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Current HIV Research

Editor-in-Chief

ISSN (Print): 1570-162X
ISSN (Online): 1873-4251

What Impact Might the Economic Crisis have on HIV Epidemics in Southeast Asia?

Author(s): Richard T. Gray, Kelly-Jean Heymer, Alexander Hoare, Jisoo A. Kwon, Hla-Hla Thein, Namarola Lote, Peter Siba, Sarun Saramony, Vonthanak Saphonn, Heather Worth, John M. Kaldor and David P. Wilson

Volume 7, Issue 6, 2009

Page: [656 - 665] Pages: 10

DOI: 10.2174/157016209789973637

Price: $65

Abstract

Objective: To evaluate the potential impact of the current global economic crisis (GEC) on the spread of HIV. Design: To evaluate the impact of the economic downturn we studied two distinct HIV epidemics in Southeast Asia: the generalized epidemic in Cambodia where incidence is declining and the epidemic in Papua New Guinea (PNG) which is in an expansion phase. Methods: Major HIV-related risk factors that may change due to the GEC were identified and a dynamic mathematical transmission model was developed and used to forecast HIV prevalence, diagnoses, and incidence in Cambodia and PNG over the next 3 years. Results: In Cambodia, the total numbers of HIV diagnoses are not expected to be largely affected. However, an estimated increase of up to 10% in incident cases of HIV, due to potential changes in behavior, may not be observed by the surveillance system. In PNG, HIV incidence and diagnoses could be more affected by the GEC, resulting in respective increases of up to 17% and 11% over the next 3 years. Decreases in VCT and education programs are the factors that may be of greatest concern in both settings. A reduction in the rollout of antiretroviral therapy could increase the number of AIDS-related deaths (by up to 7.5% after 3 years). Conclusions: The GEC is likely to have a modest impact on HIV epidemics. However, there are plausible conditions under which the economic downturns can noticeably influence epidemic trends. This study highlights the high importance of maintaining funding for HIV programs.

Keywords: Global economic crisis, Southeast Asia, HIV epidemics, Cambodia, Papua New Guinea, HIV funding, mathematical modelling

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