Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

The Demographic, Social, and Economic Correlates of HIV Infection Status in Sub-Saharan Africa

Version 1 : Received: 19 December 2020 / Approved: 21 December 2020 / Online: 21 December 2020 (11:14:08 CET)

How to cite: Bendavid, E.; Claypool, K.; Chow, E.; Chung, J.; Mai, D.; Patel, C. The Demographic, Social, and Economic Correlates of HIV Infection Status in Sub-Saharan Africa. Preprints 2020, 2020120507 (doi: 10.20944/preprints202012.0507.v1). Bendavid, E.; Claypool, K.; Chow, E.; Chung, J.; Mai, D.; Patel, C. The Demographic, Social, and Economic Correlates of HIV Infection Status in Sub-Saharan Africa. Preprints 2020, 2020120507 (doi: 10.20944/preprints202012.0507.v1).

Abstract

Background. Predisposition to HIV+ is influenced by a wide range of correlated economic, environmental, demographic, social, and behavioral factors. While evidence among a candidate handful have strong evidence, there is lack of a consensus among the vast array of variables measured in large surveys. Methods. We performed a comprehensive data-driven search for correlates of HIV positivity in >600,000 participants of the Demographic and Health Survey (DHS) across 29 sub-Saharan African countries from 2003 to 2017. We associated a total of 7,251 and of 6,288 unique variables with HIV+ in females and males respectively in each of the 50 surveys. We performed a meta-analysis within countries to attain 29 country-specific associations. Results. We identified 344 (5.4% out possible) and 373 (5.1%) associations with HIV+ in males and females, respectively, with robust statistical support. The identified associations are consistent in directionality across countries and sexes. The association sizes among individual correlates and their predictive capability was low to modest, but comparable to established factors. Among the identified associations, variables identifying being head of household among females was identified in 17 countries with a mean odds ratio (OR) of 2.5 (OR range: 1.1-3.5, R2 = 0.01). Other common associations were identified with marital status, education, age, and ownership of land or livestock. Conclusions. Our continent-wide search for variables has identified under-recognized variables associated with HIV+ that are consistent across the continent and sex. Many of the association sizes are as high as established risk factors for HIV+, including male circumcision.

Subject Areas

HIV; big data; Africa; epidemiology

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