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Public Library of Science, PLoS ONE, 9(16), p. e0257496, 2021

DOI: 10.1371/journal.pone.0257496

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It ain’t what you do, it’s the way that you do it: The pitfalls of using routine data to measure early infant HIV diagnosis in HIV-exposed infants

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Background Early infant HIV diagnosis (EID) is critical to ensuring timely diagnosis of HIV-exposed infants, and treatment in those found to be infected. However estimates of coverage vary considerably, depending on data sources used. We used 4 methods to estimate coverage among a historical cohort of HIV-exposed infants in rural South Africa, between 2010–2016. Methods We estimated the proportion of infants ever tested (methods 1–3) and tested by 7 weeks of age (1–4) as follows: (1) infants born to women identified as HIV-positive in demographic surveillance were linked to those with ≥1 EID result in routine laboratory surveillance; (2) the number of infants with ≥1 EID result in laboratory surveillance divided by the estimated number of HIV-exposed infants, calculated as total live births multiplied by antenatal HIV seroprevalence; (3) the number of infants with ≥1 EID result in routine laboratory surveillance, divided by the number of HIV-exposed infants as estimated by the district health service; (4) from documentation in infants’ Road-to-Health-booklets. Results The proportion ever tested was 43%, 88% and 138% for methods 1–3, and by 7 weeks of age was 25%, 49%, 86% and 46% for methods 1–4 respectively. Conclusions The four methods, applied to a range of routine data sources, resulted in estimates varying considerably, and the true coverage of EID remains unclear. Our findings highlight the importance of developing unique patient identifiers, improving training of healthcare providers using reporting systems, and ensuring the accuracy of healthcare records, to ensure the best possible health outcomes for HIV-exposed infants.