Effects of AIDS-related disability on workforce participation and earned income in Botswana: A quasi-experimental evaluation

Abstract

Background: Botswana is regarded as a leader of progressive HIV/AIDS policy, as the first country in sub-Saharan Africa to establish a free, national antiretroviral therapy program. In light of such programmatic successes, it is important to evaluate the potentially changing relationship of HIV/AIDS to the wellbeing of individuals, households, and institutions in the country. Methods: We evaluate the effects of HIV-related illness on absenteeism and earnings several years after the start of the national treatment program among a random sample of adults in Botswana using survey data from 3999 individuals aged 15 to 49, using quasi-experimental methods. We compare absenteeism between individuals with and without HIV-related illness, using a propensity score matching approach. We then estimate the effect of HIV-related illness on earnings using a Heckman selection model to account for selection into the workforce. We stratify our analyses by sex. Results: Men and women with HIV-related illness were absent by about 5.2 and 3.3 additional days, respectively, in the month prior to the survey compared to matched controls, and earned approximately 38% and 43% less, respectively, in the month prior to the survey compared to those without HIV-related illness. Conclusions: HIV-related illness appears to increase absenteeism in this sample and dramatically reduce earnings. The findings suggest a need for policies that confer greater financial security to individuals with HIV/AIDS in Botswana.

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Farahani, M. , Roumis, D. , Mahal, A. , Holmes, M. , Moalosi, G. , Molomo, C. and Marlink, R. (2013) Effects of AIDS-related disability on workforce participation and earned income in Botswana: A quasi-experimental evaluation. Health, 5, 409-416. doi: 10.4236/health.2013.53055.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] [1] UNAIDS (2010) Progress Report of the National Re-sponse to the 2001 Declaration of Commitment on HIV and AIDS, Botswana Country Report.
[2] CSO (2009) 2008 Botswana AIDS impact survey III (BAIS III). Cen-tral Statistics Office, Government of Bots wa-na.
[3] Cuddington, J.T. (1993) Modeling the macroe-conomic effects of AIDS, with an application to Tanzania. World Bank Econ Rev, 7, 173-189. doi:10.1093/wber/7.2.173
[4] Bonnel, R. (2000) HIV/AIDS and economic growth: A global perspective. South African Journal of Economics, 68, 360-379. doi:10.1111/j.1813-6982.2000.tb01282.x
[5] Cuddington, J.T. and Hancock, J.D. (1994) Assessing the impact of AIDS on the growth path of the Malawian economy. Journal of Development Economics, 43, 363-368. doi:10.1016/0304-3878(94)90013-2
[6] Arndt, C. and Lewis, J.D. (2000) The macro implications of HIV/AIDS in South Africa: A preliminary assessment. South African Journal of Economics, 68, 380-392. doi:10.1111/j.1813-6982.2000.tb01283.x
[7] MacFarlan, M. and Sgherri, S. (2001) The macroeconomic impact of HIV/AIDS in Botswana. In press.
[8] Jefferis, K., Kinghorn, A., Siphambe, H. and Thurlow, J. (2008) Ma-croeconomic and household-level impacts of HIV/AIDS in Botswana. AIDS, 22, S113-S119. doi:10.1097/01.aids.0000327631.08093.66
[9] Lisk, F. (2002) Labour market and employment implica tions of HIV/AIDS. Working Paper 1: International Labor Organ-ization (ILO) Programme on HIV/AIDS and the World of Work, Geneva.
[10] Kgathi, D.L., Ngwenya, B.N. and Wilk, J. (2007) Shocks and rural livelihoods in the Oka-vango Delta, Botswana. Development Southern Africa, 24, 289-308. doi:10.1080/03768350701327186
[11] Greener, R. (2002) AIDS and macroeconomic impact. Working Paper, Inter-national AIDS Economics Network.
