency to advise MOH on policy and operational matters; an AIDS Task Force acts as a technical advisory body to the NAC; and the Lesotho Network of AIDS services Organization (LENASO) coordinates efforts of several NGOs involved in HIV/AIDS work. PHAL, the umbrella organization for church-operated health facilities, has incorporated AIDS prevention and mitigation activities within the responsibilities of several of its professional staff. While the institutional framework is largely adequate, and in place, program development and execution have had mixed results since early the 1990s: * Considerable progress has been achieved in the decentralization of activities largely because of the efforts of WHO, which worked directly with other arms of MOH and the government. Focal persons in HSA, including counselors have been trained, and health personnel have received HIV/AIDS/STD information. * Although the success of IEC activities for HIV/AIDS prevention is difficult to assess, they appear to have been able to raise the awareness of the general population concerning AIDS. However, since the 1989 KABP study, no recent baseline levels of knowledge, risk awareness, and prevention practices have been defined against which progress could be measured.' The other most noticeable gap has been the failure to intensify the education of 'Nevertheless, a number of different IEC approaches directed at young people have been experimented. Students have been reached by information lectures organized by NAPCP and LENASO; optional Family Life Education (FLE) courses offered by LPPA have been incorporated by numerous schools; and a number of teachers have been trained on HIV/AIDS-related issues by the Ministry of Education. 26 patients being treated for STD. Overall, the direction and strategy for IEC activities in Lesotho is inadequate. * The establishment of the HIV SSS sites is providing program planners with prevalence data from two population groups: ANC and STD patients. However, the program has yet to perform special sero-prevalence surveys on target groups found to be of high risk: migrant workers, commercial workers and their clients, etc. Ascertaining HIV and STD prevalence levels and behavior profiles among risk groups could provide important information in defining core and non-core groups in Lesotho, as well as base-line data for monitoring intervention effectiveness. * All donated blood for transfusion, handled by the Lesotho Blood Transfusion Service, has been regularly screened. Surveillance data also suggests that HIV transmission through contaminated blood is minimal. Of major concern, however, is the lack of counseling services and follow-up provided for individuals giving blood, especially for those with positive HIV results. Strategy and Work Program: The cornerstone of current national prevention, containment and management in Lesotho is provided by three approaches: the formulation of the National AIDS Strategy Plan, the establishment of a multi-sectoral organizational structure, and the development of HIV/AIDS/STD policy framework. The objectives are to maintain sustained political commitment, foster multi-sectoral approach, and provide co-ordination among domestic and external agencies. Key elements of the program are: X Information, Education and Communication (IEC): Recognizing that there is no cure as yet for AIDS and no vaccine probably will emerge in the immediate future, IEC remain the most cost effective intervention for combating the epidemic. Broad themes of the messages include the promotion of positive and responsive sexual behavior, promotion of early STD care seeking behavior, and avoidance of discrimination. All channels of communication (modem and traditional) will be used. * HIV Testing: HIV testing should be done for the purposes of diagnosis, ensuring safe blood transfusion, surveillance and research. Diagnostic testing should be voluntary and confidential, supported by pre-test counseling. * Comprehensive Health Care and Social Support: Appropriate health facility based care for HIV/AIDS patients, including counseling will underlie Government's programs. It is thus intended that the capacity of health and social workers to provide the special care required of HIV/AIDS patients will be strengthened. * Human Rights and Non-discrimination: Recognizing the dangers of discrimination against people with HIV/AIDS that arises from ignorance, misinformation, fear and prejudice, the Government will promote a broad multisectoral response to promote the human rights of People Living with HWV/AIDS (PLWHA). * Research and surveillance: HIV/AIDS-related research will require ethical clearance from the relevant authorities and must conform to international guidelines for biomedical research involving human subjects. The Government intends to encourage partnership between local and international research institutions in HIV/AIDS/STD research. 27 In the light of the above broad guidelines, the Government has also identified specific policies that cover condom promotion and utilization; safe blood supply; HIV/AIDS and the youth, women, homosexuals, and sex workers; STD prevention and control; and WHV/AIDS and breastfeeding, mother to child transmission (MTC), insurance, prison, international travel, orphans, and counseling. A draft National AIDS Strategy Action Plan is under preparation that seeks to define specific activities, beginning 2000 through 2003. The budget for the draft strategic action plan amounts to about M 20 million per year (Table 3.1). Table 3.1: Draft Budget for National AIDS Strategy Action Plan (In Thousands of Maloti) Program 2000/2001 2001/2002 2002/2003 Resource Mobilization 70 40 49 Establishment of Structures 1,060 255 160 IEC Program 1,982 2,173 2,383 Support to Infected & Affected 2,800 3,920 4,730 Youth Information 660 1,240 1,430 Reduction of STD 10,850 10,850 12,350 Surveillance and Testing 824 220 220 Total 18,246 18,698 21,322 Source: Draft National AIDS Strategic Action Plan (Maseru: 2000) B. Proposals to Strengthen Ongoing Initiatives The potential for increased HIV infection levels in Lesotho can be attributed to three factors: (i) likely high prevalence of STD among migrant workers (particularly those returning from South Africa) and teenagers; (ii) increasing prevalence of HIV in surrounding countries, particularly in South Africa where most migrant workers work; and (iii) increasing urbanization that weakens cultural norms in sexual behavior. With the exception of programs directed at youth, specific strategies to address these important variables are now being developed. In view of the above, and building upon ongoing initiatives to deal with the impact of HIV/AIDS in Lesotho, the focus of this section will be (a) reducing the transmission of HIV (prevention), and (b) prolonging life and reducing AIDS morbidity (mitigation). Table 3.2 outlines broad strategies for pursuing prevention and mitigation options. All estimates of cost in this chapter are averages over a 15 year period 2000-15, which gives a longer term planning perspective. The discussion concludes with recommendations for mitigating the negative impact of AIDS on the economy of Lesotho. 28 Table 3.2: Strategies and Options Category Policy Option Implementation I. Prevention Ages 0 - 5 years Close to zero mother to child 100% testing of pregnant transmission. women and encouraged use of antiviral drugs (e.g. AZT, Nevirapine, etc) as necessary. Ages 6 - 10 years Close to zero new infection. Age specific sex education. Ages 11 - 14 years Close to zero new infection. Age specific sex education/ (Childhood) Development of youth activities. Ages 15 - 19 years Focused and monitored Age specific sex (Teenage cohort) reduction in new infections. education/youth counseling/community condom distribution, reward for good behavior, part time employment. Ages 20+ years Reduction of new infection Work place condom (Adult) through behavior modification distribution, free and and safe sex. voluntary counseling centers, information dissemination through media, religious groups and indigenous groups, and stage performances/talk shows using PLWHA. Risk groups Special programs for targeted Same as 20+ category with groups such as miners and emphasis on counseling and commercial sex workers. anonymity. H. Mitigation __X___ Ages 0 - 5 years Improved quality of life. Medical care. Ages 6 - 14 years Community based orphan Educational, medical care and (Childhood) care. food programs through school. Ages 15 - 49 years Improved quality of life/ HIV counseling/medical Prevent further spread care/community & work place condom distribution/community home based care. Ages 50+ years Improved quality of life Medical care/ Pension I__________________________ ________benefits. Reducing the Transmission of IEIV: Policies aimed at reducing the transmission of HIV has to be directed at two main groups, with substantially different approaches. The two groups are the youth (under 15 years) and the sexually active population (15 - 49 years). Policies focused at the youth under 15 years should aim at Close to zero new infection. While this target is ambitious, it is attainable under appropriate environment involving participating parent/youth involvement. This group is not yet sexually active or only at the onset of sexual activity. Two specific focused policies could be implemented on this group, recognizing the possible sources of transmission: 29 * Age group 0-5 years: MTC of the HIV virus could occur in new born children in three ways: during pregnancy, delivery or breast feeding. In the case of Zimbabwe MTC is estimated at 20 percent during pregnancy, while 30 percent transmission took place during delivery and another 30 percent occurred during breast-feeding2. Existing medical knowledge suggests that if drugs, such as AZT or Nevirapine, are provided to pregnant mothers, the transmission rate could be reduced significantly. There are side effects associated with these drugs such as toxicity and resistance. But two doses of the drug Nevirapine, one to mother and one to child, it is reported, can reduce MTC by 35 to 40 percent. Unit cost of AZT is approximately US$150 or M 900 per mother, which is more expensive than Nevirapine which costs about US$8 or M50 per treatment3 of two doses, one to the mother and one to the child. * Mothers and Infants: There are about 122,000 females in the child bearing age group. If it is assumed that 15 percent of them would become pregnant, the estimated number of pregnant mothers would be around 18,000. The potential risk group in this category is estimated at about a fourth at 4,5004. The total cost per year for a zero MTC using AZT is therefore M 5 million (about 2.6% of health budget) or alternatively M 270,000 using Nevirapine (about 0.1% of health budget). * Children: Children in the age groups 6 months to 5 years need regular checkups and shots to keep good health. They need to be watched since not all mothers with HIV are tested. This age group constitute about 111,700 and the estimated cost per child group is about half of per capita health expenditure (M 46). The total cost is M 5 million or 0.1% of GDP. * Age group 6-10 years: For this age group early sex education would be the best preventive policy. These young children are the most important group to protect since they are not effected by the epidemic yet. There are 350,000 in this age group. Estimated cost per child is a fifth of per capita education expenditure or M 42 per year. Total average cost M 15 million per year or 0.3% of GDP. * The 10 - 15 years age cohort constitutes a group on the onset of sexual activity. For this group adequate sex/health education which is tailored appropriately to their age and capacity to enable them to deal positively and responsibly with their sexuality is the first approach. The program should deal with both abstinence and condom usage at the appropriate time. Based on assumptions about the framework for such a program', it is estimated that an expenditure of M 17 million will cover 332,900 beneficiaries. This amounts to about 0.3% of the GDP. The latter requires aggressive, accelerated and intensive IEC and peer education efforts targeted at the youth in order to facilitate individual assessment of risk and behavior change towards prevention. Parental/Youth participatory involvement with the assistance of the community and NGOs/CBOs may be necessary. A successful publicity campaign focussing on the youth with effective IEC messages can prevent HIV transmission over the medium term. These efforts will require support from behavioral and epidemiological research to determine the characteristics of the youth contributing to high risk. 2Herald Daily News paper from Zimbabwe, July 26, 2000. 