Refusal bias in HIV prevalence estimates from nationally representative seroprevalence surveys

Abstract

Objectives: To assess the relationship between prior knowledge of one's HIV status and the likelihood to refuse HIV testing in populations-based surveys and explore its potential for producing bias in HIV prevalence estimates.

Methods: Using longitudinal survey data from Malawi, we estimate the relationship between prior knowledge of HIV-positive status and subsequent refusal of an HIV test. We use that parameter to develop a heuristic model of refusal bias that is applied to six Demographic and Health Surveys, in which refusal by HIV status is not observed. The model only adjusts for refusal bias conditional on a completed interview.

Results: Ecologically, HIV prevalence, prior testing rates and refusal for HIV testing are highly correlated. Malawian data further suggest that amongst individuals who know their status, HIV-positive individuals are 4.62 (95% confidence interval, 2.60-8.21) times more likely to refuse testing than HIV-negative ones. On the basis of that parameter and other inputs from the Demographic and Health Surveys, our model predicts downward bias in national HIV prevalence estimates ranging from 1.5% (95% confidence interval, 0.7-2.9) for Senegal to 13.3% (95% confidence interval, 7.2-19.6) for Malawi. In absolute terms, bias in HIV prevalence estimates is negligible for Senegal but 1.6 (95% confidence interval, 0.8-2.3) percentage points for Malawi. Downward bias is more severe in urban populations. Because refusal rates are higher in men, seroprevalence surveys also tend to overestimate the female-to-male ratio of infections.

Conclusion: Prior knowledge of HIV status informs decisions to participate in seroprevalence surveys. Informed refusals may produce bias in estimates of HIV prevalence and the sex ratio of infections.

Fig. 1. Prior testing and refusal rates in 14 African countries by HIV prevalence (size of the circles) and disaggregated by rural/ urban residence and sex (in %)

Countries included in the graph are Cameroon (2004), Ethiopia (2005), Ghana (2003), Guinea (2005), Kenya (2003), Lesotho (2004), Malawi (2004), Niger (2006), Rwanda (2005), Tanzania (2003–04), Senegal (2005), Uganda (2004–05), Zambia (2002) and Zimbabwe (2005–06). The prior testing rate is defined as the percentage of respondents who have ever been tested for HIV and received the results of the last test. In Zambia and Tanzania, it is the percentage tested before irrespective of the receipt of the test result. The refusal rate is defined as the percentage of respondents who refused the HIV test conditional on having completed the survey interview. The circles labeled with an R or U denote population subgroups in Rwanda and Uganda. They stand out with relatively low refusal rates for the level of prior testing. Reproduced from Demographic and Health Surveys and AIDS Indicator Surveys.

Fig. 2. Observed HIV prevalence, adjusted HIV prevalence and their ratio by country, sex and type of place of residence

The bars represent the observed and adjusted HIV prevalence under the medium scenario in which HIV-positive individuals who know their status are 4.62 times more likely to refuse than HIV-negative individuals who know their status. The grey dots represent the ratio of the adjusted over observed prevalence. The whiskers on the ratio correspond to values for the ratio estimated under the assumption that HIV-positive individuals are between 2.60 and 8.21 times more likely to refuse or to the 95% confidence interval around the estimate of the E parameter.