Evidence map›Paper›PMID 28296805›Full record

ArticleAIDS (London, England)2017

Does nonlocal women's attendance at antenatal clinics distort HIV prevalence surveillance estimates in pregnant women in Zimbabwe?

Katherine C Wilson, Mutsa Mhangara, Janet Dzangare, Jeffrey W Eaton, Timothy B Hallett, Owen Mugurungi, Simon Gregson

Abstract read
In one paragraph

Article in AIDS (London, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Katherine C WilsonaDepartment of Infectious Disease Epidemiology, Imperial College London School of Public Health, London, W2 1PG, UK bAIDS and TB Department, Zimbabwe Ministry of Health and Child Care cBiomedical Research and Training Institute, Harare, Zimbabwe.
Mutsa Mhangara
Janet Dzangare
Jeffrey W Eaton
Timothy B Hallett
Owen Mugurungi
Simon Gregson

Funding

Quantifying Spatial Representativeness and Uncertainty in Antenatal Care Sentinel Surveillance for HIV in Sub-Saharan Africa.R03AI125001 · NIAID · IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE · PI EATON, JEFFREY WILLIAM · 2017 to 2018
$105k
NIAID NIH HHS R03 AI125001Wellcome Trust
6 · The paper itself

Abstract

objectiveThe objective was to assess whether HIV prevalence measured among women attending antenatal clinics (ANCs) are representative of prevalence in the local area, or whether estimates may be biased by some women's choice to attend ANCs away from their residential location. We tested the hypothesis that HIV prevalence in towns and periurban areas is underestimated in ANC sentinel surveillance data in Zimbabwe.

methodsNational unlinked anonymous HIV surveillance was conducted at 19 ANCs in Zimbabwe in 2000, 2001, 2002, 2004, 2006, 2009, and 2012. This data was used to compare HIV prevalence and nonlocal attendance levels at ANCs at city, town, periurban, and rural clinics in aggregate and also for individual ANCs.

resultsIn 2000, HIV prevalence at town ANCs (36.6%, 95% CI 34.4-38.9%) slightly underestimated prevalence among urban women attending these clinics (40.7%, 95% CI 37.6-43.9%). However, there was no distortion in HIV prevalence at either the aggregate clinic location or at individual clinics in more recent surveillance rounds. HIV prevalence was consistently higher in towns and periurban areas than in rural areas. Nonlocal attendance was high at town (26-39%) and periurban (53-95%) ANCs but low at city clinics (<10%). However, rural women attending ANCs in towns and periurban areas had higher HIV prevalence than rural women attending rural clinics, and were younger, more likely to be single, and less likely to be housewives.

conclusionsIn Zimbabwe, HIV prevalence among ANC attendees provides reliable estimates of HIV prevalence in pregnant women in the local area.

Indexed as

Epidemiological MonitoringAdolescentAdultFemaleHIV InfectionsHumansMiddle AgedPregnancyPregnancy Complications, InfectiousPrenatal CarePrevalenceYoung AdultZimbabwe

Identifiers

PMID28296805
PMCPMC5677598

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.