3CNN: http://cnn.com/SPECIALS/2000/aids/stories/treatment. 4Herald Daily News paper from Zimbabwe, October 3, 2000 At least a quarter of all expectant mothers in Mutare are infected with HIV virus according to a survey. s Age group 10-15 consists of 290,000 in 2000 and projected to increase to 360,000 by 2015. Cost of these activities is estimated at M 500 per person per year. 30 There is growing evidence that sexual activity among the youth is widespread, yet most health and educational institutions ignore their needs, resulting in unwanted pregnancies and an alarming prevalence of STD. If the Government does not yet feel ready to promote openly youth counseling activities, it should at the minimum continue to encourage and assist those agencies and NGOs which do, in order to ensure that such services are available nationwide. This would entail the need for an expansion of facilities to provide appropriate space for counseling and for educational films and informational materials. Such facilities, provided in conjunction with play ground and sporting game facilities, will help facilitate fruitful use of free time by the youth. Toward the goal of providing comprehensive health care for the youth, the existing efforts to provide family life education to secondary school student should be targeted at primary students as well. With 33 percent of primary school students older than 12 years of age (1986 Census) and several of the under 12 years also found with HIV, suggest that some students probably begin sexual relations while still in primary school. Focusing primary school students with HIV education is a very difficult task that will require parent/teacher and health workers to work collectively. The second group involves the sexually active population (15-49 years). The policy objective for this group is to promote increased and consistent condom use for the sexually active population. A key policy for reducing new HIV infection is the promotion of condom usage. A framework of logistics and management information system for condom supply and promotion already exists but they need to be pulled together and adequately monitored. The main problems which persist include inadequate appreciation by HSA management and staff of the importance of maintaining user statistics and using these to determine future requirements; the absence of a tracking system which signals low stock levels; and the availability of too wide a range of contraceptive types and brands, as a result of the high reliance on donor funding. In this context, it is suggested that Government should: * Ensure adequate condom supplies: The MOH relies too heavily on donors for the funding of condoms. It is essential that funding be identified to meet requirements two to three years into the future if reliable supplies are to be assured. It is assumed that (male) youth in the age group 15-19 require 2 condoms per week or 156 per year and adults require 4 per week or 234 per year. The number of youth 15-19 year age group is estimated at 155,555, and 20+ age group at 518,550. Total estimated cost per year for condoms for all youth 15-19 age group is M 24 million or 0.5% of GDP; for adults it is M 121 million or 2.4% of GDP.In the absence of donor assistance, the Government must be in a position to ensure that funding will be available from the budget. To support the process, the Government should explore the concept of social marketing of condoms. Evidence in Zimbabwe and elsewhere indicate that people are willing to pay for condoms. * Enhance NGO support for condom distribution: The extent to which HIV/AIDS counseling and condom distribution services are offered differ markedly between Government and that of the PHAL and NGO facilities. This suggests that Government needs to increase its efforts to enlist non-governmental institutions in its efforts. For example, the limitations of the Roman Catholic health services from providing artificial methods of family planning constrain the access of people within those service areas to condom for HIV prevention and associated information. * Provide community based and work-based services: Experience worldwide has demonstrated that the use of alternative delivery systems, such as community-based delivery of condom can increase usage, even in inaccessible rural communities, as are found in Lesotho. With a pool 31 of Village Health Workers (about 5,000-6,000) and Traditional Birth Attendants (about 2,000), Lesotho has the potential to extend HIV prevention in the rural areas at a relatively low cost. Work-based condom distribution and HIV education programs may require active participation of management and appropriate allocation of required budget. IEC, voluntary testing and counseling: It is extremely important to provide voluntary testing and counseling (described in detail in the following paragraphs) for prevention purposes. For the 15-19 year age group it would cost about M 32 million to cover 304,000 male and female youth at a rate of M 104 per person (which is about half of the per capita education budget). The comparable estimate for adults is M 96 million that covers an estimated 1.158 million people at an average cost of M 83 (which equals one fourth of per capita education budget plus one third of per capita health budget). Prolonging Life and Reducing AIDS morbidity: Because HIV/AIDS is stigmatized, affected people are often prevented from gaining access to some of the few social support mechanisms for which they might be eligible. Programs to mitigate the household impact of HIV/AIDS therefore should deal with legal concerns, voluntary IRV counseling and testing, ration of health care, and the role of home-based care. The legal environment plays a substantial role on issues relating to the rights of women, marriage laws, inheritance and property, contraception, abortion and prostitution, all which impact on resources available to the AIDS patients. A dual legal system exists in Lesotho, as in many other parts of Africa, with customary (or traditional) law existing side by side with Roman- Dutch common law. The criteria by which courts decide which law is applicable have become shallow over the years and largely impacted by the social status of the relevant litigants. Nevertheless, it is the impact on the status of women that is of immediate importance in the context of mitigating the effect of HIV/AIDS. A number of factors may be highlighted: Although the presence of Roman-Dutch law might, in theory, have given women more legal rights that they are accorded under customary law, in practice women are discriminated against under both legal systems. The Masotho woman under customary law is considered under the guardianship of her father from birth until marriage, at which time she becomes the responsibility of her husband. Upon her husband's death, she comes under the control of her eldest son, if any, or of the husband's male heir. Should she never marry, she would remain under the responsibility of her father, or his male heir. Under common or civil law, legal majority is accorded to single women above the age of 21 years. With marriage, however, a woman would normally come under her husband's marital power and be considered a legal minor.7 The legal minority of women has several consequences: it reduces a woman to a subservient position in society vis-A-vis that of a man, with the result that her capacity to have an effective say in matters of consequence to her, including the number of children she will bear or the use of condoms, is compromised. Under customary law, women have no legal right to enter into contracts, no right to own property and no right to sue or be sued. The resultant economic dependency of women not only constrains them in realizing their productive potential but also compromises their influence on the family with regard to fertility decisions and thus undermines the gains one would normally expect from their relatively high education status. 6 Women in rural areas would normally be considered, and consider themselves, as subject to customary law. 7 Common law recognizes, however, the validity of an ante-nuptial contract entered into by both parties, which can conceivably exclude the husband's marital power and thereby enable the woman to have a legal capacity equal to that of the man. 32 Because the inferior legal status of women can negatively impact on self image and willingness to assert themselves, even in matters regarding infection, it is recommended that all existing legislation - under both customary and common laws - be reviewed systematically to determine those provisions which erodes women's legal status and equitable treatment under the law.8 Changing existing laws will undoubtedly take time. The Government should thus mount a program that will ensure women are made aware of their rights under existing laws, and educate society in general as to the benefits likely to accrue to the society if women can make decision to prevent HIV infection. Voluntary counseling and testing can play a useful role in helping individuals with HIV/AIDS to seek assistance in dealing with the epidemic. Active public promotion could also serve as an instrument in assisting potential AIDS patients and serving as a prevention measure for controlling risk behavior. Studies conducted in Malawi (1998) indicated that, males who received voluntary counseling and testing reported a decrease in unprotected sex from 30 percent to 18 percent, compared to males who only received health information who reported a decrease from 30 to 26 percent. Counseling on HIV can be useful in decision-making on a variety of areas - from prevention to care. Testing however, helps to solve the issue of uncertainty in that a positive test serves as a strong incentive for the use of condom, while a negative test may help to reinforce responsible sexual behavior. The role of counseling and testing is to handle the psychological aspects of HIV/AIDS, but may serve as a useful instrument for finding individual solution for prolonging live and reducing AIDS related morbidity. Counseling and testing sites need to be established in each urban center, with special facility devoted for returning miners. In an environment of high AIDS cases, the inevitable increase in demand may lead to the rationing of health care, mainly on the public hospital sector. Figure 3.1 shows the projected increase in hospital bed-days attributable to AIDS. It is possible that in a constrained resource environment, non-HIV related patients would experience a greater degree of rationing than AIDS related patients. In other countries (e.g. Botswana), close to about 60 percent of hospital beds are already being allocated to AIDS-related patients. The options are either to increase the number of hospital beds or to seek alternatives to hospital-based care. The challenge is for both the public and the private sectors to shift to fundamentally more cost effective mode for terminal care. In this connection, a widespread adoption of cost-effective program such as home-based care may be recommended. The type of home-based care envisaged in Lesotho will not be limited to only AIDS patients but also to all terminal patients. It will aim at providing a range of services (clinical and nursing care, counseling and social support) extending from home to hospital and different levels of health facilities, all linked by discharge planning and referral network. Besides being cost-effective in reducing case load at health facilities, home-based care is likely to promote positive outlook for terminal patients and enhance the capacity for preventive education for other members of the extended family. ./ s Many such provisions have been identified by the National Organization of Women Lawyers in Lesotho. 