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Economic Impact of HIV/AIDSin Botswana: Linkages between
Macroeconomic, Sector and Household levels
HIV/AIDS intervention in developing countries: use of Cost Effectiveness and Cost
Benefit analysis to guide Policy and ActionHarvard School of Public Health
Sept 13-15 2006
Keith Jefferis and Anthony Kinghorn
Background
Previous macroeconomic impact study 2000Roll-out of ARTNational Strategic Framework costing – considered “unaffordable”Subsequent work on macroeconomic impact in Botswana (IMF) and elsewhere in Southern Africa
Ongoing Study - 2006
Funded by UNDP, on behalf of GoB/NACAParallel demographic impact studyReview of earlier studies
Accuracy of projectionsMethodology
ComponentsUpdating of macroeconomic modelsFirm/industry reviewCosting/fiscal impactHousehold/poverty impact
Macroeconomic Modelling
Macroeconomic Modelling
Aim to capture variety of macro impact channels:Labour force
slower growth (demographics)changed age & experience structurelabour productivity (illness/absence)
Broader macro impacts overall productivity growthexpenditure diversionsavings & investment
Macroeconomic Modelling
Dual approach: Aggregate production function (Solow growth model) incorporating formal and informal sectors, skilled & unskilled labourComputable General Equilibrium (CGE) model incorporating range of economic sectors and labour and household categories
Both solve for macroeconomic equilibrium on the basis of calibrated model & input assumptions (e.g. demographics)
Macroeconomic Modelling
Scenario modelling:No AIDSwith AIDSAIDS with treatment (ART)
Solve annually and roll forward to 2021Outputs include GDP, growth, per capita incomes, employment, wages
Model Structure (Agr. PF)
FormalSector
InformalSector
Capital
SkilledLabour
UnskilledLabour
Population & AIDS
OUTPUTProductivity
(TFP)
Illustrative GDP Growth Impact
0%
1%
2%
3%
4%
5%
6%
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
No AIDS AIDS no ART AIDS with ART
Contributions to GDP GrowthNo-AIDS vs AIDS with ART
TFP, 31%
Skilled, 14%
Unskilled, 6%
Capital, 49%
Illustrative Impact - Real GDP per capita
10,00011,00012,00013,00014,00015,00016,00017,00018,00019,000
2001 2004 2007 2010 2013 2016 2019
P m
illio
n (2
001
pric
es)
No AIDS AIDS No ART AIDS with ART
Key Modelling Results & Conclusions
Labour market effects through:demand (investment, wage levels, productivity)supply (size & composition of LF)
Result: less favourable employment trends (reduced demand outweighs reduced supply)Higher un/under-employment and slower wage growthOnly partially alleviated by ART
Household-level Impact
Household Impact
Poverty impact simulated through use of household survey data (income & expenditure, 2002/03 & AIDS impact, 2004)Superimpose HIV/AIDS on population in accordance with demographic prevalence trendsSimulate income and expenditure effects and calculate impact on poverty headcount rates
CGE Results - Poverty
19
20
21
22
23
24
2003 05 07 09 11 13 15 17 19 21
Nat
iona
l pov
erty
hea
dcou
nt (%
)
With AIDS
Without AIDS
Treatment
Costing & Fiscal Impact of HIV/AIDS
Methodology
Demographic projectionsART, No-ART, No-AIDS
UtilisationVarious protocols, policies, site dataCalibration to empirical data - plausible Limitations
CostsUnit costs of ART, Orphan Grant, program expenditure history, step down for in- and outpatient
Projected Total Number of adults and children on ART(Provisional - illustrative)
0
20
40
60
80
100
120
140
160
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
thou
sand
s
ART Best estimate ART 10% lower ART 10% higher
• There will continue to be large, rapidly rising numbers on ART
• Some uncertainty about length of survival on ART, uptake rates that may affect scenarios
Projected Number of Total deaths per year(Provisional - illustrative)
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
No AIDS No ART ART Best estimate
• Needs for terminal care should not increase substantially beyond recent levels
Costs
Preliminary projected Costs – % contribution of selected interventions No ART(Best estimate)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
P m
illio
n
Hospital In-patient Ambulatory excl ART ARTHBC Prevention Prog. mgt.OVC
Preliminary projected Costs – % contributed by selected interventions combined with ART (Best estimate)
0%10%20%30%40%50%60%70%80%90%
100%
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
P m
illio
n
Hosp. in-patient Ambulatory excl ARTART HBC Prevention Prog. mgtOVC OA pensions (cost vs. no ART)
Key preliminary findings
Terminal care and hospital bed needs are unlikely rise substantially above 2001/2 levels until after 2015, but substantial backlogs and referral system inefficiencies remainThe double orphan epidemic should reach a plateau soon under high ART coverage scenariosPrevention expenditure is uncertain but costing shows importance of effective prevention for sustainabilityCapacity requirements of sustainable, effective ART models are still unclear
Current models and implications for e.g. HBC and hospital loads are not clear
Preliminary Conclusions: Impact on Government Budget
Overall fiscal impact of HIV/AIDS expected to be substantial, but (just) manageableBulk of HIV/AIDS-related costs required whether or not ART is provided (ART adds 50% to costs)Incremental costs of ART can probably be partially – but not completely - funded from taxes on extra GDP generatedOverall costs of HIV/AIDS cannot be financed from budget deficitsNeed to reprioritise expenditures within health budget, HIV and AIDS program and elsewhereTougher trade-offs required if ART is providedDonor resources needed to keep fiscal burden manageable
Summary of Preliminary Conclusions
Preliminary Conclusions –Methodological issues
Policy making advantages of combined macroeconomic, sectoral and poverty analysis
Shows linkages between sectoral decisions and effectsClearer tradeoffs for prioritisation
Fiscal analysisMacro planning – establishing “common language” with health and programme plannersDeveloping implicit policy scenarios and interpreting them for different audiences and purposes
Preliminary Conclusions –Methodological issues
Macroeconomic analysisMacro modelling approaches valid and usefulCGE + micro-simulation particularly useful in providing integrated approachSome key input parameters – investment and productivity impacts – have uncertain empirical basis – key areas for further, micro-level research
HIV impact on impact on firms’ decision making processesTrade-off between cuts in recurrent and investment spending in fiscal decisions
Preliminary Conclusions – Policy making implications
Risks of inadequate NSF costingPrioritisationObjectives of costingCost vs cost benefit focus
Cost control essential (ART, welfare)Consider cost & clinical effectiveness of ART distribution channels; innovative solutions necessaryExploring implications of Abuja Declaration targets – Health as 15% of public expenditureAdvocacy to donor community
Implications – other countries
Botswana somewhat exceptional (in sub-Saharan Africa):
Very high HIV prevalence rateHigh income, GDP growthSavings surplus (over investment)Capital intensiveFiscal, BoP surplusesDomestically-financed ART provision feasible but tough even in favourable environment
Methodological approaches useful and transferable depending on quality of dataResults elsewhere could well be different elsewhere