Yiqing Xia1, Rachael M Milwid1, Arnaud Godin1, Marie-Claude Boily2, Leigh F Johnson3, Kimberly Marsh4, Jeffrey W Eaton2, Mathieu Maheu-Giroux1. 1. Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, McGill University, Montreal, Quebec, Canada. 2. MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom. 3. Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa. 4. Strategic Information Department, Joint UN Programme on HIV/AIDS (UNAIDS), Geneva, Switzerland.
Abstract
BACKGROUND: In many countries in sub-Saharan Africa, self-reported HIV testing history and awareness of HIV-positive status from household surveys are used to estimate the percentage of people living with HIV (PLHIV) who know their HIV status. Despite widespread use, there is limited empirical information on the sensitivity of those self-reports, which can be affected by nondisclosure. METHODS: Bayesian latent class models were used to estimate the sensitivity of self-reported HIV-testing history and awareness of HIV-positive status in four Population-based HIV Impact Assessment surveys in Eswatini, Malawi, Tanzania, and Zambia. Antiretroviral (ARV) metabolite biomarkers were used to identify persons on treatment who did not accurately report their status. For those without ARV biomarkers, we used a pooled estimate of nondisclosure among untreated persons that was 1.48 higher than those on treatment. RESULTS: Among PLHIV, the model-estimated sensitivity of self-reported HIV-testing history ranged from 96% to 99% across surveys. The model-estimated sensitivity of self-reported awareness of HIV status varied from 91% to 97%. Nondisclosure was generally higher among men and those aged 15-24 years. Adjustments for imperfect sensitivity did not substantially influence estimates of PLHIV ever tested (difference <4%) but the proportion of PLHIV aware of their HIV-positive status was higher than the unadjusted proportion (difference <8%). CONCLUSION: Self-reported HIV-testing histories in four Eastern and Southern African countries are generally robust although adjustment for nondisclosure increases estimated awareness of status. These findings can contribute to further refinements in methods for monitoring progress along the HIV testing and treatment cascade.
BACKGROUND: In many countries in sub-Saharan Africa, self-reported HIV testing history and awareness of HIV-positive status from household surveys are used to estimate the percentage of people living with HIV (PLHIV) who know their HIV status. Despite widespread use, there is limited empirical information on the sensitivity of those self-reports, which can be affected by nondisclosure. METHODS: Bayesian latent class models were used to estimate the sensitivity of self-reported HIV-testing history and awareness of HIV-positive status in four Population-based HIV Impact Assessment surveys in Eswatini, Malawi, Tanzania, and Zambia. Antiretroviral (ARV) metabolite biomarkers were used to identify persons on treatment who did not accurately report their status. For those without ARV biomarkers, we used a pooled estimate of nondisclosure among untreated persons that was 1.48 higher than those on treatment. RESULTS: Among PLHIV, the model-estimated sensitivity of self-reported HIV-testing history ranged from 96% to 99% across surveys. The model-estimated sensitivity of self-reported awareness of HIV status varied from 91% to 97%. Nondisclosure was generally higher among men and those aged 15-24 years. Adjustments for imperfect sensitivity did not substantially influence estimates of PLHIV ever tested (difference <4%) but the proportion of PLHIV aware of their HIV-positive status was higher than the unadjusted proportion (difference <8%). CONCLUSION: Self-reported HIV-testing histories in four Eastern and Southern African countries are generally robust although adjustment for nondisclosure increases estimated awareness of status. These findings can contribute to further refinements in methods for monitoring progress along the HIV testing and treatment cascade.
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