33 In order to widely promote the concept of community home-based care, there is the need for a comprehensive study to address the following: * Feasibility issues concerning the availability and adequacy of staffing, transport, supervision and drug supply arrangement. Furthermore, the acceptance of the concept by the community and households would need to be ascertained. * Detailed work would need to be done concerning the number of patients that would be covered, frequency of visits, type of home visitor (e.g. Family Welfare Educator, nurse or both), and the nature of administrative support, including the staffing of clinics to support home visit. * Home-based care lowers costs of inpatient care. It should be noted that home based care works in a more organized and densely populated urban setting but it is more complicated in rural areas due to the distances to be covered by any supporting outreach services. Figure 3.1: Hospital Bed Days Needed for AIDS Patients Hospital Beds Days Needed for AIDS Patients 3,500,000 3,000s000 2,500,000 tNon-AIDS 2,000,000 mAIDS 1,500,000 1,000,000 500,000 Mitigating the Negative Impact of AIDS on the Economy: Policies to deal with the negative impact of HI V/AIDS would need to focus on (a) strategies for human resource development (replacement of lost labor and skills), and (b) preserving savings and investment levels. These policies would need to apply at the household, enterprise, and public levels (both sectoral and national). Human resource development efforts must aim at replacing lost skills and ensuring adequate pool of skills. Lesotho is generally skilled labor deficient in that a large number of trained people leave the country. The impact of HIV/AIDS is to exacerbate the shortage of skilled labor, especially in the public sector where most trained personnel are employed. Salaries, benefits and other incentives to retain skilled people have not been sufficient in the past. Because the negative impact of AIDS on skilled labor is likely to be regional, out-migration from Lesotho will probably increase. 34 Dealing with the skilled labor shortage in Lesotho may require information as well as incentives. In the area of information gathering, there may be a need for a census of skills both in the private and public sectors. Such a census may be followed by projections and plans of skills needed at sectoral level that may be necessary for developing and incentive program for the private sector. Private sector incentives could be in the form of tax rebates for retraining programs. The need for skill replacement is likely to be more important for the public sector than the private sector. The public sector may need to identify critical areas for the preservation of skills. There may also be the need to intensify staff development programs, training and public/private partnership in these areas. Using data on the estimated deaths in the public sector due to AIDS, it is estimated that M 0.48 million in year 2000, rising to M 8.35 million by 2015, may be needed to deal with retraining and replacement of staff. Related to the skills replacement needs of the economy is the role of AIDS death in increasing the number of orphans. The estimates suggest that the number of orphans (loss of mother or both parents) in Lesotho will increase from an estimated 19,070 in 2000 to about 152,985 by 2015. As of 1999 there were an estimated 15,000 orphans and every year 5,000 to 8,000 on average would be added to this pool. An orphan status has major implications for the growth of the child and human capital development. Orphans tend to feel low sense of self esteem and in the absence of appropriate programs could lead to abuse, neglect and a life of crime both as a child and adult. It is estimated that a comprehensive incremental orphan care in Lesotho would cost about M 67 million per year or 1.3% of GDP, Dealing with the orphan problem may require studies that address the following options: * Given the resource constraint of the extended family, orphanages provide an option that has been used in western countries. * Home based orphan care in the community, especially in the rural areas, provide an alternative similar to the home based care in which support is provided to the extended family in kind. The intervention is in the form of advice and counseling to the extended family. * Complementing the home based orphan care is support for schooling and the establishment of income generation projects to provide employment for orphans exiting from the school system. The proposal for home based orphanage could be developed in the context of the home based care for AIDS patients. The rationale for this is that during the period before the death of AIDS parents, older siblings and other members of the extended family who provide care for the sick tend to withdraw from the labor market with major implications for household income. The most affected are children who tend to be neglected and may withdraw from the school system even before they become orphans. An expanded home based system incorporating care of the terminally ill and assistance for potential orphans may provide the most cost effective means for dealing with both problems. Costing such a program should be the objective of further study. The costing of the proposed initiatives are summarized in Table 3.3 (with necessary assumptions outlined in Annex III). The preliminary estimates suggest that the various elements of prevention could amount to between 0.1 to 6.2 percent of GDP per year. In terms of mitigation, orphan care is estimated at about an average of 1.3 percent of GDP per year. The largest single cost element is hospital care, which is estimated at about 13.6 percent of GDP per year, on average, during 2000-2015. The latter points to the need for alternative programs for handling AIDS and terminal care. Although these may underestimate the likely cost of 35 prevention/mitigation activities, they point to the likely magnitudes and suggest that such programs can be accommodated by existing resources of Government. The loss of GDP associated with HIV/AIDS is estimated at, on average, M 560 million per year in constant terms, or about 10 percent of GDP in the absence of HIV/AIDS during 2000-15. If the country is loosing such a magnitude in potential GDP, it should be able to contain these losses by appropriate prevention programs that arnounts to less than 6.5 percent of GDP per year. On the other hand, since mitigation costs are substantially higher than the loss of GDP, it is prudent that Government intensify preventive measures. Finally, policies to reduce the cost of both preventive and mitigation programs are warranted. Table 3.3: Summary of Estimated Costs of Selected Policy Interventions Cost per year % GDP % GNP Category (Million Maloti in 1999/2000 prices) I. Selected Prevention Support for MTC transmission 5 0.1 0.1 (Age cohort: 0-5 years) Sex Education, & Community Programs 32 0.6 0.5 (Age cohort: 6-15 years) Sex Education for Teenagers 56 1.1 0.8 (Age cohort: 15-19 years) Increased Condom Use 121 2.4 1.8 (Age cohort: Adults) IECNoluntary testing/Counseling 96 1.9 1.4 II. Selected Mitigation Orphan care 67 1.3 1.0 Hospital care for AIDS patients 708 13.6 10.6 Old age pension for AIDS patients 21 0.4 0.3 C. The Need for Further Research A key limitation of ongoing study on the development impact of WV/AIDS is the constraints posed by existing data. Dealing with the data constraints will require identifying areas where the impact is severe and conducting appropriate studies. Three areas may be identified. The impact of BIEV/AIDS on the household: The microeconomic basis for the development impact of the epidemic indicates substantially more damaging implications at the household level. Furthermore, prevention and mitigation programs require more information than currently available. A household level survey focusing on impact of HIV/AIDS on household consumption (expenditures), labor supply, and coping mechanisms could provide valuable information for 36 designing appropriate response to the epidemic. Furthermore, such a survey can provide behavioral indicators that may be useful for developing preventive messages9. The impact of HIV/AIDS on the civil service: This will be required to deal with programs for recruitment and personnel management. While the broad parameters dealing with the impact on the civil service in Lesotho has been identified in the present study, detailed analysis would need to deal with the skill profile of the public service and the long term implications on the pension systems. Analysis on the likely impact of the HIV/AIDS on the cost structure of the administration will also provide the opportunity to revisit the role of the public sector and to redefine its role to accommodate the effects of the epidemic. This may require a public sector comprehensive census with a possibility for selective testing. Integration of HIV/AIDS into Planning Models and Decision Making: This will require building capacity at two levels. Thefirst may require the application of user friendly impact models at both the macro and sectoral levels. Such models, as planning tools, will provide estimates of the impact of AIDS on the supply of inputs (or resources) into production activities at various levels and sectors of the economy. It will deal with the training needs, recruitment, sick-leave, deaths, health expenditures, life insurance and benefit packages for each sector (and unit) within the economy. The analysis will essentially be a costing process (similar to those undertaken in this study) which will ultimately be incorporated into the annual budget process. This activity may need to be supplemented by a general equilibrium type modeling. Thesecond level of capacity building will involve equipping each agency within a sector to integrate IIIV/AIDS prevention and mitigation efforts into its operations. This activity is within the operational budget of each agency and involves the development of workplace voluntary counseling systems and information sharing. 9 Selected survey of this type is already taking place in Uganda with support from USAID and experts from Johns Hopkins University and Medical Hospital. 