HIV surveillance based on routine testing data from antenatal clinics in Malawi (2011–2018): measuring and adjusting for bias from imperfect testing coverage
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Author(s)
Maheu-Giroux, Mathieu
Jahn, Andreas
Kalua, Thokozani
Mganga, Andrew
Eaton, Jeffrey W
Type
Journal Article
Abstract
Objective:
The use of routinely collected data from prevention of mother-to-child transmission programs (ANC-RT) has been proposed to monitor HIV epidemic trends. This poses several challenges for surveillance, one of them being that women may opt-out of testing and/or test stock-outs may result in inconsistent service availability. In this study, we sought to empirically quantify the relationship between imperfect HIV testing coverage and HIV prevalence among pregnant women from ANC-RT data.
Design:
We used reports from the ANC Register of all antenatal care (ANC) sites in Malawi (2011–2018), including 49 244 monthly observations, from 764 facilities, totaling 4 375 777 women.
Methods:
Binomial logistic regression models with facility-level fixed effects and marginal standardization were used to assess the effect of testing coverage on HIV prevalence.
Results:
Testing coverage increased from 78 to 98% over 2011–2018. We estimated that, had testing coverage been perfect, prevalence would have been 0.4% point lower (95% CI 0.3–0.5%) than the 7.9% observed prevalence, a relative overestimation of 6%. Bias in HIV prevalence was the highest in 2012, when testing coverage was lowest (72%), resulting in a relative overestimation of HIV prevalence of 15% (95% CI 12–17%). Overall, adjustments for imperfect testing coverage led to a subtler decline in HIV prevalence over 2011--2018.
Conclusion:
Malawi achieved high coverage of routine HIV testing in recent years. Nevertheless, imperfect testing coverage can lead to overestimation of HIV prevalence among pregnant women when coverage is suboptimal. ANC-RT data should be carefully evaluated for changes in testing coverage and completeness when used to monitor epidemic trends.
The use of routinely collected data from prevention of mother-to-child transmission programs (ANC-RT) has been proposed to monitor HIV epidemic trends. This poses several challenges for surveillance, one of them being that women may opt-out of testing and/or test stock-outs may result in inconsistent service availability. In this study, we sought to empirically quantify the relationship between imperfect HIV testing coverage and HIV prevalence among pregnant women from ANC-RT data.
Design:
We used reports from the ANC Register of all antenatal care (ANC) sites in Malawi (2011–2018), including 49 244 monthly observations, from 764 facilities, totaling 4 375 777 women.
Methods:
Binomial logistic regression models with facility-level fixed effects and marginal standardization were used to assess the effect of testing coverage on HIV prevalence.
Results:
Testing coverage increased from 78 to 98% over 2011–2018. We estimated that, had testing coverage been perfect, prevalence would have been 0.4% point lower (95% CI 0.3–0.5%) than the 7.9% observed prevalence, a relative overestimation of 6%. Bias in HIV prevalence was the highest in 2012, when testing coverage was lowest (72%), resulting in a relative overestimation of HIV prevalence of 15% (95% CI 12–17%). Overall, adjustments for imperfect testing coverage led to a subtler decline in HIV prevalence over 2011--2018.
Conclusion:
Malawi achieved high coverage of routine HIV testing in recent years. Nevertheless, imperfect testing coverage can lead to overestimation of HIV prevalence among pregnant women when coverage is suboptimal. ANC-RT data should be carefully evaluated for changes in testing coverage and completeness when used to monitor epidemic trends.
Date Issued
2019-12-15
Date Acceptance
2019-09-01
Citation
AIDS, 2019, 33, pp.S295-S302
ISSN
0269-9370
Publisher
Ovid Technologies (Wolters Kluwer Health)
Start Page
S295
End Page
S302
Journal / Book Title
AIDS
Volume
33
Copyright Statement
© 2019 Wolters Kluwer Health, Inc. This is an open access article distributed under the terms of the Creative Commons Attribution-Non
Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the
work provided it is properly cited. The work cannot be changed in any way or used commercially without
permission from the journal.
Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the
work provided it is properly cited. The work cannot be changed in any way or used commercially without
permission from the journal.
Sponsor
Medical Research Council (MRC)
National Institutes of Health
UNAIDS
Medical Research Council (MRC)
Identifier
https://insights.ovid.com/crossref?an=00002030-900000000-96832
Grant Number
MR/K010174/1B
1R03AI125001-01A1
2017/778519
MR/R015600/1
Subjects
Virology
06 Biological Sciences
11 Medical and Health Sciences
17 Psychology and Cognitive Sciences
Publication Status
Published
Date Publish Online
2019-09-06