[12] Greener, R., Jefferis, K. and Siphambe, H. (2000) The impact of HIV/AIDS on poverty and inequality in Botswana. South African Journal of Economics, 68, 393-404. doi:10.1111/j.1813-6982.2000.tb01284.x
[13] Thurlow, J. (2007) Is HIV/AIDS undermining Botswana’s “success story”? IFPRI Discussion Paper 00697, Washington DC.
[14] Bachmann, M.O. and Booysen, F.L.R. (2004) Relation ships between HIV/AIDS, income and expendi-ture over time in deprived South African households. AIDS Care: Psychological and Socio-Medical Aspects of AIDS/HIV, 16, 817-826.
[15] Bachmann, M.O. and Booysen, F.L.R. (2006) Economic causes and effects of AIDS in South African households. AIDS, 20, 1861-1867. doi:10.1097/01.aids.0000244205.03382.84
[16] Bachmann, M.O. and Booysen, F.L.R. (2003) Health and economic impact of HIV/AIDS on South African house holds: A co-hort study. BMC Public Health, 3, 8. doi:10.1186/1471-2458-3-8
[17] Duraisamy, P., Ganesh, A.K., Homan, R., Kumarasamy, N., Castle, C., Sripriya, P., et al. (2006) Costs and financial burden of care and support services to PLHA and households in South India. AIDS Care: Psychological and Socio-Medical Aspects of AIDS/HIV, 18, 121-127. doi:10.1080/09540120500159359
[18] Naidu, V. and Harris, G. (2005) The impact of HIV/AIDS morbidity and mortality on households—A review of household studies. South African Journal of Economics, 73, 533-544. doi:10.1111/j.1813-6982.2005.00037.x
[19] Russell, S. (2004) The economic burden of illness for households in developing countries: A review of studies focusing on malaria, tuberculosis, and human immunodeficiency vi-rus/acquired immunodeficiency syndrome. American Journal of Tropical Medicine and Hygiene, 71, 147 155.
[20] Tekola, F., Reniers, G., Mariam, D.H., Araya, T. and Davey, G. (2008) The economic impact of HIV/AIDS morbidity and mortality on households in Addis Ababa, Ethiopia. AIDS Care: Psychological and Socio-Medical Aspects of AIDS/HIV, 20, 995-1001. doi:10.1080/09540120701777256
[21] Wyss, K., Hutton, G. and N’Diekhor, Y. (2004) Costs attributable to AIDS at household level in Chad. AIDS Care-Psychological and Socio-Medical Aspects of AIDS/ HIV, 16, 808-816. doi:10.1080/09540120412331290167
[22] Rajaraman, D., Russell, S. and Heymann, J. (2006) HIV/ AIDS, income loss and economic survival in Botswana. AIDS Care: Psychological and Socio-Medical Aspects of AIDS/HIV, 18, 656-662. doi:10.1080/09540120500287010
[23] Bussmann, H., Wester, C.W., Ndwapi, N., Grundmann, N., Gaolathe, T., Puvimanasinghe, J., et al. (2008) Five-year outcomes of initial patients treated in Botswana’s Nation al Antiretro-viral Treatment Program. AIDS, 22, 2303 2311. doi:10.1097/QAD.0b013e3283129db0
[24] Nixon, S., Hanass-Hancock, J., Whiteside, A. and Barnett, T. (2011) The increasing chronicity of HIV in sub-Saha ran Africa: Re-thinking “HIV as a long-wave event” in the era of widespread access to ART. Globalization and Health, 7, 41. doi:10.1186/1744-8603-7-41
[25] Oliva, J. (2009) Labour participation of people living with HIV/AIDS in Spain. Health Economics, 19, 491-500. doi:10.1002/hec.1487
[26] Dray-Spira, R., Lert, F., Ma-rimoutou, C., Bouhnik, A.-D. and Obadia, Y. (2003) So-cio-economic conditions, health status and employment among persons living with HIV/ AIDS in France in 2001. AIDS Care: Psychological and Socio-Medical Aspects of AIDS/HIV, 15, 739-748. doi:10.1080/09540120310001618595
