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National South African HIV prevalence estimates robust despite substantial test non-participation

机译:尽管没有大量参加测试,但南非全国艾滋病毒感染率估计仍很强劲

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Background. South African (SA) national HIV seroprevalence estimates are of crucial policy relevance in the country, and for the worldwide HIV response. However, the most recent nationally representative HIV test survey in 2012 had 22% test non-participation, leaving the potential for substantial bias in current seroprevalence estimates, even after controlling for selection on observed factors.Objective. To re-estimate national HIV prevalence in SA, controlling for bias due to selection on both observed and unobserved factors in the 2012 SA National HIV Prevalence, Incidence and Behaviour Survey.Methods. We jointly estimated regression models for consent to test and HIV status in a Heckman-type bivariate probit framework. As selection variable, we used assigned interviewer identity, a variable known to predict consent but highly unlikely to be associated with interviewees’ HIV status. From these models, we estimated the HIV status of interviewed participants who did not test.Results. Of 26 710 interviewed participants who were invited to test for HIV, 21.3% of females and 24.3% of males declined. Interviewer identity was strongly correlated with consent to test for HIV; declining a test was weakly associated with HIV serostatus. Our HIV prevalence estimates were not significantly different from those using standard methods to control for bias due to selection on observed factors: 15.1% (95% confidence interval (CI) 12.1 - 18.6) v. 14.5% (95% CI 12.8 - 16.3) for 15 - 49-year-old males; 23.3% (95% CI 21.7 - 25.8) v. 23.2% (95% CI 21.3 - 25.1) for 15 - 49-year-old females.Conclusion. The most recent SA HIV prevalence estimates are robust under the strongest available test for selection bias due to missing data. Our findings support the reliability of inferences drawn from such data.
机译:背景。南非(SA)全国HIV血清阳性率估计值对该国以及全球HIV应对措施至关重要。但是,2012年最新的全国代表性HIV检测调查中有22%的检测未参与,即使在控制了观察因素的选择后,目前的血清阳性率估计仍可能存在重大偏差。为了重新估计SA中的全国HIV患病率,在2012 SA SA全国HIV患病率,发病率和行为调查中控制因观察和未观察因素的选择而造成的偏见。在Heckman型双变量概率框架中,我们共同估算了测试同意和HIV状况的回归模型。作为选择变量,我们使用分配的访问者身份,该变量已知可以预测同意,但极不可能与访问者的HIV状况相关。从这些模型中,我们估计了未经测试的受访者的HIV状况。在26 710名被邀请接受艾滋病毒检测的受访者中,有21.3%的女性和24.3%的男性有所下降。采访者的身份与接受艾滋病毒检测的意愿密切相关;拒绝测试与HIV血清状况弱相关。我们的HIV患病率估算值与使用标准方法来控制偏见的估算值并无明显差异,原因是根据观察因素进行选择:15.1%(95%置信区间(CI)12.1-18.6)对14.5%(95%CI 12.8-16.3) 15至49岁的男性; 15至49岁女性的23.3%(95%CI 21.7-25.8)v。23.2%(95%CI 21.3-25.1)。结论。在因数据缺失而导致的选择偏倚的最强可用测试中,最新的SA HIV患病率估算是可靠的。我们的发现支持从此类数据得出的推论的可靠性。

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