37 BIBLIOGRAPHY Ainsworth, Martha, Lievefransen, & Mead Over (Ed) (1998), Confronting AIDS: Evidence from the Developing World, Selected background paper for the World Bank Policy Research Report, Confronting AIDS: Public Priorities in a Global Epidemic, Brussels: European Commission & D.C.: World Bank. Alan Whiteside and Greg Wood (1994) , Socio-Economic Impact of HIV/AIDS in Swaziland, Mbabane: Min. of Economic Planning and Development Bureau of Statistics (1989), Basotho Women and their Men: Female and Males in Lesotho, Maseru: Ministry of Economic Planning. Everold N. Hossein (1999), A National Crisis Communication Strategy for Reducing the Spread of HIV/AIDS in Swaziland Gregson, Simon, and Basia Zaba (1998), Measuring the Impact of HIV on fertility in Africa, AIDS (London) Vol. 12, Supplement 2, pp. 541-550 Gill, D. (1994), Women in Disadvantage in Lesotho, Maseru: Sechaba Consultants. Kalilani, J. A. (1998), Results of AIDS Questionnaire in Machabeng High School, Maseru: WHO (Unpublished). Kingdom of Swaziland (1994), AIDS Issues Paper: Socio-Economic Impact HIV/AIDS in Swaziland, Prepared by Alan Whiteside and Gref Wood, Capricorn Africa Economic Association, Mbabane Lesotho Distance Training Center (1989), A Study of Knowledge, Attitudes and Practices of Basotho Regarding Tuberclosis, Leprosy, AIDS, Syphilis, Gonorrhea, Breastfeeding and Family Planning, Maseru. Matobo, T (1992), Basotho Mineworkers Sexual Practices, Maseru: National University of Lesotho. McMurchy, D. (1993), The Economic Impact of HIV/AIDS in Lesotho, Direct and Indirect Costs: 1993 - 1998, Maseru: WHO Ministry of Health (1993), Preliminary Results on Knowledge, Attitudes and Practices on Sexuality, STD/AIDS Among High School Students and Teachers, Maseru: Disease Control and Environmental Health Division, STD Prevention and Control Program, February Otti, P. N. and M. Rasekoai (1998), A Socio-cultural Study of HIV/AIDS in Lesotho, Maseru: UN Theme Group on HIV, June. Rapolaki, M. E. (1992), Income Inequality and Fertility Patterns in Lesotho, Maseru: Ministry of Planning (Mimeograhed). The Kingdom of Swaziland (1993), Work Plan and Budget (1994/95) - Second Medium- Term Plan for the Prevention and Control of WHV/AIDS and Other STDs among the People of Swaziland; Mbabane 38 Swaziland Government (1991), Swaziland - National AIDS Prevention and Control Program - Review Report, Mbabane, March, 1991 The Kingdom of Swaziland (1995), Review Report: External Review of the Swaziland Government (1991), Swaziland - National AIDS Program, Mbabane - July 1995 UN (1998), The Demographic Impact of HIV/AIDS, Report of the Technical Meeting, New York, 10 Nov 1999 (UN, Population Division, Dept. of Economic and Social Affairs). U.S. Census Bureau (1999), World Population Profile: 1998 Report WP/98, U.S. Government Printing Office, Washington D.C. World Bank (1997), Confronting AIDS: Public Priorities in a Global Epidemic, World Bank Policy Research Report, Oxford University Press. World Bank (1998), AIDS Assessment Study, Report No. 17740MAL (Volumes I & II) World Bank (1998), African Development Indicators, Washington D.C. World Health Organization (1990), Final Report on Knowledge, Attitudes, Beliefs and Practices on AIDS, Maseru: NACPP/MOHSW. 39 Annex I The Result of the Lesotho Hospital Based HIV Seroprevalence Survey Introduction Background: All Health Service Areas (HSA) in Lesotho were encouraged to participate in the Seroprevalence survey conducted during October - November, 1999 with the assistance of WHO and the Ireland Aid. Pre-specified sample sizes were allotted to the different HSA according to patient turnout at the different collection points. The confidentiality requirement and anonymity behind HIV testing means that patient consent is required to take blood samples for MV testing. This was both a very difficult practical and ethical issue to overcome. Hence a random sample of patients at the different collection points was not possible. An alternative sampling process was adopted. Unlinked anonymous serum testing was used. The only information required was the name of the Health Service Area, the patient's age, sex and occupation plus the provisional diagnosis. This ensured confidentiality for the individual patients. Part of blood already taken from patients for investigation of other conditions was used. The need for pre-test counselling was therefore obviated. Limitations: This sampling process itself can be considered to bias. First, hospital patients are sick, and therefore not representative of the general population. Second, blood samples taken for illnesses/conditions such as TB/pregnancy which themselves are either immuno-suppressive or states of health which are likely to be closely related to higher unprotected sexual activity and hence could bias the results upwards. Furthermore, women tend to use health facilities more than men do. Hospital based surveys such as this are therefore bound to indicate a disproportionately high female preponderance. As long as this is not misinterpreted as women being at a higher risk for the condition under survey, it does not affect the overall outcome. There were also methodological weaknesses relating to timing and sample size The one month during which the samples were collected could be seen to restrictive on the sample size given the difficulty of response. Furthermore, the sample sizes for participants under 15 years of age and above 70 years are very small. Sample Characteristics: In order to get a better understanding of the data, this section provides a demographic profile of the survey data. This data covered the following variables: health service areas (HSA), age, gender, site, occupation, diagnosis, and HIV status. The hospitals which participated in the survey operate within the respective HSA. Out-patients account for 51% of the sample. The second largest site are ante-natal clinics which by definition are only frequented by women. This also partially explains the over-representation of women in the survey. Although every attempt was made to encourage the participation of the different HSA, responses from some were very poor ( Table 1). Women are indeed over-represented in the sample as they account for 77% of the sampled patients. This over-representation can introduce a bias in the results. ' This annex is based on the data generated by Kalilani (1998). It was put together by Bala Rajaratnam (Consultant) with extensive support from Dr. Givans K. Ateka. The assistance by Dr. Ateka and Dr. Kalilani (both of WHO, Lesotho) are gratefully acknowledged. 40 Table 1: Sample Frequency by Health Service Area HSA Sample Response % Resp. HIV+ HIV - % HIV+ Berea 800 491 61 197 294 40 Butha-Buthe 800 773 97 308 465 40 Leribe 1000 1012 101 322 690 32 Mafeteng 1000 997 99 320 677 32 Maluti 800 438 55 157 281 36 Mamohau 400 175 44 48 127 27 Mantsunyane 400 219 55 54 165 25 Mohale's Hoek 800 809 101 286 523 35 Paray 400 202 51 72 130 36 Qacha's Nek 400 236 59 144 92 61 Queen Elizabeth 11 1000 20 2 8 12 40 Hospital Quthing 800 536 67 173 363 32 Roma 600 122 20 38 84 31 Scott 600 358 60 130 228 36 Seboche 600 601 100 171 430 601 Tebellong 400 67 17 12 55 18 Total 11200 7056 63 2440 4616 35 As discussed earlier, the survey under-represents children (0-14) and the elderly (70 or more). Figure I illustrates that sample sizes within these age groups are too small to make concrete statements. Figure 1: Age distribution in the Sample WHO survey: Age distribution 1600 ,400 1200 Sooo L .iI. 80 0 0 400 200 Age group 41 II. Estimation Methodology This sections deals with the methodology employed to correct the sample limitations in the survey. Table 2 outlines the key deficiencies and establishes ways in which some of the more important weaknesses can be corrected. These include the reconstruction of a random sample, the introduction of weights to remove design deficiencies and discussion on the weighting procedure. Table 2: Summary of Methodological Weakness and Corrective Measures Methodological Explanation Solution Weakness 1. Time limitation This implied having to contend with smaller Outliner analysis sample sizes than would have been desired. Establishment of confidence intervals The small sample size gives rise to higher Comparison with estimates from variability which in turn could give rise to previous studies more imprecise estimates Graduation techniques 2. Over The study does not control for gender, age or Weighting will remove the design representation of HSA catchment area. The implication of this bias. The national population census women is that a simple HIV prevalence rate is needed for this. 3. Variability in essentially constitutes a biased estimate for the sample sizes for the population prevalence rate Since certain age groups are not different HSA adequately represented for example 4. Under- those under 15 and over 70 - the representation in findings should not estimate HIV certain age groups seroprevalence rates for these groups 5. Being hospital This is perhaps the most serious So essentially, the sample does not based methodological weakness of the study. By represent a random sample of being hospital based, the survey samples a set Lesotho's population. However, of individuals who do not represent Lesotho's there is a way in which a random and entire population adequately. This is true as representative sample can be those without any illnesses or ailments are not constructed/derived from the original represented at all. In fact the participants in data. The WHO survey data also has the WHO survey better represent hospital the provisional diagnosis for each goers in Lesotho of whom large proportion patient. Each of these can be either may be HIV positive. As discussed above, the classified as "Not opportunistic", sampling process could be biasing the results "Opportunistic", or "May be upwards. The bias originates from two factors: opportunistic". Those with diagnosis 1. Only hospital-goers have a chance to be "Not opportunistic" are in fact a picked for HIV testing. This removes the subset of hospital goers and can be non-hospital going and healthy regarded as a representative sample individuals from being included in the of Lesotho's population. sample 2. Moreover, only those with diseases/illnesses which require giving blood can be tested. Those who visit the hospital but are not required to give blood are automatically excluded from the sample. If those illnesses which require - giving blood are either immuno- suppresive or related to higher sexual activity, then these by design have a higher likelihood of having HIV/AIDS. This could of course lead to much higher prevalence rates than those in the general I_ _ population 42 Reconstruction of Random Sample: This section outlines how a random sample is reconstructed from the survey data. This is based on the provisional diagnosis for each patient. The diagnosis of each patient can be classified as either "not opportunistic", "opportunistic", or "may be opportunistic" according to the nature of the illness/ailment (appendix). This is assembled in Table 3. Discarding those who are classified as "opportunistic" and "may be opportunistic" yields a reasonably random sample, which is made up of approximately 84% of the sample population. This is further supported by evidence which indicate that HIV prevalence rates for opportunistic disease is as high as 63%, 51% for those which could be potentially opportunistic and 30% for those which are classified as "not opportunistic". Patients classified as "not opportunistic" are in fact a subset of hospital goers and can be regarded as a representative sample of Lesotho's population. Table 3: Distribution of Sample by Type of Diagnosis HIV-Link Total % Share HIV Positive HIV Negative °% of total May be opportunistic 617 9 51 49 100 Not opportunistic 5929 84 30 70 100 Opportunistic 512 7 63 37 100 Grand Total 7058 100 35 65 100 Introduction of Weights to Remove design Weaknesses: A possibility for the bias is the unintended design effect brought about by the over-representation of women in the sample. On the other hand, the young and elderly are underrepresented. The unintended design effects also spills over to inaccurate representation of districts and health service areas. The unintended design effects can be corrected by weighting using data from the population census. The 1996 National Population Census for Lesotho provides population estimate by district and gender. Table 4 indicates that districts such as Maseru and Leribe are more heavily populated than the other districts. Since Mokhotolong