HIV Incidence in Sub-Saharan Africa: A Review of Available Data with Implications for Surveillance and Prevention Planning

HIV Incidence in Sub-Saharan Africa: A Review of Available Data with Implications for Surveillance and Prevention Planning

Sarah L. Braunstein 1, Janneke H.H.M. van de Wijgert 1, Denis Nash 1

1 NULL

*Correspondence: Denis Nash, Email not available

Abstract

Background: HIV incidence estimation is increasingly being incorporated into HIV/AIDS surveillanceactivities in both resource-rich and developing countries. We conducted a systematic review to assessthe availability of HIV incidence data from sub-Saharan Africa.
Methods: We examined peer-reviewed articles, conference proceedings and technical reports publishedfrom 1987-2008. Incidence estimates were classified by country, year, population group, and estimationmethod (prospective study or the serologic testing algorithm for recent HIV seroconversion; STARHS.
Results: Our search yielded HIV incidence estimates for 15 of 44 sub-Saharan African countries, with57 studies generating 264 unique estimates. Of these, 239 (91%) were obtained via prospective studies,and 25 (9%) via the STARHS method (24 using the BED-CEIA assay). Only five countries reportedpopulation-based estimates, and less than two-thirds of studies reported risk factor information.STARHS use increased over time, comprising 20% of estimates since 2006. However, studies thatcompared STARHS estimates with prospectively observed or modeled estimates often found substantiallevels of disagreement, with STARHS often overestimating HIV incidence.
Conclusions: Population-based HIV incidence estimates and risk factor information in sub-SaharanAfrica remain scant but increasingly available. Regional STARHS data suggest a need for further validationprior to widespread use and incorporation into routine surveillance activities. In the meantime, prevalenceand behavioral risk factor data remain important for HIV prevention planning.

Keywords: Africa. HIV incidence. Surveillance. Prevention. Risk factors. Serologic testing algorithm for recent HIVseroconversion (STARHS). BED-CEIA. Avidity index. Seroincidence.

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