Evidence map›Paper›PMID 38573760›Full record

ArticleJMIR public health and surveillance2024

Leveraging Routinely Collected Program Data to Inform Extrapolated Size Estimates for Key Populations in Namibia: Small Area Estimation Study.

Talia Loeb, Kalai Willis, Frans Velishavo, Daniel Lee, Amrita Rao, Stefan Baral, Katherine Rucinski

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Talia LoebData for Implementation (Data.FI), Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-3852-0661
Kalai WillisData for Implementation (Data.FI), Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-0157-0593
Frans VelishavoIntraHealth Namibia, Windhoek, Namibia.ORCID 0009-0009-9639-6698
Daniel LeeUnited States Agency for International Development Dominican Republic, Santo Domingo, Dominican Republic.ORCID 0009-0007-9882-3177
Amrita RaoData for Implementation (Data.FI), Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-9596-2418
Stefan BaralData for Implementation (Data.FI), Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-5482-2419
Katherine RucinskiData for Implementation (Data.FI), Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-9858-5953

Funding

Leveraging Big Data Science to Focus the HIV Response in Countries with Generalized HIV EpidemicsR01AI170249 · NIAID · JOHNS HOPKINS UNIVERSITY · PI BARAL, STEFAN DAVID · 2022 to 2025
$2.9M
Implementation Research to Optimize ART Delivery for Adolescents and Young Adults Living with HIVK01MH129226 · NIMH · JOHNS HOPKINS UNIVERSITY · PI Katherine B Rucinski · 2022 to 2026
$792k
NIAID NIH HHS R01 AI170249NIMH NIH HHS K01 MH129226
6 · The paper itself

Abstract

backgroundEstimating the size of key populations, including female sex workers (FSW) and men who have sex with men (MSM), can inform planning and resource allocation for HIV programs at local and national levels. In geographic areas where direct population size estimates (PSEs) for key populations have not been collected, small area estimation (SAE) can help fill in gaps using supplemental data sources known as auxiliary data. However, routinely collected program data have not historically been used as auxiliary data to generate subnational estimates for key populations, including in Namibia.

objectiveTo systematically generate regional size estimates for FSW and MSM in Namibia, we used a consensus-informed estimation approach with local stakeholders that included the integration of routinely collected HIV program data provided by key populations' HIV service providers.

methodsWe used quarterly program data reported by key population implementing partners, including counts of the number of individuals accessing HIV services over time, to weight existing PSEs collected through bio-behavioral surveys using a Bayesian triangulation approach. SAEs were generated through simple imputation, stratified imputation, and multivariable Poisson regression models. We selected final estimates using an iterative qualitative ranking process with local key population implementing partners.

resultsExtrapolated national estimates for FSW ranged from 4777 to 13,148 across Namibia, comprising 1.5% to 3.6% of female individuals aged between 15 and 49 years. For MSM, estimates ranged from 4611 to 10,171, comprising 0.7% to 1.5% of male individuals aged between 15 and 49 years. After the inclusion of program data as priors, the estimated proportion of FSW derived from simple imputation increased from 1.9% to 2.8%, and the proportion of MSM decreased from 1.5% to 0.75%. When stratified imputation was implemented using HIV prevalence to inform strata, the inclusion of program data increased the proportion of FSW from 2.6% to 4.0% in regions with high prevalence and decreased the proportion from 1.4% to 1.2% in regions with low prevalence. When population density was used to inform strata, the inclusion of program data also increased the proportion of FSW in high-density regions (from 1.1% to 3.4%) and decreased the proportion of MSM in all regions.

conclusionsUsing SAE approaches, we combined epidemiologic and program data to generate subnational size estimates for key populations in Namibia. Overall, estimates were highly sensitive to the inclusion of program data. Program data represent a supplemental source of information that can be used to align PSEs with real-world HIV programs, particularly in regions where population-based data collection methods are challenging to implement. Future work is needed to determine how best to include and validate program data in target settings and in key population size estimation studies, ultimately bridging research with practice to support a more comprehensive HIV response.

Indexed as

HIV InfectionsSexual and Gender MinoritiesSex WorkersAdolescentAdultBayes TheoremFemaleHomosexuality, MaleHumansMaleMiddle AgedNamibiaYoung Adultfemale sex workersHIVkey populationsmen who have sex with menNamibiapopulation size estimationsmall area estimation

Identifiers

PMID38573760
PMCPMC11027056

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LicenceCC BY
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Registered trials

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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.