Statistical models for incorporating data from routine HIV testing of pregnant women at antenatal clinics into HIV/AIDS epidemic estimates
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Published version
Author(s)
Type
Journal Article
Abstract
Objective: HIV prevalence data collected from routine HIV testing of pregnant women at antenatal clinics (ANC-RT) are potentially available from all facilities that offer testing services to pregnant women and can be used to improve estimates of national and subnational HIV prevalence trends. We develop methods to incorporate these new data source into the Joint United Nations Programme on AIDS Estimation and Projection Package in Spectrum 2017.
Methods: We develop a new statistical model for incorporating ANC-RT HIV prevalence data, aggregated either to the health facility level (site-level) or regionally (census-level), to estimate HIV prevalence alongside existing sources of HIV prevalence data from ANC unlinked anonymous testing (ANC-UAT) and household-based national population surveys. Synthetic data are generated to understand how the availability of ANC-RT data affects the accuracy of various parameter estimates.
Results: We estimate HIV prevalence and additional parameters using both ANC-RT and other existing data. Fitting HIV prevalence using synthetic data generally gives precise estimates of the underlying trend and other parameters. More years of ANC-RT data should improve prevalence estimates. More ANC-RT sites and continuation with existing ANC-UAT sites may improve the estimate of calibration between ANC-UAT and ANC-RT sites.
Conclusion: We have proposed methods to incorporate ANC-RT data into Spectrum to obtain more precise estimates of prevalence and other measures of the epidemic. Many assumptions about the accuracy, consistency, and representativeness of ANC-RT prevalence underlie the use of these data for monitoring HIV epidemic trends and should be tested as more data become available from national ANC-RT programs.
Methods: We develop a new statistical model for incorporating ANC-RT HIV prevalence data, aggregated either to the health facility level (site-level) or regionally (census-level), to estimate HIV prevalence alongside existing sources of HIV prevalence data from ANC unlinked anonymous testing (ANC-UAT) and household-based national population surveys. Synthetic data are generated to understand how the availability of ANC-RT data affects the accuracy of various parameter estimates.
Results: We estimate HIV prevalence and additional parameters using both ANC-RT and other existing data. Fitting HIV prevalence using synthetic data generally gives precise estimates of the underlying trend and other parameters. More years of ANC-RT data should improve prevalence estimates. More ANC-RT sites and continuation with existing ANC-UAT sites may improve the estimate of calibration between ANC-UAT and ANC-RT sites.
Conclusion: We have proposed methods to incorporate ANC-RT data into Spectrum to obtain more precise estimates of prevalence and other measures of the epidemic. Many assumptions about the accuracy, consistency, and representativeness of ANC-RT prevalence underlie the use of these data for monitoring HIV epidemic trends and should be tested as more data become available from national ANC-RT programs.
Date Issued
2017-04-01
Date Acceptance
2017-01-26
Citation
AIDS, 2017, 31 (Supplement 1), pp.S87-S94
ISSN
0269-9370
Publisher
LIPPINCOTT WILLIAMS & WILKINS
Start Page
S87
End Page
S94
Journal / Book Title
AIDS
Volume
31
Issue
Supplement 1
Copyright Statement
© 2017 The Author(s). Published by 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 http://creativecommons.org/licenses/by-nc-nd/4.0), 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.
terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND http://creativecommons.org/licenses/by-nc-nd/4.0), 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
UNAIDS
Bill & Melinda Gates Foundation
National Institutes of Health
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000398210100011&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
PO201153562
OPP1131208
1R03AI125001-01A1
Subjects
Science & Technology
Life Sciences & Biomedicine
Immunology
Infectious Diseases
Virology
antenatal clinic surveillance
HIV prevalence
statistical models
routine HIV testing among pregnant women
06 Biological Sciences
11 Medical And Health Sciences
17 Psychology And Cognitive Sciences
Publication Status
Published