did not participate the hospital survey, adjustments were made accordingly2. Other complication arose from the small sample sizes in Qacha's Nek - which was resolved by grouping strata. A similar process was followed for Tsaba-Tseka. Table 4: Population Size by District and Gender in Lesotho - 1996 District Male Female Total Butha-Buthe 53,920 55,272 109,192 Leribe 146,729 153,431 300,160 Berea 117,703 123,051 240,754 Maseru 186,481 199,388 385,869 Mafeteng 104,625 107,345 211,970 Mohale's hoek 90,073 93,961 184,034 Quthing 61,342 65,000 126,342 Qacha's Nek 34,389 37,276 71,665 Mokhotlong 42,260 43,368 85,628 Thaba-Tseka 61,844 64,310 126,154 Not specified 199 Total 899,366 942,402 1,841,967 2 This implies that the weights sum to the national population census estimate for 1996 minus the population for those strata which were excluded due to non-coverage 43 Once population and sample counts were established for each of the strata, the weights were determined as the reciprocal of the sampling fraction within each stratum. The above approach deliberately avoids weighting by HSA, and is regarded as more appropriate as the sample sizes within some of the HSA are too small. Additionally, confidence interval can be established for weighted prevalence rates using the finite sampling formula below (Cochran, 1960) where the summation extends over the different strata. V(p.) N2 ENh (Nh -nhQ III. Survey Findings Using the total reconstructed sample of 5928 patients, HIV prevalence estimates for Lesotho can be derived as 26.48%. This figure must be interpreted with caution as sample sizes in the "young" and "elderly" are small. The 95% Confidence Interval for this estimate is (26.42% ; 26.54%). The narrow confidence band gives validity to the estimate. This is substantially lower than the simple estimate of 34.6% in the absence of data reconstruction. The outcome implies that one in very four Basotho is infected with the HIV virus. The WIV prevalence rates differ by district with Maseru yielding the highest prevalence rate of 39.5%. Being the most populous and urbanised district, the result echoes the graveness of the situation. Qacha's Nek follows with a prevalence rate of 37.2%. This estimate must be interpreted with caution because of the small sample sizes in this district. -HV prevalence rates in other districts are generally in mid to late 20's. Only two districts record HIV prevalence rates of less than 20%. Table 5: Estimated HIV Prevalence Rates for Lesotho by District District Female Male Overall HIV Adult HIV prevalence rates prevalence rates Berea 34.7 42.8 27.1 38.6 Butha-Buthe 31.8 29.9 24.4 30.9 Leribe 25.2 36.4 18.4 30.7 Mafeteng 28.1 26.2 15.4 27.6 Maseru 34.6 48.5 39.5 41.2 Mohale's Hoek 28.4 41.5 22.3 34.8 Qacha's Nek 26.3 32.0 37.2 57.7 Quthing -- -- 24.9 29.4 Thaba-Tseka 19.5 46.1 24.5 32.5 Total 29.7 39.4 26.5 35.3 HIV prevalence rates are much higher in the adult population. One in every 3 of the adult population of Lesotho are infected with the AIDS virus. These estimates can be regarded as more reliable as sample sizes within these age categories are large. Almost all the adult prevalence rates are higher than the 30% mark. HIV prevalence rates in Maseru and Berea are in the 40% region. Qacha's Nek should be viewed with caution once again due to the small sample size. Disaggregation by gender tells a more informative story. The prevalence rates among adult women is approximately 30% whereas the prevalence rates in the male population is almost 40%. (Table 5). Apart from in Butha-Buthe and Mafeteng, the male HIV prevalence rates is higher than its female counterpart in all districts. It appears that every one in two adult males in the Maseru district is infected. Other districts follow closely. There could be several factors which could cause the 44 gender disparities. These could include the "migration effect", "the prostitution effect" and higher levels of promiscuity among men. WHV prevalence rates by age also paints an infornative picture (Table 6). The age category 25-29 has the highest prevalence rates. Sample sizes in the 0-14 category are too small to make a conclusive statement. Table 6: HIV Prevalence Rates by Age Group3 AGE Female Male 0-14 20 11 15-19 24 39 20-24 32 35 25-29 38 54 30-34 36 48 35-39 32 36 40-4 30- 5054 18 - 17 55-59 24 22 60--69 14--= 12- 70 and over 23 14 Statistical breakdown by occupation is presented in Table 7. The highest prevalence rates are found among "house maids", "miners" and " farmers". Teachers and students have relatively lower HIV prevalence rates. Table 7: HIV Prevalence by Occupation Occupation HIV prevalence rate Ex-miner 29 Farmer 44 House maid 50 Housewife 28 Miner 47 Other 41 Student 17 Teachers 25 Unemployed 22 Unspecified 25 Total 26 HIV prevalence rates appear to be uniform among the different types of health facility (Table 8). 3Qacha's Nek has been excluded from this table due to the small sample size 45 Table 8: HIV Prevalence by Type of Health Facility SITE HIV prevalence rates Antenatal Clinic 26 Family Planning Clinic 27 In-patients 26 Out-patients 27 Unspecified site 8 IV. Conclusion and Recommendations The overall HIV prevalence rate in Lesotho is approximately 26.5% . The rate among adults is 35.3%. Although the estimated HIV prevalence rate of 26.5% is lower than that obtained without refining the sample, it still shows that the epidemic has indeed spread to almost all corners of Basotho society. The prevalence rates among adult males is almost 40% and the adult prevalence rates in Maseru and Qacha's Nek are in the 50% region. These results are indeed reason for alarm. In terms of further research: * Future surveys should take sample design into account so that sample sizes within vital strata are not too small. This will ensure that more representative and reliable HIV prevalence rates can be derived. * Coverage should be more extensive to ensure it represents the target groups * Other demographic variables such as education level, use of contraceptives, sexual activity should also be gathered. These will help to better understand the nature and spread of the epidemic in Lesotho. Additionally, this information can be used to model and project future prevalence and incidence rates and the associated demographic impact. 46 .APPENDIX to annex I DIAGNOSES ENCOUNTERED IN THE LESOTHO HOSPITAL-BASED HIV SEROPREVALENCE SURVEY Abbreviated Diagnosis Full Diagnosis Categorisation ABD/PAIN and ABDPAIN Abdominal pain Not opportunistic ABORTION Abortion Not opportunistic ABSCESS Abscess Not opportunistic ACNE Acne Not opportunistic ADENITIS Adenitis Not opportunistic AESTHENI Asthenia May be opportunistic ALLERGY Allergy Not opportunistic AMENNORR, AMENORRH and AMMENORR Amenorrhoea Not opportunistic ANAEMIA Anaemia Not opportunistic ANC Antenatal care attendee Not opportunistic ANOREXIA Anorexia Not opportunistic ANTHRAX Anthrax Not opportunistic ANXIETY Anxiety Not opportunistic APH Antenatal haemorrhage Not opportunistic APPENDIC Appendicitis Not opportunistic ARTHRITI Arthritis Not opportunistic ASCITIS Ascitis Not opportunistic ASSAULT Assault Not opportunistic ASTHMA Asthma Not opportunistic BACKACHE and BACKPAIN Lower back pain Not opportunistic BODYPAIN B Generalised body pain Not opportunistic BARTHOLI Bartholinitis Not opportunistic BLEEDING Bleeding from unspecified site Not opportunistic BOH Bad obstetric history Not opportunistic BOIL and BOILS Boil (Surface abscess) Not opportunistic BREASTCA and CABREAST Breast cancer Not opportunistic BRONCHIT Bronchitis Not opportunistic BTL Bilateral tubal ligation Not opportunistic BURNS Burns Not opportunistic C/S Caesarean section Not opportunistic CACERVIX and CERVIXCA Cancer of the Cervix Not opportunistic CACHEXIA Cachexia May be opportunistic CARBUNCL Carbuncles Not opportunistic CARDIAC, CARDICD and CARDITIS Cardiac disease Not opportunistic CARIES Dental caries Not opportunistic CATARACT Cataract Not opportunistic CCF Congestive cardiac failure Not opportunistic CELLULIT Cellulitis Not opportunistic CERVICIT Cervicitis Not opportunistic CHECKUP Medical check up Not opportunistic CHESTPAI Chest pain Not opportunistic CHICKENP Chickenpox Not opportunistic CHRONIC Non specific chronic ill health May be opportunistic CIRCUMCI Circumcision Not opportunistic CIRRHOSI Liver cirrhosis Not opportunistic CO/ABORT Complete abortion Not opportunistic COLIC Colicky abdominal pain Not opportunistic COMA Unspecified Coma Not opportunistic CONFUSIO Confusion Not opportunistic CONJUCTI Conjunctivitis Not opportunistic CONTACT Contact dermatitis - Not opportunistic CONVULSI and FITS Convulsions Not opportunistic COUGH Cough May be opportunistic CRAMPS Cramps Not opportunistic CREPS Crepitations Not opportunistic CVA and STROKE Cerebrovascular accident Not opportunistic CYST and CYSTITIS Cystitis Not opportunistic D+C Dilatation and Curettage Not opportunistic DEHYDRAT Dehydration Not opportunistic 4 The information in this table was provided by Dr. Givans K. Ateka (WHO, Lesotho) 47 DELIVERY, NUD and NSD Normal vaginal delivery Not opportunistic DEPRESSI Depression Not opportunistic DERMATIT Dermatitis Not opportunistic DIABETES and DIAMETES Diabetes mellitus Not opportunistic DIARRHOE Diarrhoea May be opportunistic DISCHARG Unspecified discharge Not opportunistic DIZZINES and DIZZY Unexplained dizziness Not opportunistic DVT Deep venous thrombosis Not opportunistic DYSATHRI Dysathria Not opportunistic DYSENTRY Dysentery Not opportunistic DYSMENOR Dysmenorrhoea Not opportunistic DYSPEPSI Dyspepsia Not opportunistic DYSURIA Dysuria Not opportunistic ECLAMPSI Eclampsia Not opportunistic ECTOPIC Ectopic pregnancy Not opportunistic EFFUSION Unspecified effusion May be opportunistic EPILEPSY and EPILESPY Epilepsy Not opportunistic EPISTAXI Epistaxis Not opportunistic EYESIGHT Visual impairment Not opportunistic EYETRAUM Trauma to the eye Not opportunistic EYETUMOR Tumour of the eye Not opportunistic F/PALSY Facial nerve palsy May be opportunistic FACERASH Facial rash Not opportunistic FATIGUE and FATIQUE Unexplained fatigue Not opportunistic FATNECRO Fat necrosis Not opportunistic FEVER Unexplained fever May be opportunistic FIBRIODS, FIBROID and FIBROIDS Fibroids Not opportunistic FLU Influenza viral infection Not opportunistic FPLANING and FPLANNIN Family planning Not opportunistic FRACTURE Fracture Not opportunistic FUNGAL Unspecified fungal infection May be opportunistic G/E Gastro-enteritis Not opportunistic G/RASH Genital rash Not opportunistic G/WARTS Genital warts May be opportunistic GALACTOR Galactorrhoca Not opportunistic GALLSTON Gall stones Not opportunistic GANGLION Ganglion Not opportunistic GANGRENE Gangrene Not opportunistic GASTRITI Gastritis Not opportunistic GBP Could not figure out what this stands for GOITRE Goitre Not opportunistic GOUT Gout Not opportunistic GROUPING Croup Not opportunistic H/HEARIN and H/INJURY Head injury Not opportunistic HAEMATURI and HAMATURI Haematuria Not opportunistic HAEMORRH and HEMORROI Haemorrhoids Not opportunistic HAEMOTHO Haemothorax Not opportunistic HEADACHE Headache Not opportunistic HEPATITI Hepatitis Not opportunistic HERNIA Hemia Not opportunistic HERPES Herpes May be opportunistic HERPESZO Herpes zoster Opportunistic HTN and HYPERTEN Hypertension Not opportunistic HYDROCOE Hydrocoel Not opportunistic HYPOGLYC Hypoglycaemia Not opportunistic HYSTEREC Hysterectomy Not opportunistic HYSTERIA Hysteria Not opportunistic I/SUPPRE and NS Suspected immunosuppression Opportunistic ICD Intercostal drainage tube Not opportunistic ILLDEFIN Ill-defined illness May be opportunistic IMPOTENC Impotence Not opportunistic IMPETIGO Impetigo Not opportunistic IN/ABORT Incomplete abortion Not opportunistic INFERTIL Infertility Not opportunistic INSOMNIA Insomnia Not opportunistic ITCHINES Itchiness Not opportunistic IUD and IUFD Intrauterine