HIV-Prevalence Mapping Using Small Area Estimation in Kenya, Tanzania, and Mozambique at the First Sub-National Level

Background: Local estimates of HIV-prevalence provide information that can be used to target interventions and consequently increase the efficiency of resources. This enhanced allocation can lead to better health outcomes, including the control of the disease spread, and for more people. Methods: In...

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Autor principal:	Enrique M. Saldarriaga
Formato:	article
Lenguaje:	EN
Publicado:	Ubiquity Press 2021
Materias:	Infectious and parasitic diseases RC109-216 Public aspects of medicine RA1-1270
Acceso en línea:	https://doaj.org/article/fa9fa13cf25e468fbf30b522af970f5c
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spelling	oai:doaj.org-article:fa9fa13cf25e468fbf30b522af970f5c2021-12-02T18:56:39ZHIV-Prevalence Mapping Using Small Area Estimation in Kenya, Tanzania, and Mozambique at the First Sub-National Level2214-999610.5334/aogh.3345https://doaj.org/article/fa9fa13cf25e468fbf30b522af970f5c2021-09-01T00:00:00Zhttps://annalsofglobalhealth.org/articles/3345https://doaj.org/toc/2214-9996Background: Local estimates of HIV-prevalence provide information that can be used to target interventions and consequently increase the efficiency of resources. This enhanced allocation can lead to better health outcomes, including the control of the disease spread, and for more people. Methods: In this study, we used the DHS data phase V to estimate HIV prevalence at the first-subnational level in Kenya, Tanzania, and Mozambique. We fitted the data to a spatial random effect intrinsic conditional autoregressive (ICAR) model to smooth the outcome. Further, we used a sampling specification from a multistage cluster design. Results: We found that Nyanza ('Pi' = 13.6%) and Nairobi ('Pi' = 7.1%) in Kenya, Iringa ('Pi' = 15.4%) and Mbeya ('Pi' = 9.3%) in Tanzania, and Gaza ('Pi' = 15.2%) and Maputo City ('Pi' = 12.9%) in Mozambique are the regions with the highest prevalence of HIV, within country. Our results are based on publicly available data that through statistically rigorous methods, allowed us to obtain an accurate visual representation of the HIV prevalence at a regional level. Conclusions: These results can help in identification and targeting of high-prevalent regions to increase the supply of healthcare services to reduce the spread of the disease and increase the health quality of people living with HIV.Enrique M. SaldarriagaUbiquity PressarticleInfectious and parasitic diseasesRC109-216Public aspects of medicineRA1-1270ENAnnals of Global Health, Vol 87, Iss 1 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Infectious and parasitic diseases RC109-216 Public aspects of medicine RA1-1270
spellingShingle	Infectious and parasitic diseases RC109-216 Public aspects of medicine RA1-1270 Enrique M. Saldarriaga HIV-Prevalence Mapping Using Small Area Estimation in Kenya, Tanzania, and Mozambique at the First Sub-National Level
description	Background: Local estimates of HIV-prevalence provide information that can be used to target interventions and consequently increase the efficiency of resources. This enhanced allocation can lead to better health outcomes, including the control of the disease spread, and for more people. Methods: In this study, we used the DHS data phase V to estimate HIV prevalence at the first-subnational level in Kenya, Tanzania, and Mozambique. We fitted the data to a spatial random effect intrinsic conditional autoregressive (ICAR) model to smooth the outcome. Further, we used a sampling specification from a multistage cluster design. Results: We found that Nyanza ('Pi' = 13.6%) and Nairobi ('Pi' = 7.1%) in Kenya, Iringa ('Pi' = 15.4%) and Mbeya ('Pi' = 9.3%) in Tanzania, and Gaza ('Pi' = 15.2%) and Maputo City ('Pi' = 12.9%) in Mozambique are the regions with the highest prevalence of HIV, within country. Our results are based on publicly available data that through statistically rigorous methods, allowed us to obtain an accurate visual representation of the HIV prevalence at a regional level. Conclusions: These results can help in identification and targeting of high-prevalent regions to increase the supply of healthcare services to reduce the spread of the disease and increase the health quality of people living with HIV.
format	article
author	Enrique M. Saldarriaga
author_facet	Enrique M. Saldarriaga
author_sort	Enrique M. Saldarriaga
title	HIV-Prevalence Mapping Using Small Area Estimation in Kenya, Tanzania, and Mozambique at the First Sub-National Level
title_short	HIV-Prevalence Mapping Using Small Area Estimation in Kenya, Tanzania, and Mozambique at the First Sub-National Level
title_full	HIV-Prevalence Mapping Using Small Area Estimation in Kenya, Tanzania, and Mozambique at the First Sub-National Level
title_fullStr	HIV-Prevalence Mapping Using Small Area Estimation in Kenya, Tanzania, and Mozambique at the First Sub-National Level
title_full_unstemmed	HIV-Prevalence Mapping Using Small Area Estimation in Kenya, Tanzania, and Mozambique at the First Sub-National Level
title_sort	hiv-prevalence mapping using small area estimation in kenya, tanzania, and mozambique at the first sub-national level
publisher	Ubiquity Press
publishDate	2021
url	https://doaj.org/article/fa9fa13cf25e468fbf30b522af970f5c
work_keys_str_mv	AT enriquemsaldarriaga hivprevalencemappingusingsmallareaestimationinkenyatanzaniaandmozambiqueatthefirstsubnationallevel
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HIV-Prevalence Mapping Using Small Area Estimation in Kenya, Tanzania, and Mozambique at the First Sub-National Level

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