Excess mortality associated with HIV

Survey estimates from the PHIA project

Bibliographic Data

ID2637876
AuthorsShannon Farley, Shannon M Farley (0000-0003-0321-5974, ICAP Global Health, corresponding author), Giles Reid (0000-0002-1699-4324, ICAP Global Health), Kay Yuengling (ICAP Global Health), Connor Wright (0000-0002-5346-420X, ICAP Global Health), Vesper Hichilombwe Chisumpa (0000-0003-1234-3644, University of Zambia), George Bello (0000-0003-1257-619X, Ministry of Health), James M Juma, James Juma, Abigail R Greenleaf (0000-0002-8261-7025, ICAP Global Health), Stephen Mccracken (0000-0002-9180-0366, Centers for Disease Control and Prevention), Paul Stupp (Centers for Disease Control and Prevention), Helleringer (0000-0002-5921-9651, New York University Abu Dhabi), Stephane Helleringer, Jessica Justman (0000-0003-4704-3115, ICAP Global Health)
Year2024
Volume51
Issue2
Pages1183-1200
Publication date2024-11-15
Open AccessYes
TypeARTICLE
VenueDemographic Research (JOURNAL)
Journal identifiersISSN: 1435-9871 • E-ISSN: 2363-7064
PublisherMax Planck Institute for Demographic Research (PUBLISHER • DE)
DOI10.4054/demres.2024.51.38
PMID40390835
OpenAlexW4404353842
LanguageEN
References cited22

BACKGROUND: Incomplete vital statistics systems in resource-limited countries hinder accurate HIV epidemic assessments. Population-based survey data combined with HIV infection biomarkers may partially address this gap, providing excess mortality estimates in households where people living with HIV (PLWH) reside. OBJECTIVE: Examine household-level excess HIV mortality in households with PLWH using population-based survey data, including mortality reported by heads of households, and HIV biomarkers. METHODS: We compared mortality between households with and without PLWH using publicly available data from 11 Population-based HIV Impact Assessments conducted between 2015 and 2019 in Cameroon, Côte d'Ivoire, Eswatini, Kenya, Malawi, Namibia, Rwanda, Tanzania, Uganda, Zambia, and Zimbabwe. Eligible, consenting household members provided blood for HIV testing. Household-level regression models estimated deaths per 1,000 person-years (PY) for the three-year period before the survey; death rate ratios were calculated. Quasi-Poisson distribution accounted for household death over-dispersion. RESULTS: Country-specific deaths rates per 1,000 PY were significantly higher among rural versus urban households for five countries. For example, in Cameroon, the rates were 9.3 (95% confidence interval [CI]: 8.7-9.9) versus 6.5 (95% CI: 5.9-7.1). In six countries, death rates were significantly higher (1.3-1.7-fold) among households with PLWH versus those without. Death rate ratios were significantly higher among rural (1.4-1.8-fold) and urban households (1.6-2.3-fold) with PLWH versus those without in four and three countries, respectively. CONCLUSIONS: General population household survey findings in multiple countries in Africa indicate that households where PLWH resided experienced excess mortality relative to other households. CONTRIBUTION: The novel approach we use to describe HIV-related household-level mortality offers an additional method to measure progress toward zero AIDS-related deaths

Excess mortality · Geography · Mortality rate · Sociology · Demography · HIV Research and Treatment · HIV/AIDS Impact and Responses · HIV/AIDS Research and Interventions · Medicine · Virology

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