Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.

<h4>Background</h4>Model-based small area estimation methods can help generate parameter estimates at the district level, where planned population survey sample sizes are not large enough to support direct estimates of HIV prevalence with adequate precision. We computed district-level HI...

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Autores principales:	Joseph Ouma, Caroline Jeffery, Colletar Anna Awor, Allan Muruta, Joshua Musinguzi, Rhoda K Wanyenze, Sam Biraro, Jonathan Levin, Joseph J Valadez
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/cc6f94ab738d4ed3921aee742feda9ad
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spelling	oai:doaj.org-article:cc6f94ab738d4ed3921aee742feda9ad2021-12-02T20:18:35ZModel-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.1932-620310.1371/journal.pone.0253375https://doaj.org/article/cc6f94ab738d4ed3921aee742feda9ad2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0253375https://doaj.org/toc/1932-6203<h4>Background</h4>Model-based small area estimation methods can help generate parameter estimates at the district level, where planned population survey sample sizes are not large enough to support direct estimates of HIV prevalence with adequate precision. We computed district-level HIV prevalence estimates and their 95% confidence intervals for districts in Uganda.<h4>Methods</h4>Our analysis used direct survey and model-based estimation methods, including Fay-Herriot (area-level) and Battese-Harter-Fuller (unit-level) small area models. We used regression analysis to assess for consistency in estimating HIV prevalence. We use a ratio analysis of the mean square error and the coefficient of variation of the estimates to evaluate precision. The models were applied to Uganda Population-Based HIV Impact Assessment 2016/2017 data with auxiliary information from the 2016 Lot Quality Assurance Sampling survey and antenatal care data from district health information system datasets for unit-level and area-level models, respectively.<h4>Results</h4>Estimates from the model-based and the direct survey methods were similar. However, direct survey estimates were unstable compared with the model-based estimates. Area-level model estimates were more stable than unit-level model estimates. The correlation between unit-level and direct survey estimates was (β1 = 0.66, r2 = 0.862), and correlation between area-level model and direct survey estimates was (β1 = 0.44, r2 = 0.698). The error associated with the estimates decreased by 37.5% and 33.1% for the unit-level and area-level models, respectively, compared to the direct survey estimates.<h4>Conclusions</h4>Although the unit-level model estimates were less precise than the area-level model estimates, they were highly correlated with the direct survey estimates and had less standard error associated with estimates than the area-level model. Unit-level models provide more accurate and reliable data to support local decision-making when unit-level auxiliary information is available.Joseph OumaCaroline JefferyColletar Anna AworAllan MurutaJoshua MusinguziRhoda K WanyenzeSam BiraroJonathan LevinJoseph J ValadezPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0253375 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Joseph Ouma Caroline Jeffery Colletar Anna Awor Allan Muruta Joshua Musinguzi Rhoda K Wanyenze Sam Biraro Jonathan Levin Joseph J Valadez Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.
description	<h4>Background</h4>Model-based small area estimation methods can help generate parameter estimates at the district level, where planned population survey sample sizes are not large enough to support direct estimates of HIV prevalence with adequate precision. We computed district-level HIV prevalence estimates and their 95% confidence intervals for districts in Uganda.<h4>Methods</h4>Our analysis used direct survey and model-based estimation methods, including Fay-Herriot (area-level) and Battese-Harter-Fuller (unit-level) small area models. We used regression analysis to assess for consistency in estimating HIV prevalence. We use a ratio analysis of the mean square error and the coefficient of variation of the estimates to evaluate precision. The models were applied to Uganda Population-Based HIV Impact Assessment 2016/2017 data with auxiliary information from the 2016 Lot Quality Assurance Sampling survey and antenatal care data from district health information system datasets for unit-level and area-level models, respectively.<h4>Results</h4>Estimates from the model-based and the direct survey methods were similar. However, direct survey estimates were unstable compared with the model-based estimates. Area-level model estimates were more stable than unit-level model estimates. The correlation between unit-level and direct survey estimates was (β1 = 0.66, r2 = 0.862), and correlation between area-level model and direct survey estimates was (β1 = 0.44, r2 = 0.698). The error associated with the estimates decreased by 37.5% and 33.1% for the unit-level and area-level models, respectively, compared to the direct survey estimates.<h4>Conclusions</h4>Although the unit-level model estimates were less precise than the area-level model estimates, they were highly correlated with the direct survey estimates and had less standard error associated with estimates than the area-level model. Unit-level models provide more accurate and reliable data to support local decision-making when unit-level auxiliary information is available.
format	article
author	Joseph Ouma Caroline Jeffery Colletar Anna Awor Allan Muruta Joshua Musinguzi Rhoda K Wanyenze Sam Biraro Jonathan Levin Joseph J Valadez
author_facet	Joseph Ouma Caroline Jeffery Colletar Anna Awor Allan Muruta Joshua Musinguzi Rhoda K Wanyenze Sam Biraro Jonathan Levin Joseph J Valadez
author_sort	Joseph Ouma
title	Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.
title_short	Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.
title_full	Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.
title_fullStr	Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.
title_full_unstemmed	Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.
title_sort	model-based small area estimation methods and precise district-level hiv prevalence estimates in uganda.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/cc6f94ab738d4ed3921aee742feda9ad
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_version_	1718374313282764800

Model-based small area estimation methods and precise district-level HIV prevalence estimates in Uganda.

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