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  3. Getting it right when budgets are tight: Using optimal expansion pathways to prioritize responses to concentrated and mixed HIV epidemics.
 

Getting it right when budgets are tight: Using optimal expansion pathways to prioritize responses to concentrated and mixed HIV epidemics.

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BORIS DOI
10.7892/boris.106894
Publisher DOI
10.1371/journal.pone.0185077
PubMed ID
28972975
Description
BACKGROUND

Prioritizing investments across health interventions is complicated by the nonlinear relationship between intervention coverage and epidemiological outcomes. It can be difficult for countries to know which interventions to prioritize for greatest epidemiological impact, particularly when budgets are uncertain.

METHODS

We examined four case studies of HIV epidemics in diverse settings, each with different characteristics. These case studies were based on public data available for Belarus, Peru, Togo, and Myanmar. The Optima HIV model and software package was used to estimate the optimal distribution of resources across interventions associated with a range of budget envelopes. We constructed "investment staircases", a useful tool for understanding investment priorities. These were used to estimate the best attainable cost-effectiveness of the response at each investment level.

FINDINGS

We find that when budgets are very limited, the optimal HIV response consists of a smaller number of 'core' interventions. As budgets increase, those core interventions should first be scaled up, and then new interventions introduced. We estimate that the cost-effectiveness of HIV programming decreases as investment levels increase, but that the overall cost-effectiveness remains below GDP per capita.

SIGNIFICANCE

It is important for HIV programming to respond effectively to the overall level of funding availability. The analytic tools presented here can help to guide program planners understand the most cost-effective HIV responses and plan for an uncertain future.
Date of Publication
2017-10-03
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services
500 Science > 510 Mathematics
Language(s)
en
Contributor(s)
Stuart, Robyn M
Kerr, Cliff C
Haghparast-Bidgoli, Hassan
Estill, Janne Anton Markus
Institut für Mathematische Statistik und Versicherungslehre (IMSV)
Institut für Sozial- und Präventivmedizin (ISPM)
Grobicki, Laura
Baranczuk, Zofia
Institut für Sozial- und Präventivmedizin (ISPM)
Prieto, Lorena
Montañez, Vilma
Reporter, Iyanoosh
Gray, Richard T
Skordis-Worrall, Jolene
Keiser, Oliviaorcid-logo
Institut für Sozial- und Präventivmedizin (ISPM)
Cheikh, Nejma
Boonto, Krittayawan
Osornprasop, Sutayut
Lavadenz, Fernando
Benedikt, Clemens J
Martin-Hughes, Rowan
Hussain, S Azfar
Kelly, Sherrie L
Kedziora, David J
Wilson, David P
Additional Credits
Institut für Sozial- und Präventivmedizin (ISPM)
Institut für Mathematische Statistik und Versicherungslehre (IMSV)
Series
PLoS ONE
Publisher
Public Library of Science
ISSN
1932-6203
Access(Rights)
open.access
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