foetal death Not opportunistic JAUNDICE Jaundice Not opportunistic KAPOSIS Kaposis sarcoma Opportunistic 48 KERATITI Keratitis Not opportunistic KETOACID Diabetic ketoacidosis Not opportunistic L/ADENIT and LMPHADEN Lymphadenopathy May be opportunistic L/OEDEMA Lymphoedema Not opportunistic LABOUR and LABOURER Matemity admission Not opportunistic LACTATIN Breastfeeding clinic attendee Not opportunistic LAP Lower abdominal pain Not opportunistic LIBIDO Reduced libido Not opportunistic LIPOMA Lipoma Not opportunistic LRTI Lower respiratory tract infection Not opportunistic M/SPASM and M/STENOS Mitral stenosis Not opportunistic MALAISE Malaise May be opportunistic MALNUTRI Malnutrition Not opportunistic MARASMUS Marasmus Not opportunistic MEDEXAM Medical examination Not opportunistic MENINGIT Meningitis Not opportunistic MENORRHA Menorrhagia Not opportunistic MYALGIA Myalgia Not opportunistic MYOSITIS Myositis Not opportunistic NAUSEA Nausea Not opportunistic NECKPAIN Neck pain Not opportunistic NEPHRITI Nephritis Not opportunistic NSD and NUD Nommal vaginal delivery Not opportunistic O/SORES Oral sores May be opportunistic OITHRUSH Oral thrush Opportunistic OB Obstetric complaints Not opportunistic OEDEMA Oedema Not opportunistic ORCHITIS Orchitis Not opportunistic OSTEOMYE and OSTEOMYL Osteomyelitis Not opportunistic OSTEOPOR Osteoporosis Not opportunistic OTITISIM Otitis media Not opportunistic P.N.CARE and POSTNATA Postnatal care Not opportunistic P/RASH Penile rash Not opportunistic P/SEPSIS Puerperal sepsis Not opportunistic P/ULCER Penile ulcer Not opportunistic P/WARTS Penile warts May be opportunistic PAIN Non specific body pain Not opportunistic PALPITAT Palpitation Not opportunistic PELLAGRA Pellagra Not opportunistic PERICARD Pericarditis Not opportunistic PERITONI Peritonitis Not opportunistic PHARYNGI Pharyngitis Not opportunistic PHYMOSIS Phymosis Not opportunistic PID Pelvic inflammatory disease Not opportunistic PIH Pregnancy induced hypertension Not opportunistic PLEURISY Pleurisy Not opportunistic PLEURITI and PRURITIS Pruritis Not opportunistic PNEUMONI Pneumonitis Not opportunistic PNEUMOTH Pneumothorax Not opportunistic POISONIN Poisoning Not opportunistic POLYDIPS Polydipsia Not opportunistic POLYURIA Polyuria Not opportunistic PPH Postpartum haemorrhage Not opportunistic PREGNANC Pregnancy Not opportunistic PRELABOR and PROM Pre-labour rupture of membranes Not opportunistic PROCTOTI Proctotitis Not opportunistic PROST/CA Prostate cancer Not opportunistic PSYCHOSI Psychosis Not opportunistic PTB Pulmonary tuberculosis - Opportunistic PTBRELAP Relapsed PTB Opportunistic PUD and PUN Peptic ulcer disease Not opportunistic PUO Pyrexia of unknown origin May be opportunistic PURPURA Purpura Not opportunistic PVBLEED Per vaginal bleeding Not opportunistic PVD Per vaginal discharge Not opportunistic R/PLACEN Retained placenta Not opportunistic RAPE Rape Not opportunistic RASH Non specific rash Not opportunistic REC/MASS Rectal mass Not opportunistic 49 REC/STDS Rectal sexually transmitted disease Not opportunistic RENAL/F Renal failure Not opportunistic RETENTIO and U/RETENT Urinary retention Not opportunistic RETINITI Retinitis Not opportunistic REUMATIS Rheumatism Not opportunistic RIGOURS Rigours Not opportunistic RTA Road traffic accident Not opportunistic RTI Respiratory tract infection Not opportunistic S/ABORT Septic abortion Not opportunistic SALPINGI Salpingitis Not opportunistic SEPSIS Sepsis Not opportunistic SEPTICAE Septicaemia Not opportunistic SKINRASH Non specific skin rash Not opportunistic SOL Space occupying lesion Not opportunistic SORE and SORES Sore(s) Not opportunistic SORETHRO Sore throat Not opportunistit STAB Stab wound Not opportunistic STD Sexually transmitted disease Not opportunistic STRICTUR Stricture Not opportunistic SURGERY Surgery Not opportunistic SWEATING Excessive sweating Not opportunistic SWELLING Swelling Not opportunistic SYNCOPE Syncope Not opportunistic SYPHILIS Syphilis Not opportunistic TACHCARD Tachycardia Not opportunistic TH/ABORT Threatened abortion Not opportunistic THRUSH Thrush May be opportunistic THYROTOX Thyrotoxicosis Not opportunistic TIREDNES Unexplained tiredness May be opportunistic TONSILLI Tonsillitis Not opportunistic TOOTHACH Toothache Not opportunistic TRAUMA Trauma Not opportunistic TYPHIOD and TYPHOID Typhoid Not opportunistic ULCER Ulcer Not opportunistic UNSPECIF Unspecific complaints May be opportunistic URETHRIT Urethritis Not opportunistic URTI Upper respiratory tract infection Not opportunistic UTI Urinary tract infection Not opportunistic V/ABSCES Vulval abscess Not opportunistic V/ITCH and V/PRURIT Vulval itchiness Not opportunistic V/RASH Vulval rash Not opportunistic V/SORES and V/ULCER Vulval sores/ulcers Not opportunistic V/THRUSH Vaginal thrush May be opportunistic V/WARTS Vaginal warts May be opportunistic VAGINITI Vaginitis Not opportunistic VOMITING Vomiting Not opportunistic WAISTPAI and WAITRESS Waist pain Not opportunistic WARTS Warts May be opportunistic WASTING Wasting Opportunistic NOTES * The term opportunistic is normally used forinfections that would lead to a suspicion of compromised immunity but in this case, it refers to all conditions that may arouse such suspicion; * Conditions listed as "May be opportunistic" are some of those which constitute the minor criteria for a diagnosis of immunosuppression; * Conditions categorised as "Opportunistic" are some of those which constitute the major criteria for a diagnosis of immunosuppression; and * Teasing out these two categories (highlighted in the tables) from the range of other diagnoses would leave us with patients who although seen in hospitals had no signs that would make anybody suspect the possibility of immunosuppression. 50 Annex II Modeling the Impact of HIV/AIDS in Lesotho 1. The purpose of this Annex is to describe, in detail, the models used in the report to analyze the impact of HIV/AIDS on Lesotho's economy. It also outlines the assumptions and the sensitivity of the results. 2. The main model is Spectrum, which is a windows-based program, developed by The Futures Group International with funding from the USAID. This model analyzes existing information to determnine the future consequences of current population programs and policies. It has several modules of which two are relevant for our purpose here: DemProj (Demographic Projections) used for the demographic projections on the basis of current population, fertility, mortality, and migration; and AIM (AIDS Impact Model) used for projecting the consequences of the AIDS epidemic. 3. DemProj: The following information is required by the DemProj module. * Base year population by age and sex. * Total fertility rate. * The age distribution of fertility. * Life expectancy at birth. * Life table. - International migration by sex. All the above variables require future assumptions relating to expected future trends except the population estimates which are derived as the basis of the estimates generated for these parameters. The following information is used in the demographic projections module for Lesotho. * Base year population by age and sex for 1986 (actual): Age group Male Female (in years) 0 - 4 124,890 122,386 5 - 9 107,068 105,770 10- 14 99,702 100,256 15- 19 82,541 87,139 20 - 24 67,168 74,628 25 - 29 55,844 61,714 30 - 34 46,968 49,213 35 - 39 39,568 39,440 40 - 44 33,604 32,739 45 - 49 30,288 29,783 50 - 54 26,750 27,326 55 - 59 20,670 21,892 60 - 64 16,114 17,950 65 - 69 13,116 15,958 70 - 74 8,903 12,101 75-79 11,480 22,152 80+ 0 0 Total 784,724 820,447 (=1,605,171) (Source: 1986 Population Census Analysis Report Vol. IV pp. 5.3. Note that the latest population census was conducted in 1996 but the model uses 1986 as the base year since the first HIV/AIDS case was detected in 1985). 51 * Total Fertility Rate (TFR): 5.6 for 1997 and projected to decline to 4.0 by 2015. (Source: 1986 Population Census Analysis Report Vol. IV pp. 2.7. TFR was estimated to be between 4.9 and 5.6. This was in line with 1976 census estimate of 5.4). * Age Specific Fertility Rates (ASFR): These are defined as the number of live births per 1,000 women in the age groups. Age group % distribution % distribution (in years) in 1986 in 2015 15- 19 7.10 6.0 20-24 23.10 29.0 25-29 23.10 25.0 30-34 19.30 18.0 35-39 15.70 14.0 40 -44 8.60 6.0 45-49 3.10 2.0 100.00 100.0 (Source: 1986 Population Census Analysis Report Vol. IV pp. 2.9. Relative percentages were calculated by the CSO using the Brass method). * Sex Ratio at Birth: 105 male births per every 100 female births. (Source: African average based on UNAIDS data). * Life Expectancy: (without AIDS) 1986 2015 Male: 56.0 65 Female: 58.6 67 (Source: 1986 Population Census Analysis Report Vol. IV pp. 5.2. The average for males during 1987- 91 was estimated at 58.5 and for females 62.2). • Infant Mortality Rate (IMR) and Crude Death Rate (CDR): IMR: 87.5; CDR: 10.4 (Source: 1986 Population Census Analysis Report Vol. IV pp. 3.15. IMR was around 87.5 and CDR was 11.7. The model uses the UN assumptions of IMR 90 and CDR 11.7 as an average). i International Migration (net): negative number indicates more Basotho's went out than entering the country. 1986 2015 Male: -141,868 -200,000 Female: 0 0 (Source: 1986 Population Census Analysis Report Vol. IV pp. 4.15). Note: Lesotho is highly mountainous and the arable land is very limited. The demand for Basotho men to work in the newly discovered South African diamond mines went up at the beginning of the century. On average 40 percent of males in their working age were at any time migrant laborers. Thus out of 354,671 economically active population in Lesotho in 1986 an estimated 141,868 worked in South Africa. This estimate is in line with the employment of Basotho miners in 1985 at 116,513. 4. AIM: The following assumptions are used in the AIDS impact module for Swaziland. Epidemiology: 1986 2015 Adult HIV Prevalence: 0.03 32.0 HIV/AIDS parameters * Start year of AIDS epidemic 1985 * Percent infants with AIDS dying in the first year 67.0 * Life expectancy after AIDS onset (years) 1.0 * Reduction in fertility among HIV+ (%women) 30.0 * Prenatal transmission rate (%) 30.0 30.0 52 HIV Incubation period Adults Children Cumulative percent developing AIDS by number of years since infection Years 1 0.0 29.0 2 6.0 62.0 3 20.0 75.0 4 30.0 85.0 5 40.0 90.0 6 50.0 95.0 7 59.0 95.0 8 68.0 95.0 9 77.0 95.0 10 86.0 95.0 11 90.0 95.0 12 90.0 95.0 13 90.0 95.0 14 90.0 95.0 15 90.0 95.0 16 90.0 95.0 17 90.0 95.0 1 8 90.0 95.0 19 90.0 95.0 20 90.0 95.0 (Source: Faster pattem of cumulative percent developing AIDS by the number of years since infection for both adults and children based on UNAIDS estimates). Age Distribution of New HIV Male Female (Ratio of HIV prevalence at 25-29) Age group 0- 4 0.0 0.0 5 -9 0.0 0.0 10- 14 0.0 0.0 15- 19 0.4 0.9 20 -24 1.2 1.8 25 -29 1.0 1.0 30 - 34 0.3 0.5 35 - 39 0.2 0.2 40-44 0.1 0.1 45 -49 0.3 0.0 50 - 54 0.0 0.0 55 - 59 0.0 0.0 60 - 64 0.0 0.0 65 -69 0.0 0.0 70 - 74 0.0 0.0 75 - 79 0.0 0.0 80+ 0.0 0.0 53 * Impacts: 1986 2015 * Expenditure per AIDS patient 2,800 24,344 * Percent AIDS hospitalized 80 80 * Ministry of Health budget (Million Maloti) 50 1,031 * Hospital beds 8,000 10,000 * Bed capacity factor (1=100% beds used) 1.0 1.0 * Bed days/AIDS patient (days) 70 70 * Prop of 0-5 vaccination for measles (%) 40 40 * Measles vaccine efficacy (%) 80 80 * Measles case fatality rate (%) 2.4 2.4 * Malaria episodes/person/year 3 3 * Malaria case fatality rate 3.15 3.15 * TB incidence without HIV (%) 2.4 2.4 Percent population with latent TB 50 50 * TB incidence with HIV (%) 90 90 (Source: Informal discussions with the Government and NGOs). 