OBJECTIVE: To quantify refusal bias due to prior HIV testing, and its effect on HIV prevalence estimates, in general-population surveys. DESIGN: Four annual, cross-sectional, house-to-house HIV serosurveys conducted during 2006-2010 within a demographic surveillance population of 33 000 in northern Malawi. METHODS: The effect of prior knowledge of HIV status on test acceptance in subsequent surveys was analysed. HIV prevalence was then estimated using ten adjustment methods, including age-standardization; multiple imputation of missing data; a conditional probability equations approach incorporating refusal bias; using longitudinal data on previous and subsequent HIV results; including self-reported HIV status; and including linked antiretroviral therapy clinic data. RESULTS: HIV test acceptance was 55-65% in each serosurvey. By 2009/2010 79% of men and 85% of women had tested at least once. Known HIV-positive individuals were more likely to be absent, and refuse interviewing and testing. Using longitudinal data, and adjusting for refusal bias, the best estimate of HIV prevalence was 7% in men and 9% in women in 2008/2009. Estimates using multiple imputations were 4.8 and 6.4%, respectively. Using the conditional probability approach gave good estimates using the refusal risk ratio of HIV-positive to HIV-negative individuals observed in this study, but not when using the only previously published estimate of this ratio, even though this was also from Malawi. CONCLUSION: As the proportion of the population who know their HIV-status increases, survey-based prevalence estimates become increasingly biased. As an adjustment method for cross-sectional data remains elusive, sources of data with high coverage, such as antenatal clinics surveillance, remain important.
OBJECTIVE: To quantify refusal bias due to prior HIV testing, and its effect on HIV prevalence estimates, in general-population surveys. DESIGN: Four annual, cross-sectional, house-to-house HIV serosurveys conducted during 2006-2010 within a demographic surveillance population of 33 000 in northern Malawi. METHODS: The effect of prior knowledge of HIV status on test acceptance in subsequent surveys was analysed. HIV prevalence was then estimated using ten adjustment methods, including age-standardization; multiple imputation of missing data; a conditional probability equations approach incorporating refusal bias; using longitudinal data on previous and subsequent HIV results; including self-reported HIV status; and including linked antiretroviral therapy clinic data. RESULTS: HIV test acceptance was 55-65% in each serosurvey. By 2009/2010 79% of men and 85% of women had tested at least once. Known HIV-positive individuals were more likely to be absent, and refuse interviewing and testing. Using longitudinal data, and adjusting for refusal bias, the best estimate of HIV prevalence was 7% in men and 9% in women in 2008/2009. Estimates using multiple imputations were 4.8 and 6.4%, respectively. Using the conditional probability approach gave good estimates using the refusal risk ratio of HIV-positive to HIV-negative individuals observed in this study, but not when using the only previously published estimate of this ratio, even though this was also from Malawi. CONCLUSION: As the proportion of the population who know their HIV-status increases, survey-based prevalence estimates become increasingly biased. As an adjustment method for cross-sectional data remains elusive, sources of data with high coverage, such as antenatal clinics surveillance, remain important.
Authors: Sheri A Lippman; Starley B Shade; Alison M El Ayadi; Jennifer M Gilvydis; Jessica S Grignon; Teri Liegler; Jessica Morris; Evasen Naidoo; Lisa M Prach; Adrian Puren; Scott Barnhart Journal: J Acquir Immune Defic Syndr Date: 2016-09-01 Impact factor: 3.731
Authors: Wanjiru Waruiru; Andrea A Kim; Davies O Kimanga; James Ng'ang'a; Sandra Schwarcz; Lucy Kimondo; Anne Ng'ang'a; Mamo Umuro; Mary Mwangi; James K Ojwang'; William K Maina Journal: J Acquir Immune Defic Syndr Date: 2014-05-01 Impact factor: 3.731
Authors: Olivier Koole; Rein Mgj Houben; Themba Mzembe; Thomas P Van Boeckel; Michael Kayange; Andreas Jahn; Frank Chimbwandira; Judith R Glynn; Amelia C Crampin Journal: J Acquir Immune Defic Syndr Date: 2014-09-01 Impact factor: 3.731