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Jean-Paul Moatti*, Bruno Ventelou*, Yann Videau*, Michel Kazatchkine**

“Time is costly”: Modelling the macro-economic impact of scaling up access to antiretroviral treatment for HIV/AIDS. Jean-Paul Moatti*, Bruno Ventelou*, Yann Videau*, Michel Kazatchkine** *INSERM Research Unit 379, University of the Mediterranean, Marseille

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Jean-Paul Moatti*, Bruno Ventelou*, Yann Videau*, Michel Kazatchkine**

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  1. “Time is costly”:Modelling the macro-economic impact of scaling up access to antiretroviral treatment for HIV/AIDS Jean-Paul Moatti*, Bruno Ventelou*, Yann Videau*, Michel Kazatchkine** *INSERM Research Unit 379, University of the Mediterranean, Marseille **Ministry of Foreign Affairs, French Ambassador for HIV/AIDS  

  2. Context Macroeconomic policy constraints = • Control inflation • Avoid large-scale public deficit • Limit long term dependence on external donor financing • Opportunity costs of AIDS programmes for other poverty reduction strategies  Limitations of available funding for reaching the goal of universal access to HIV care & treatment in 2010

  3. Economic Impact of the HIV epidemic in developing countries Three channels forimpacting the economy • Direct costs AIDS treatment (including opportunistic diseases)  reduction in savings  lower accumulation of capital. • Indirect costs (short term) AIDS  invalidity  reduction in labour participation. • Deferred indirect costs (long term) AIDS  Alteration of the long-term choices of the agents (households and firms)  lower investment in physical & ‘human capital’ (education, knowledge, know-how)

  4. Previous macro-economic estimations of reduction in GNP attributable to HIV/AIDS

  5. Methods • Model of growth with multiple factors of accumulation (“endogenous” growth model: including choices on long term resources, as human capital)… • …Using the following macroeconomic production function: with , population's epidemiological status and the constraint:

  6. Methods • Propriety of the model, two paths for the economy:

  7. « Scaling up access to HIV treatment? »

  8. “scaling up”? What we hypothesize: The policy response is represented through the following pathway: a reduction of the healthcare price index, which has the direct effect of increasing demand and consumption for healthcare…

  9. ‘‘Scaling up’’? …Then (indirect effects), the model takes into account the fact that more healthy people can : • participate to the production with a greater likelihood • work better, now and in the future, as their (good) health status facilitates effort as well as transmission of knowledge and savoir-faire to others, including their own children.

  10. “scaling up”? …How to read our results: If scaling up GDP if the AIDS-shock did not occur « Real » GDP (no scaling up)

  11. Results

  12. Results(i): success in five countries

  13. Results(i): success in five countries Scaling-up access to treatment would limit GDP losses due to AIDS from a 24.8% reduction in GDP loss in Central African Republic to a 85.2% in Angola, with Cameroon and Ivory Coast respectively presenting 32.9 and 32.1% reductions.

  14. Results (ii): failure in Zimbabwe Zimbabwe does not seem to strongly react to scaling up with only a limited 10.3% reduction in GDP loss. There is no range of the price policy which could redirect the country in the positive growth path (see the proprieties of an endogenous model of growth)

  15. Results (iii): GDP-gains minus Costs Table 2 shows that for four out of the six countries (Angola, Benin, Cameroon, Ivory Coast), the macroeconomic gains of scaling up would become potentially superior to its associated costs in 2010. At this date, these countries could de facto self-finance their program.

  16. Discussion

  17. Discussion/limitations • Our simulations of the impact of scaling up treatment do not take into account how the increased availability of treatment may modify the dynamics of HIV transmission in the long run. • Ambiguity: mathematical epidemiologic models indicate the decreased infectiveness of treated patients is likely to be counterbalanced by the increase in life expectancy of the patients that will predictably translate into an increased probability of sexual encounters between sero-different partners…

  18. Discussion/limitations • We introduced the policy of scaling up treatment by the way of a decrease in price of the health care commodities • In no way of course should it be considered as an evaluation of the impact of current programs. It is rather an attempt to simulate the potential economic gains that may be expected from scaling up to the extent that resources are used in an “ideally” efficient way (alongside the « healthcare demand function »)

  19. Discussion/conclusion • A massive investment in scaling-up access to HIV treatment may efficiently counter-act the detrimental long term impact of the HIV pandemic for growth in Sub-Saharan Africa. Potential macroeconomic benefits of scaling up may even compensate for its associated costs at the 2010 horizon • Our approach also focuses attention on the importance of timing in the policy response. Delays may have irreversible effects. The policy response may be efficient in restoring the dynamics of growth, if and only if its implementation is carried out at a rapid and massive scale.

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