5. Analysis of the Results and Conclusions: * Number of HIV patients will increase from 115,832 in 2000 to 476,111 in 2015 an annual increase of 9 percent. * Cumulative AIDS cases will increase from 40,211 in 2000 to 456,286 in 2015 an annual increase of 16 percent. - Annual AIDS deaths for the next 15 years will be around 44,000 (cumulative) or 11 percent increase per annum. - Life expectancy will go down by 31 years during the next fifteen years due to HIV/AIDS thus reducing the average life of Basotho by 2 years per annum. 4 On average 14,000 orphans will be added to the cost of govemment budget to provide food, education and employment. By 2015 a total of 152,000 orphans will be waiting to be taken care of by somebody. The following tables and diagrams provide the complete outputs for the modeling process. The analysis and qualifications of the projections are undertaken in the main body of the report. 54 HIV-AIDS HIVIAIDS ProJectos__ _ Indicator 1999 2000 2001 _ 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 _ 2012 2013 2014 2015 Adults 1.309,329 1,338,405 1,366,653 1,400,873 1,433,686 1,467,276 1,500 ,802 1 ,533.540 15 1,595.635 16,602 1,651.769 1,676,944 1,699,677 1,719,891 1,737 1,5,1 HIV+ adults 97,067 110,132 124,414 140,090 159295 181039 203,960 227,809 252,370 277,510 303,211 329,450 355,979 382,437 4043727 4, 460,294 Adult HIV prevalence % 7.41349 8.23 9.10 10.01 11.11 126.4 13.59 _14.8 1.12 17.39 18.66 _1995 21.23 22.50 23.76 25.02 26.27 HlV+ population 101,959 115,832 130,865 147,238 167,129 189,563 213,178 237,701 262,911 288,655 314.905 341,627 368,738 395,871 422,925 449,643 476,111 AIDS cases 8.347 10,148 11,932 13.574 15,283 17.117 19,178 _21,592 24,139 26,722 29,352 32,106 35,015 38,034 41,103 44 ,062 46.866 Cumulative AIDS cases 30,063 40,211 52,143 65,717 81,000 98,117 117,295 138,887 163,026 189,748 219,100 251,206 286,221 324,255 365,358 409,420 456,286 tin AdutAIDS cases 7,334 8,946 10,550 2024 13586 15276 17,188 19,451 21,861 24.312 26,820 29,466 32,24 35,181 38,090 40,878 43,503 Adu_ _____ 2_ ___13__586_ AduKt HIV incidence 18,865 20.399 23,228 26,226 31,229 35,330 38,197 41,037 44,012 47,001 50,013 53.059 55,995 58,742- 61,471 64,008 66.527 Adut HIV incdence 1.44% 1.52% 1.70% 1.87% 2.18% 2.41% 2.55% 2.68% 2.81% 2.95% 3.08% 3.21% 3.34% 3.46% 3.57%_ 3.68% 3.80% (Percent)____ Chart data =_ _ _ HIV+ adult i_______ AIDS cases ___ 19997 2000 2001 2002 2003 2004 2005- 2006 2007-2008 2009 -2010 2011 2012 2013 2014 2015 HIV incidence 1.4%1 1.5% 1.7%i 1.9% 2.2% 2.4% 2.5% 2.7% 2.8% 2.9% 3.1% 3.2%i 3.3% 3.5%1 3.65og 3.?%i 3.8%1 Mortality Mortality Impacts of AIDS indicator _ _ Projection 1999 i2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Young aduildeaths With AIDS _ _ 9147 10541 '12,008. 13,546 15,070 16,691 I 18,470' 20,509 22,775 25,130 27,532 30,024 32,659 35,408 38.203 40,949 43,589 (Annual deaths to No AIDS 3,083 . 3,056 3,024 3,125 3,231 3,340 3,451 3,565 3,681 3802 3924 4,048 4175 4,303 i4434 7 4,586 45699 adults 15-49) Young adult Infantmortalilyrate WithAIDS_ 58.9 576 562 56.5 56.9 57.3 57.7 58.0 58.4 58.6 58.8 59.0 596 60.1 60.7 61.2 61.7 (Infant deathsper NogAIDS 58.7 57.4 55.9 56.1 56.4 56.7 57.0. 57.2 57.4 57.5 57.6 _ 57.6 58.0 58.3 58.6 58.8 591 1000live brths) Intant_mortati - inder5mortalityrate WithAIDS - 84.8 84.0 83.1 84.6 86.0 87.4 88i.9 90.4 91.8 93.0 94.2 _ 95.1 _ 96.0 97.2 99.0 100.9 103.1 (Deaths to 0-4 per No AIDS 73.9 71.2 68. 88.4 68. 688 68.4 88.4 68.4 88.4 68.4 68.4 68.4 68.4 68.4 68.4 68.4 t100 live births) Under_5_mO_ Llte expectancy - With AIDS 54.8_ 53.5 52.4i 51.1 49.9 48.7 47.3i 45,8 44.3i 43.0 41.7 40.4 39.1 37.9 36.7 35.6 34.6 at birth No AIDS 65.0 65.5 66.0 66.0 66.0 6660 680 88.0 66.0 6 68.0 6 86.0 66 88.0 .0 66.0 0 66.0 860 66.0 _Lieexpectar . . AnnualAIDS daths WithAIDS 6,716 8,347 101,48 11,932 13,574 15,283 17,117 19,178 21,592 24,139 26,722 - 29,352 32,106 35,015 38.034 ,41103_ 44.062 AIDS_deathsl j _ - O Cumulative AIDS ;With AIDS _21,717 30,064 40,212 52,144 65,718 81,001 _98.118 117,296 138,888 163,027 189,749 219,101 251,207 286,222 324,256 365,359 409,421 deaths Cum_AIDS_d CrudeAIDSdeathrate WithAIDS 2.9 3.6 4.3 4.9 5.5 _ 6.1 6.7 7.4 86.2 9.0 9.8 _ 10.7 11.6 12.5 13.5 14.5 15.5 - _ Crude AIDS Chadtdata --- 1999 200 2001 2002 - 2,003 2004 -- 2005' 2006.2007_ 2008- 2009 2010_ 2011 2012 2013 2014 2015 Young adult deaths With AIDS . 9.147 10.541 1 12.008 5 6.691 18.47 20.509 22.775 25.13 27.532 30.024 32.659 35.408 38.203 40.949 43.569 (Annual deathsto _No AiDS 3.083 3.056 3.024 3.125 3.231 3.34 3.451 3.565 3.681 3.802 3.924 4.048 4.175 4.303 4.434 4.566 4.69 adults 1549) . Demography Demographic impacts of AIDS Indicator __Projection 1999 2000 _ 2001 _2002' -2003 i 2004 2005, 2006 2007 2008_ 2009 2010 2011_ _22012 _2013 2014 - 2015 Population size With AIDS 2.279,870 2,332,10 2,382,893 2,432,031 2,479,342__2524,796 2.567,970 2,608,629 2,646,691 2,682,221. 2,714,959 2,744,959 2,771,835 2,795,503 2,815,603_2,832,270 2,845,362 No AIDS 2,318.167 2,383,768 2,450,509 2,518,164_2,586,554 2,655,865' 2.725,908 2 796,817 2,868,829 2,942,173 3,016,655 3,092,511 3.169,522 3,247,830 3,327,1154 _3,407.706 3,489,18 Pop.see-f _ __ _ - _ - _ _, __ Annualpo ulation WithAIDS 24%A 2.34 2.2%° 2.1% 1.9%5 1i8% 1.7% 1.6' 1.5% 1.3% 1.2% 1.1% 1.09 0.9% 0.7% 0.6% 0.5% growth rate _ No AIDS 2.9% 2.8% 2.8% 2.8% 2.7% 2.7bA 2.6% 2.6% 2.6% 2.6% 2.5% 2.5%, 25% 2.4% 2.4% 2.4% (Percentlyear)- Annual_pg_. _ . _- - - - Adultubton With AIDS 1,309,329 1,338,405 .366,653 1,400073 1,433.686 1,467,276 1,500802i 1533,540 1,565;26i 1,595,635' 1.624.602 1,651,i68 1,676.94i 1.699677_1.719,891 1,737.360_1.752,31 NoAIDS 1,331,628 1,368,706 1,406,510 1,450,966 1,497.070_1,544,714 1,594,071 1,644,742 1,696.820 1,750,147 1.804,805 1,860.575 1,917,495 1,975,305 2.034,039 2,093,463 2,153,672 Adult_pop =_ __ -- Crude birth rate With AIDS 35 34.3' 336 33.1 32.5 _ 32 31.4 30.9 30.5 30.2 29.8 29.5 29.2 28.9 28.6 __28.37 28.0 (Birthsper NogAIDS __ 36 35.5 349 34.5 34 33.6 33.2 32.8 32.5 32.4 32.1 31.9 31.7 31.5 31.2 _ 31 30.8 1Opeople_Crude birth_ Crude death rate WitiAIDS _ 11.6 11.9 12.3 12.9' 13.4 13.9 14.6_ 15.3=__ 16.1 16.9 1 7.7-_ 18.6 195 20.5 21.5 l22.5 23. (Deaths per No AIDS 8.3 __ 8 7.7 76 7.6 7. 7.5 7.5 7.4 _ 7.4 _7.4 7.4 7.4 7.4_ 7.4 7.4 7.4 tA 1000 people) Crude deat& _ _ De_Dpendency railoWihAIDS 0.87 _0.87X 0.87 0.87 _ 0.88 0.85 0.83 0.82 0.81 0 079 0.78 0.77 0.76 _ 0.75 0.74 0.74 _Dependents per NoAiDS 0.87 0.87 0.87 0.86 0.85 0.84 0.83 0.82 0.81 0.79 0.78 0.77 0.76 0.75 0.74 0.73 _ 0.72 adult 15-64) Dependency Heelth car I.Pate Of AIDS ladlicato projectio o1"8 2000 _ 2001 2002 2003 2004 2005 2008 2007 2000 2000 260i _ 201 _ 2012 2013 2014 7I.2015 D.redcteddw -WihAIDS 200Q258910 40,242,057, 521451 0,9,0 110§018,2.5 2.8.6I 132987 188,749.453 230,124.2 50 278.383.282 3,36.271,072 .402.50282,00 -8.157 7701 _75.7482.02 71002 forAIDS cMr No AIDS 8 8 8 8 0 8 0. 0 8 0 8 8, 0 0 0- 0 0 Expnditre ~ -- Percent of19 WIOh AIDS 155 10.7 21.8 24.0 27.5 30.06- 34t.0 30.0 --42.2 48.3 50 -54 069.3 03.8 68A 72.7 _ 74' exptxtilxAlDs i oAIDs __ .0 0.0 0.0 0.0 __ 0.0 0.0' - .0 0. 0. 0. 0.0 0.0 ~ 0.0. 0.0 0.0 0.9.O. 0.0 _ 00 -PercenI Dl - I4xxp.taIbed.dxyx AIcOAIDS 3048003 _448,579 __ 536.940 _ 3 236 700,287- 806553 817.3Cr)_ 1,0.48,42 1108q570 1,330334 1.488,386 1052817 -1.828,5011 2,014,618 2,208.053 2480302258.675 n-eded forAlDS fla AIDS 0 0 0 0 07 0a- 8, 0 0 0 0 0- 0 0 0 00 Poecetolfbeds __WithAIDS 12 18 ¶ 21 24 ~ 20i 31 36 ~ 41. 46 ~ 51 57 _ 63 oo. 786 82 - 89 neadedtsr~AIIOS No AIDS 0 0 .0 . . 0 0 00 0 0 0 8 0 0 0 0 _ _ 0 Percesl0x Chldcxxesal - - WithAIDS 41,107 -41,207 41.3290 41,334 41,287 41.1688 41.000 40810q A*5s3 40,388 40.192 40.018 . 30,842 30.650 39.390 _39.092- 20.70 measles t4xAIDS _ 42,082 43.130 ~~~~~~~~~43,637 4.1 4,57 480- 434 4086 48,239 48,744 47.274 _ 47,878 48,507 -.49,100 49.780 50.400 8000 Chiddcla#.hcle _W,ithAIDS_ __ 82 85 827 8 27 _ 820 a 23_ 820 816 - 12 _ 088 804 SO0 797 -793 788 . 782 774 txeMeaSlex M NAIDS -852- M6 873 _ 882 _ 881 9008 90 18 025- 935 . 40 057 . 70 883 8988 1,808 -_1,020 Measlesk_dex - Ut. Cdhidcaxws of tWithAIDS 3633517 366.705 369,01O 7,2 ~ 31,9 7,0 .372324 373283 .373101 373,130 3738070 373384- 373,522 37,5 . -373016 - 372.1071 370,304 00 saliae N.82 AD 378808 383.330 388.616 305,7886_ 401.563 407,431 __ 413.086 418,9052 434,001 431.749 4382000 448,583 454748 463.186 471,397 679,777 4779 Massearea .. - Clid dect xhdue WithAIDSi 1.818 1,824 1,845 1,854, 1,860 1885 I,8 ,6 1.866- 1,86 I.os 1,867 1.8688 1,868 .65 1.860 _ 1,852 lo .WWx No AIDS 1,883 19`17 _ .848_ 1.078 . 2,098 2,637 20805- 28895- 2,125 ~ 2,108 2,3194 __2.23.3 _ 2,274 2,316- 2,357 __ 2.399- 2,3 Child deaxttdxe WithAJDS -- 88 1.137 __ 1.301 _ 1,448e _ 10574 ._ 1,888 1'820~ 1,001 . 2.0 2.208, 2.312 _ 2,405. 242 2,94 276 28N_1 t.xAIDO 'i- NAiDs 0 8 0 0 0 O 0 0 0 _ 0 0 0 0 08 0 __ 0 Ch1d deatiht Thcaeex____ ~~W6hA13S 7-,-472 8'1823 0.954 9,805 . 10,832 _1_7 320 448 5,74, .07 ,10, '19.778 21.153 22,52- 23.876 . 25.27 260519 NoAIDS _ 2,663; 2,737 2,813 -28902 38894 3.0089 3.18 3208 30 35080D 3,610 32721. 3,820 3.951 4.068 4.1187 _4,307 EubaTOcaxes ~~WithAIDS __4800 5.448 6.141 8,903. 7,838 88847 _10811 _ 11,100 12 355 135686 4,0 _ 18.0055 17,318 - k51 1,m, 2,2 dxx to HIV Economny Macro-econornic Impacts of AIDS_ indicator _ Projection IM99 _ 2000.____ 2001 - 2002 __2003 2004 2005 2006G 2007. 2008 2009E 20101 2011 - 2012 2013 2014, 2015 Labor onie size WOfiAIDS 457.36_ 498232 _5269598 5553431 583,361 611.008 638.7551 866.,232: 692,683 7180451 743429 767.3.32 789.981 811.700 832,404 851,92 87,4 _ ~~~~~~~No AIDS 496.094 510,086 542 715 576.491 610,335 64.6 680.128 716,503 753,177 _ 790,640_ _828.877867.7117 907,1127 94.0 69,225 1,031,861: 1.075,568 LF size= Pc AID cae epenitue -WIt AIS _ 40,42.5752.154.521 65,390,091 r81.1307,7710228 12358716 132798 '87866749 453 ~230,124,250 278,363.292_235,271072.402582.892 461,416597527916,7382i1992 _No AIDS 0 - 0 _ 0 _0 0 - 0 0 0 0 0 0: 0 0 0_ 0 - 0 Capital stck (inSllons)_ With AIDS 13,419 13.087- 12,810 12.595. 12,436, 12.323 -. 1-2,249 __ 12,207, _ 12.188 121584-121188 12,192_ 12.187 I12A63 12,11 11 12.022 11,886 NAIDS --13,4611_ 13146 12.918 - 12763 12,67-7 - 12653~~ 12,687- 12.774 ..12.912 13.007 13,32-7 13,598 -31%9Oq _14,258, 14,643 -1506 _15519 -- - ~~~~Capital-Stosi - Idxo anil_prog--ss 1.013 1.014. 1.01-5 1_I.016_ - 1.017 1.018 _ 1.019, __1.020, 1.0211 1.022 1.023. 1.024 1.025____1.026 1.027 1.028_ 1.029 index Iech.J C.s. - ~ ~ ~~ C-,31D4184,2 4 504ons- 506 516501r Grndmsiproduc WihAD 3.945 4,31 4-6 4,308 4,446 4,5851 4.64867 5,4 5,139 5,6' 5,393 508 66 .5,715 581 5,874 (m8ions) CONSTANT -No AIDS 3.945 4,104 4267_ 4,440. 4,616. 4.798 4.990 5,192 5,399 5,615 5,840 6.073 6.314 _6.565. 6,826 - 098 7380 GDP =CD_ 4.102 4,268 4,438, 4,617 4,800 --4,990_ 5190 5,399~ 5.615 5.84 6,074 81316_ 6566 _6827T 7,099_ 7.382 Gr05sdomesitcinve-lme -- -iiAD 1,5 ,7 1,209 -1240 1,269 1,295i_ 1,3-19_ 1.338 1,350~ 137_ 3 1,350. 1,330. 1,3-00 1,250 1.200; _1129 (rnii5ons) - -No AIDS -1.1 83 1,231 1,280 1 332 1,385 11439 __ 1,497 1,557i 1,620 1.665 __ .752 1,822 1,894 1 969 2,046 2,1294 2214 GDI =GDP' 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0% 30.0 30.0% 100%. 30.0% 30.0%: 30.0% 30% 3.% 3.0 GDP growth rate With AIDS -2.8 2.2- 3.4 3.4 3.2 3.1 __ 3.1 3.0 2.8 2.71 2.5 __2A4 2.1 2.0 1.8 1.5 1.3 ~.I (percent) -No AIDS 2. _ 4.01 4.0 4.0' 4.0 4.01 4.0 6 4.0 4.0 4.0 __40' 4.0 4.0 4.06. . . _GDP..srowh GDPpercapIa __Wfth AIDS - 1730 1728._ 1749, IT 1793 ~ 18161640196 14(1 1965 1987- 2009 _ 2030 2048 - 2084 N4o AIDS 1702- 171I 1741 -176 __ 17815 1507:-- 1831- 1856 1862 1909 192613 1964 1992 2021 2052 208 2115 __ ~~~~GDP_peLc - - -_--- _ GDPpercap4lgrore0lreleWIIhlAIDS 0.4, -0.1, 12 1.3 _ 1.2 1.3 1.3 14 1.3 1.3. 1.3 1.2 1.2 1.1 1.O 0 0.9 0.8 (percent) - 4 oAD 01- 1.2 1.2- 1.2 1.2 1.27 1.3, 1.4 1.4A IA- . IA 1.4 A1. .515 . GDP cc Orphans Number of AIDS 0rhar __. __ __ ___ ____ ___ _. 