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Comparison of HIV Prevalence Among Antenatal Clinic Attendees Estimated from Routine Testing and Unlinked Anonymous Testing


In 2015, WHO and UNAIDS released new guidance recommending that countries transition from conducting antenatal clinic (ANC) unlinked anonymous testing (ANC-UAT) for tracking HIV prevalence trends among pregnant women to using ANC routine testing (ANC-RT) data, which are more consistent and economic to collect. This transition could pose challenges for distinguishing whether changes in observed prevalence are due to a change in underlying population prevalence or due to a change in the testing approach. We compared the HIV prevalence measured from ANC-UAT and ANC-RT in 15 countries that had both data sources in overlapping years. We used linear mixed-effects model (LMM) to estimate the RT-to-UAT calibration parameter as well as other unobserved quantities. We summarized the results at different levels of aggregation (e.g., country, urban, rural, and province). Based on our analysis, the HIV prevalence measured by ANC-UAT and ANC-RT data are consistent in most countries. Therefore, if large discrepancy is observed between ANC-UAT and ANC-RT at the same location, we recommend that people should be cautious and investigate the reason. For countries that lack information to estimate the calibration parameter, we propose an informative prior distribution of mean 0 and standard deviation 0.2 for the RT-to-UAT calibration parameter.

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This research was supported by the Joint United Nations Programme on HIV/AIDS (UNAIDS), NIH/NIAID 5-R01-AI136664, NIH 5-R03-AI125001, NSF IGERT-DGE-1144860. The authors are also grateful to Kimberly Marsh and Kaiyi Wu.

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Correspondence to Le Bao.

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Sheng, B., Eaton, J.W., Mahy, M. et al. Comparison of HIV Prevalence Among Antenatal Clinic Attendees Estimated from Routine Testing and Unlinked Anonymous Testing. Stat Biosci 12, 279–294 (2020).

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  • Antenatal clinic
  • HIV prevalence
  • Unlinked anonymous HIV testing
  • Routine HIV testing
  • Calibration parameter
  • Linear mixed-effects model