[27] Dray-Spira, R., Persoz, A., Boufassa, F., Gueguen, A., Lert, F., Allegre, T., et al. (2006) Employment loss fol lowing HIV infection in the era of highly active antiretro viral therapies. European Journal of Public Health, 16, 89-95. doi:10.1093/eurpub/cki153
[28] Ezzy, D., De Visser, R. and Bartos, M. (1999) Poverty, disease progression and employment among people living with HIV/AIDS in Australia. AIDS Care: Psychological and Socio-Medical Aspects of AIDS/HIV, 11, 405-414. doi:10.1080/09540129947785
[29] Massagli, M.P., Weissman, J.S., Seage 3rd, G.R. and Ep stein, A.M. (1994) Correlates of employment after AIDS diagnosis in the Boston health study. American Journal of Public Health, 84, 1976-1981. doi:10.2105/AJPH.84.12.1976
[30] Rabkin, J.G., McEl-hiney, M., Ferrando, S.J., Van Gorp, W. and Lin, S.H. (2004) Predictors of employment of men with HIV/AIDS: A longitudinal study. Psychosomatic Me dicine, 66, 72-78. doi:10.1097/01.PSY.0000108083.43147.6D
[31] Yelin, E.H., Greenblatt, R.M., Hollander, H. and McMaster, J.R. (1991) The impact of HIV-related illness on employment. American Journal of Public Health, 81, 79-84. doi:10.2105/AJPH.81.1.79
[32] Auld, M.C. (2002) Dis-entangling the effects of morbidity and life expectancy on labor market outcomes. Health Economics, 11, 471-483. doi:10.1002/hec.753
[33] Leigh, J.P., Lubeck, D.P., Farnham, P. and Fries, J.F. (1995) Potential and actual workdays lost among patients with HIV. Journal of Ac-quired Immune Deficiency Syndromes and Human Retro-virology, 8, 392-398. doi:10.1097/00042560-199504000-00011
[34] Scitovsky, A.A. and Rice, D.P. (1987) Estimates of the direct and indirect costs of acquired immunodeficiency syndrome in the United States, 1985, 1986, and 1991. Public Health Reports, 102, 5-17.
[35] Mullins, C.D., Whitelaw, G., Cooke, J.L. and Beck, E.J. (2000) Indirect cost of HIV infection in England. Clinical Therapeutics, 22, 1333-1345. doi:10.1016/S0149-2918(00)83030-1
[36] Oliva, J., Roa, C. and Llano, J. (2003) Indirect costs in ambulatory pa-tients with HIV/AIDS in Spain: A pilot study. Pharma-coeconomics, 21, 1113-1121. doi:10.2165/00019053-200321150-00005
[37] Kass, N.E., Munoz, A., Chen, B., Zucconi, S.L. and Bing, E.G. (1994) Changes in employment, insurance, and in come in relation to HIV status and disease progression. The multicenter AIDS cohort study. Journal of Acquired Im-mune Deficiency Syndromes, 7, 86-91.
[38] Fox, M.P., Rosen, S., MacLeod, W.B., Wasunna, M., Bii, M., Foglia, G., et al. (2004) The impact of HIV/AIDS on labour productivity in Kenya. Tropical Medicine & Inter national Health, 9, 318-324. doi:10.1111/j.1365-3156.2004.01207.x
[39] Habyarimana, J., Mbakile, B. and Pop-Eleches, C. (2010) The impact of HIV/AIDS and ARV treatment on worker absenteeism. Journal of Human Resources, 45, 809-839. doi:10.1353/jhr.2010.0032
[40] Larson, B.A., Fox, M.P., Rosen, S., Bii, M., Sigei, C., Shaffer, D., et al. (2008) Early effects of antiretroviral therapy on work performance: Preliminary results from a cohort study of Kenyan agricultural workers. AIDS, 22, 421-425. doi:10.1097/QAD.0b013e3282f3cc0c
[41] Mahal, A., Canning, D., Odumosu, K. and Okonkwo, P. (2008) As-sessing the economic impact of HIV/AIDS on Nigerian households: A propensity score matching appro ach. AIDS, 22, S95-S101. doi:10.1097/01.aids.0000327629.62350.59
[42] Rosen, S., Ketlhapile, M., Sanne, I. and Desilva, M.B. (2008) Differences in normal activities, job performance and symptom prevalence between patients not yet on antire-troviral therapy and patients initiating therapy in South Africa. AIDS, 22, S131-S139.