1 _ _ Indicator l 1999 2000 2001 2002 __ 2003 2004 2005 _ 2006 2007 2005 2009 2010 2011 2012 2013 2014 2015 AIDS deathsto 3676 4484 5281 6016 6789 7626 8567 9684 10860 12052 _ 13268 14545 15906 -17299 18691 20020 21257 adul females Total fertilirte _ 49 4.8 4.8 4.7 _ 4.7 .6 4.6 4.5 4.4 _ 4.4 4.3 4.3 4.2 _ 4.2 4.1 4.1 4 Nw orphans /death 1.3 1.3 1 1.3 1.3 1.3 1.3 1 1. 3 3 1 1 .3 1.3 1.3 1.3 1.3 1.3 aeo3 .3.8 3.8 3.8 3. 8 3.8 3.8 _ 33.8 3. 3.8 3.8 3.8 3.8 3.8 3.8 3.8 3.8 Average survival to age 5 0.92 0.92 0.92 0.92 0.91 0.91 0.91 0.91 0.91 091 0.91 9.90 0.-l90 0.90 0 0.90 0.90 [New orp ns - 4,495 5,487 6,469 7,357 8,290 9,298 10,428 11,768 13,177 14,604 16,056 17,584 19,210 20,865 22,499 24,048T25,471 Total orphans 1 1 19,07 23,841 34,777 40,978 47757 55,273 ,5 7 82,078 92,353 103,340 115,003 127,262 * 0 LESOTHO -1 HIV Transmission Modes X Sexual contac OPerinatal * Transfusion IIV drug ,W Homosexual El Other Age and Sex Distribution of Reported AIDS Cases 200r 150 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60+ Number of Adults Alive with HIV 500,000._v - _--- 450,000 - 400,000 350,000 300,000 250,000 200,000 150,000 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 61 LESOTHO Adult HIV Prevalence 30.0 --------- - ------ 25.0 20,0 <15.0 0 0.0 5.01 0.0 - _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 HIV Incidence 10 D 4 -- ----.. --------.. 0 0 C .SO.035 Z0,03 tp 025 0.02 0' 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 5000 '_i 0+0jt i 7 _ - i : 0~ 0 X -^- -- - - >V_ _~-_ w-, v ._ ...0.................................5. , - . , . , , . ,.,._.___.. 4500 3500 2 1,0 86 1. 19 9.....0 199 199 199 199 2;000 2 002 2004 2006 200 200 2012 20 50,000 45,000 40,000 35,000 30,0 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 62 LESOTHO Cumulative AIDS Cases 500 000 . 450,000 400,000 350,000 300,000 250,000 200,000- 150,000 100,000 50,000 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 Annual Deaths to Young Aduls (15-49) 60,000 -.. 50,000 40,000 f. . . . 30,000.. .4-With AIDS -:--.jNo AIDS 20,000 10,000 v. 0 -. 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 Under Five Morality Rate 140. 130 120 110 100 -4-With AIDE 90 f-'| -*-No AIDS 80~ 70i -- _ _ _ 60 1 . . I 50~ 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 63 LESOTHO Total Population Size 3,500 000 . - ....... 7 7 i 3,200,000 2,900,000 2,600,000 --.--Wffl AIDS t 5 : { | ~~~~~~~~~~-M9-No AIDS 2,300,000 2,000,000 1,700,000 1,400,000 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 Annual Population Growth Rate 0 03 ----------- 0.028 0 .0 2 6 ... ..::0 ;: ; ; 00-: -00.'0 ; -0 : 0 ,>* g; 0 0 ; - W- No AIDS 600,000 500,000 400,000 300,000 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 66 LESOTHO Gross Domestic Product 7,5000 7,000 5,500 . |+NOAIDSi O5,000 .-4-WIth AIDS| F 4500 -- 4,000 1= 3,500 3,000 2,500 2,000 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 , ~~~~~~~Annual GDP Growth Rate 1250 1983 1990 1992 1994 1996 1 2000 2002 2004 2006 2008 2010 2012 2014 -6 'H - GDP per Capita 2200 -S 21002 -12000 190 180 1 690t-- ' | With AIDSI 180 1 0 | |-FNOAIDS | 1961988 1990 1992 1994 1996 199 2000 2002 2004 2006 2008 2010 2012 2014 -4~~~~~~~~~6 22003I 215003 , 2 1000 19100 1700 v 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 67 Lesotho: Assumptions used in the calculation of Cost of HIVWAIDS Mitigation Programs Annex IlIl LESOTHO: Assumptions used in the calculation of COS OF HIV/AIDS Mitigation Programs Indicator Per Year PREVENTION+MITIGATION _ Total Cost Million (Maloti) Average Cost Per year Million (MaLoti) 1,106 Total Cost % to GDP Average Cost % to GDP 21.9% PREVENTION Total Cost Million (Maloti) I Average Cost per year Million (Maloti) 311 Total Cost % to GDP j Average Cost Per year % to GDP 6.2% 1. AGE 0-5 Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 5 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 0.1% la. AGE 0-6 months: MTC Policy: Zero MTC Source: Herald (Zimbabwe Daily News Paper) July 26,2000 Cost of Nevirapine (US$) $8 Exchange rate Maloti per US$ 7.4 Cost of Nevirapine (Maloti) 59 Number of Females 15-49 (Average 2000-15) 121,308 Proportion of these Pregnant 15% Pregnant Women 15-49 (Average 200-15) 18,196 Proportion of these Pregnant women HIV+ 25% Mothers requiring Nevirapine 4,549 Total Cost per year Million (Maloti) Average Cost per year Million (Maloti) 0.269 Real GDP (1999/2000) Million Maloti _ Ratio to GDP Average Ratio for 2000-15 0.005% lb. AGE 0.6-5: Policy: Health care Source: Health Budget (Actual) for 1997/8 Million (Maloti) 195 Population in 1999 Million 2.100 Percapita Health Expenditure 93 Cost per Child per year ( 1/2 of per capita Health exp) 46 Number of children 0.6-5 (Excluding Orphans) (Average 2000-15) 111,619 Total cost per year Million (Maloti) 68 Lesotho: Assumptions used in the calculation of Cost of HIVIAIDS Mitigation Programs Annex l1l 2 LESOTHO: Assumptions used In the calculation of COS OF HIVIAIDS Mitigati n Programs Ind!cator Per Year Average Cost per year Million (Maloti) 5 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 0.1% 2. AGE 6-14: Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 32 Real GDP (1999/2000) Million Maloti 4 Ratio to GDP Averape Ratio for 2000-15 08 2a. AGE 6-10: Pos pye ACe Specific Sex Education Source: Education Budget (Actual) for 1995/6 Million (Maloti) 438 Population in 1999 Million _2.100 Percapita Education Expenditure 208 Cost per Child per year ( 1/5 of per capita Education exp) _42 Number of children 6-10 (Excluding Orphans) (Average 2000-15) 350,011 Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 15 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 0.3% 2b. AGE 11-14: Policy: Age Specific Sex Education/Youth Activities Source: Education Budget (Actual) for 1995/6 Million (Maloti) 438 Population in 1999 Million 2.100 Percapita Education Expenditure 208 Cost per Young Child per year ( 1/4 of per capita Education exp) 52 Number of Young children 11-14 (Average 2000-15) 332,966 Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 17 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 0.3% 3. AGE 15-19: Policy: Age Specific Sex Education/Youth & Community Activities/Condom Distribution Source: Total cost per year Million (Maioti)________ Average Cost per year Million (Ma loti) 56 Real GDP (1999/2000) Million Maloti 69 Lesotho: Assumptions used in the calculation of Cost of HIV/AIDS Mitigation Programs Annex iII 3 LESOTHO: Assumptions used in the calculation of COS OF HIV/AIDS Mitigation Programs Indicator Per Year Ratio to GDP Average Ratio for 2000-15 1.1% 3a. AGE 15-19: Both Male and Female Policy: Age Specific Sex Education & Youth Activities _ Education Budget (Actual) for 1995/6 Million (Maloti) 437.5 Population in 1999 Million 2.100 Percapita Education Expenditure 208 Cost per Youth peryear ( 1/2 of per capita Education exp) 104 Number of MALE & FEMALE Youth 15-19 (Average 2000-15) 304,286 Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 32 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 0.6% 3b. AGE 15-19: Male onLy Policy: Condom Distribution CONDOM cost per year (2 /week, 1 condom M 1.50) 156 Number of MALE Youth 15-19 (Average 2000-15) 155,555 Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 24 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 0.5% 4. AGE 20+ Policy: Work place condom distribution/lEC/Voluntary and free counseling Source: Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 217 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 4.3% 4a. AGE 20+: Both Male and Female Source: Education Budget (Actual) for 1995/6 Million (Maloti) 437.5 Population in 1999 Million 2.100 Percapita Education Expenditure 208 Cost per Adult per year ( 1/4 of per capita Education exp) - 52 Health Budget (Actual) for 1997/8 Million (Maloti) | 194.518 Population in 1999 Million 2.100 Percapita Health Expenditure 93 Counseling Cost (1/3 of Health percapita exp) 31 Cost per Adult (20-64) per year 83 Number of Adults 20-64 (Average 2000-15) 1,158,436 70 Lesotho: Assumptions used in the calculation of Cost of HIV/AIDS Mitigation Programs Annex IlIl 4 LESOTHO: Assumptions used in the calculation of COS OF HIV/AIDS Mitigation Programs Indicator Per Year Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 96 Real GDP (1999/2000) Million Maloti Ratio to GDP __.____. ._. Average Ratio for 2000-15 1.9% 4b. AGE 20+: Male only_ Source: CONDOM cost per MALE adult year (4 per week, 1 condom M 1.5) 234 Number of MALE Adults 20-59 (Average 2000-15) 518, 557 Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 121 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 2.4% MITIGATION Total Cost Million (Maloti Averaae Cost Million (Maloti) 807 Total Cost % to GDP Averaae Cost % to GDP 15.7% 1. AGE 0-14 Policy:Orphan Care Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 67 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 1.3% la. AGE 0-5: Policy: Improved quality of life Source: Health Budget (Actual) for 1997/8 Million (Maloti) 19_ 5 Population in 1999 Million 2.100 Percapita Health Expenditure 93 Cost per Child per year ( 1/2 of per capita Health exp) 46 Real GDP (1999/2000) Million Maloti __260,445 Ratio to GOP Average Cost per year Million (Maloti) -___12 Real GDP (1999/2000) Million Maloti _ Ratio to GDP Average Ratio for 2000-15 0.2% lb. AGE 6-14 ORPHANS: Policy: Provide better health services and education Source: 71 Lesotho: Assumptions used in the calculation of Cost of HIV/AIDS Mitigation Programs Annex IlIl 5 LESOTHO: Assumptions used in the calculation of COS OF HIV/AIDS Mitigation Programs Indicator Per Year TOTAL COST of ALL ORPHANS (Maloti Million) Average Cost per year Million (Maloti) 66 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 1.4% ,lb(. AGE 6-14 NEW ORPHANS: Education Budget (Actual) for 1995/6 Million (Maloti) 437.5 Population in 1999 Million 2.100 Percapita Education Expenditure r 208 Cost per Child per year ( 1/2 of per capita Education exp) | 104 Health Budget (Actual) for 1997/8 Million (Maloti) 194.518 Population in 1999 Million 2.100 Percapita Health Expenditure 93 Cost per Child per year ( 112 of per capifa Health exp) 46 Cost of FOOD per Child per year 100 Maloti per year 100 Total Cost per Orphan per year 250 Cost per Orphan for 15 years 3,757 NEW orphans (Average 2000.15) 14,538 TOTAL COST of New ORPHANS (Maloti Million) (10 years per orphan) Average Cost per year Million (Maloti) 55 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 1.0% lb(li). AGE 6-14 EXISTING ORPHANS: l _l EXISTING orphans as of END OF 1999 ! 14,911 Cost per Orphan per year (estimated same as above) 250 Cost per Orphan for 8 years 2004 Cost per Orphan for 8 years adjusted for Inflation 0% TOTAL COST of EXISTING ORPHANS (Maloti Million) (8 years per orphans) 239 Average Cost per year Million (Maloti) 30 Real GDP (1999/2000) Million Maloti _ Ratio to GDP Average Ratio for 2000-15 0.8% 2. AGE 15-49: Policy: Improved quality of Life by providing Medciniesfood, water Source: Direct and Indirect Costs, WHO Team Report, November 1994. Cost of medcineslhospitalization per HlV patpient per year Maloti 4,392 Number of Adults 15-49 (Average 2000-15) 161,107 Total cost per year Million (Maloti) Average Cost per year Million (Maloti) 708 Real GDP (1999/2000) Million Maloti Ratio to GDP Average Ratio for 2000-15 13.6% 3. AGE 50+: 72 Lesotho: Assumptions used in the calculation of Cost of HIV/AIDS Mitigation Programs Annex IlIl 6 LESOTHO: Assumptions used in the calculation of COS OF HIV/AIDS Mitigation Programs Indicator Per Year Policy: Improved quality of life through pension Source: Average Pension Amount for Civil Servants (Actual for 1995/6 Million (Maloti) 600 Cost per Person per year ( 1/3 of average civil servant's pension) 200 Number of persons 50+ (Average 2000-15) 107,072 Total cost per year Million (Maloti) l Average Cost per year Million (Maloti) 21 Real GDP (1999/2000) Million Maloti Ratio to GDP l Average Ratio for 2000-15 0.4% 73