Economics of HIV/AIDS in Developing CountriesLecture Summary Overview of HIV/AIDS infection rates Prevention versus Treatment (Canning article) Accuracy measuring costs/benefits of each Treatment benefits (Thirumurthy et al. article) Prevention critique (Oster article)Country2005 Adult HIV prevalence(ages 15–49)2011 Adult HIV prevalence(ages 15–49)Swaziland 38.8 27.7Botswana 37.3 25.2Lesotho 28.9 23.4Zimbabwe 24.6 16.7South Africa 21.5 18.9Namibia 21.3 16.0Zambia 17.0 12.4Mozambique 16.1 10.6HIV/AIDS Infection RatesHIV/AIDS Infection RatesRegional comparisons of HIV in 2015World regionAdult HIV prevalence(ages 15–49)Total HIVcasesAIDS deathsin 2015Sub-Saharan Africa4.7% 25.5 million 1.1 millionWorldwide 0.8% 36.7 million 1.1 millionWestern Europe& North America0.3% 2.4 million 22,000Figure 2.2 Changes in the incidence rate of HIV infection, 2001 to 2009• Increasing >25%• Stable• Decreasing >25%UNAIDS, Global Report 2010Economics of HIV/AIDS in Africa 25.5 million infected in sub-Saharan Africa (roughly the same as the top-10 most populated US cities) Far-reaching consequences: death, lower productivity, orphans, food security, lower life expectancy reduced human capital investments 2 ways to reduce burden of HIV/AIDS: Treatment PreventionPrevention Goal is to limit the transmission of AIDS to non-infected individuals Different types of prevention interventionsTreatment Antiretroviral therapy (ART) comprises an important part of policy response Treatment being scaled-up rapidly Large price reductions and growing donor support Sub-Saharan Africa: Almost 68% people needing ART treatment receiving it by 2012 WHO changed threshold to be eligible for treatment from CD4 count of <350 to <500Prevention versus Treatment Debate over how best to allocate scarce resources Public health argument Economics argumentHow are HIV prevalence rates measured? See Canning Table 1 Historically what happened? What types of selection bias would this lead to? What are difficulties getting accurate HIV prevalence rates? What is the ideal approach to measure HIV infection rates? Around 2003, started doing this with Demographic and Health Surveys Rates were much lower than predicted by UNAIDS or country statistical offices Debate over whether new data confirmed effectiveness of prevention programs to lower HIV rates OR highlighted size of selection biasMeasuring HIV Prevalence Rates Define metric for measuring impact: Cost per DALY (disability adjusted life years) saved Cost effective: $1-100 USD per DALY saved compared to $350-2000 USD for ARTs (Canning--Table 3 meta-analysis) If only treatment, then no learning/understanding of how epidemic spreads and problem will continue into next period Monitoring/compliance problems with treatment could lead to drug resistanceArguments for Prevention Interventions Ethical arguments Impacts on adult labor force If adults die, orphan population increases, schooling declines, child labor increases poverty trap Problems with prevention/education: people may not follow advice, hard to measure true impactArguments for Treatment Treatment studies understate returns to treatment (Thirumurthy et al., 2008) Prevention studies overstate returns to prevention (Oster, 2012)Best Counter-Argument for TreatmentTreatment Proper cost-benefit analysis of ART requires information on full range of costs and benefits Clinical/medical benefits relatively well documented Less known about non-clinical impacts of ARTMedical Evidence Shows that ART Works Many studies document effectiveness in US and Europe Large gains in CD4 count within 6 months (Hammer et al. 1997) Evidence from developing countries equally encouraging Kenya, Senegal, and South Africa: Median CD4 gain of 82 and 180 cells/mm3at 6 and 18 months Survival probability of 86 percent at 24 months (Laurent et al. 2002; Coetzee et al. 2004)Why Also Need Socio-economic Evidence Can ART stem the socio-economic impacts of HIV? Declining productivity (Fox et al. 2004); Reduced schooling of children (Case and Ardington 2006; Evans and Miguel 2007) Macroeconomic consequences (Bell, Devarajanand Gersbach 2006) Policy context If donors & governments are going to spend a lot of money on ART, what returns can be expected?Rule of Rescue• Government is willing to spend an unlimited amount of money on an identified group of people in danger of dying• You could get more “bang for your buck” spending the limited money on other things that are cheaper and save more livesRule of Rescue (2)• ART costs $350‐2000/DALY saved, but they are identified with a picture• Child vaccinations costs $20‐30/DALY saved, but they are unidentified, anonymous statistical lives saved, someone saved but not sure who. Child vaccines save child at age 1 but then lives to age 70 so lots of life‐years saved.The Economic Impact of AIDS Treatment: Labor Supply in Western KenyaHarsha ThirumurthyJoshua Graff ZivinMarkus GoldsteinJournal of Human Resources, (2008), 43(3): 511-552Window of Opportunity for Studying Household Behavior Identifying causal effect of health on economic outcomes Challenges in establishing causality (Strauss & Thomas 1998) Main outcomes of interest Labor supply of patients Market and non-market labor supply of household members Children’s education Nutrition of young childrenEvidence from an Early ART Treatment Program• Study conducted in rural region of western Kenya• HIV clinic opened in 2001, scaled-up in 2004 (AMPATH)• AMPATH provided care for over 50,000 persons by 2004• Eligible patients receive free HIV care, including ARTSurvey Data Collected in Kenya Longitudinal survey with patients from HIV clinic and households in surrounding villages Three waves of data from 2004-2006 Linked medical records are an important feature 224 patients who began receiving ART at various times prior to second wave 503 households selected randomly from community Comparison of outcomes over time for treatment group (receiving ART) Comparison of outcomes over time for control group (random sample from population) What do you need to measure full impact of treatment?Methodology i+1 2() + is labor supply for individual i in time tiis individual fixed effect
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