[43] Riviello, E.D., Ster-ling, T.R., Shepherd, B., Fantan, T. and Makhema, J. (2007) HIV in the workplace in Botswana: Incidence, prevalence, and disease severity. AIDS Re search and Human Retroviruses, 23, 1453-1460. doi:10.1089/aid.2007.0132
[44] Canning, D., Mahal, A., Odumosu, O. and Okonkwo, P. (2006) The impact of HIV/AIDS on Nigerian households. In: Adeyi, O., Kanki, P., Odutolu, O. and Idoko, J., Eds., AIDS in Nigeria: Harvard Center for Population and De velopment Studies, Harvard University Press, Cambridge, 193-212.
[45] Dehejia, R.H. and Wahba, S. (2002) Pro-pensity score matching methods for nonexperimental causal studies. Review of Economics and Statistics, 84, 151-161. doi:10.1162/003465302317331982
[46] Rosenbaum, P.R. and Rubin, D.B. (1983) The central role of the propensity score in observational studies for causal effects. Biome-trika, 70, 41-55. doi:10.1093/biomet/70.1.41
[47] Guo, S. and Fraser, M.W. (2009) Propensity score analysis: Statistical methods and applications. Sage Publications, Thousand Oaks.
[48] Rubin, D.B. (1979) Using multivariate matched sampling and regression adjustment to control bias in observational studies. Journal of the American Statistical Association, 74, 318-328. doi:10.2307/2286330
[49] Rubin, D.B. (2006) Matched sampling for causal effects. New York Cambridge Uni-versity Press, Cambridge. doi:10.1017/CBO9780511810725
[50] Heckman, J.J., Ichimura, H. and Todd, P. (1998) Matching as an econo-metric evaluation estimator. Review of Economic Studies, 65 261-294. doi:10.1111/1467-937X.00044
[51] Gronau, R. (1974) Wage comparisons—A selectivity bias. The Journal of Political Economy, 82, 1119-1143. doi:10.1086/260267
[52] Wooldridge, J.M. (2002) Eco-nometric analysis of cross section and panel data. MIT Press, Cambridge.
[53] Heckman, J.J. (1979) sample se-lection bias as a specification error. Econometrica, 47, 153-161. doi:10.2307/1912352
[54] Cameron, A.C. and Trivedi, P.K. (2005) Microeconomet rics: Methods and applications. Cambridge University Press, Cambridge. doi:10.1017/CBO9780511811241
[55] Becker, S.O. (2002) Estimation of average treatment effects based on propensity scores. Stata Journal, 2, 358 377.
[56] Filmer, D. and Pritchett, L.H. (2001) Estimating wealth effects without expenditure data or tears: An application to edu-cational enrollments in states of India. Demography, 38, 115-132.
[57] Wooldridge, J.M. (2008) Introductory econometrics: A modern approach. South-Western College Publishing, Cincinnati.
[58] Farahani, M., Tilahun, H. and Marlink, R. (2010) Seven year mortality outcomes of the Botswana national HIV/ AIDS treatment program. Unpublished Report.
[59] UNAIDS (2008) Epidemio-logical fact sheet on HIV and AIDS: Core data on epide-miology and response. Botswana: UNAIDS, WHO Working Group on Global HIV/ AIDS and STI Surveillance.

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