Imperial College London

Jeff Eaton

Faculty of MedicineSchool of Public Health

Senior Lecturer in HIV Epidemiology
 
 
 
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Contact

 

jeffrey.eaton

 
 
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Location

 

Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Maheu-Giroux:2019:10.1097/qad.0000000000002356,
author = {Maheu-Giroux, M and Jahn, A and Kalua, T and Mganga, A and Eaton, JW},
doi = {10.1097/qad.0000000000002356},
journal = {AIDS},
pages = {S295--S302},
title = {HIV surveillance based on routine testing data from antenatal clinics in Malawi (2011–2018): measuring and adjusting for bias from imperfect testing coverage},
url = {http://dx.doi.org/10.1097/qad.0000000000002356},
volume = {33},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - 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.
AU - Maheu-Giroux,M
AU - Jahn,A
AU - Kalua,T
AU - Mganga,A
AU - Eaton,JW
DO - 10.1097/qad.0000000000002356
EP - 302
PY - 2019///
SN - 0269-9370
SP - 295
TI - HIV surveillance based on routine testing data from antenatal clinics in Malawi (2011–2018): measuring and adjusting for bias from imperfect testing coverage
T2 - AIDS
UR - http://dx.doi.org/10.1097/qad.0000000000002356
UR - https://insights.ovid.com/crossref?an=00002030-900000000-96832
UR - http://hdl.handle.net/10044/1/75343
VL - 33
ER -