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Data triangulation to estimate age-specific coverage of voluntary medical male circumcision for HIV prevention in four Kenyan counties

BACKGROUND: Kenya is 1 of 14 priority countries in Africa scaling up voluntary medical male circumcision (VMMC) for HIV prevention following the recommendations of the World Health Organization and the Joint United Nations Programme on HIV/AIDS. To inform VMMC target setting, we modeled the impact o...

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Autores principales: Kripke, Katharine, Opuni, Marjorie, Odoyo-June, Elijah, Onyango, Mathews, Young, Peter, Serrem, Kennedy, Ojiambo, Vincent, Schnure, Melissa, Stegman, Peter, Njeuhmeli, Emmanuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298728/
https://www.ncbi.nlm.nih.gov/pubmed/30562394
http://dx.doi.org/10.1371/journal.pone.0209385
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author Kripke, Katharine
Opuni, Marjorie
Odoyo-June, Elijah
Onyango, Mathews
Young, Peter
Serrem, Kennedy
Ojiambo, Vincent
Schnure, Melissa
Stegman, Peter
Njeuhmeli, Emmanuel
author_facet Kripke, Katharine
Opuni, Marjorie
Odoyo-June, Elijah
Onyango, Mathews
Young, Peter
Serrem, Kennedy
Ojiambo, Vincent
Schnure, Melissa
Stegman, Peter
Njeuhmeli, Emmanuel
author_sort Kripke, Katharine
collection PubMed
description BACKGROUND: Kenya is 1 of 14 priority countries in Africa scaling up voluntary medical male circumcision (VMMC) for HIV prevention following the recommendations of the World Health Organization and the Joint United Nations Programme on HIV/AIDS. To inform VMMC target setting, we modeled the impact of circumcising specific client age groups across several Kenyan geographic areas. METHODS: The Decision Makers’ Program Planning Tool, Version 2 (DMPPT 2) was applied in Kisumu, Siaya, Homa Bay, and Migori counties. Initial modeling done in mid-2016 showed coverage estimates above 100% in age groups and geographic areas where demand for VMMC continued to be high. On the basis of information obtained from country policy makers and VMMC program implementers, we adjusted circumcision coverage for duplicate reporting, county-level population estimates, migration across county boundaries for VMMC services, and replacement of traditional circumcision with circumcisions in the VMMC program. To address residual inflated coverage following these adjustments we applied county-specific correction factors computed by triangulating model results with coverage estimates from population surveys. RESULTS: A program record review identified duplicate reporting in Homa Bay, Kisumu, and Siaya. Using county population estimates from the Kenya National Bureau of Statistics, we found that adjusting for migration and correcting for replacement of traditional circumcision with VMMC led to lower estimates of 2016 male circumcision coverage especially for Kisumu, Migori, and Siaya. Even after addressing these issues, overestimation of 2016 male circumcision coverage persisted, especially in Homa Bay. We estimated male circumcision coverage in 2016 by applying correction factors. Modeled estimates for 2016 circumcision coverage for the 10- to 14-year age group ranged from 50% in Homa Bay to approximately 90% in Kisumu. Results for the 15- to 19-year age group suggest almost complete coverage in Kisumu, Migori, and Siaya. Coverage for the 20- to 24-year age group ranged from about 80% in Siaya to about 90% in Homa Bay, coverage for those aged 25–29 years ranged from about 60% in Siaya to 80% in Migori, and coverage in those aged 30–34 years ranged from about 50% in Siaya to about 70% in Migori. CONCLUSIONS: Our analysis points to solutions for some of the data issues encountered in Kenya. Kenya is the first country in which these data issues have been encountered because baseline circumcision rates were high. We anticipate that some of the modeling methods we developed for Kenya will be applicable in other countries.
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spelling pubmed-62987282018-12-28 Data triangulation to estimate age-specific coverage of voluntary medical male circumcision for HIV prevention in four Kenyan counties Kripke, Katharine Opuni, Marjorie Odoyo-June, Elijah Onyango, Mathews Young, Peter Serrem, Kennedy Ojiambo, Vincent Schnure, Melissa Stegman, Peter Njeuhmeli, Emmanuel PLoS One Research Article BACKGROUND: Kenya is 1 of 14 priority countries in Africa scaling up voluntary medical male circumcision (VMMC) for HIV prevention following the recommendations of the World Health Organization and the Joint United Nations Programme on HIV/AIDS. To inform VMMC target setting, we modeled the impact of circumcising specific client age groups across several Kenyan geographic areas. METHODS: The Decision Makers’ Program Planning Tool, Version 2 (DMPPT 2) was applied in Kisumu, Siaya, Homa Bay, and Migori counties. Initial modeling done in mid-2016 showed coverage estimates above 100% in age groups and geographic areas where demand for VMMC continued to be high. On the basis of information obtained from country policy makers and VMMC program implementers, we adjusted circumcision coverage for duplicate reporting, county-level population estimates, migration across county boundaries for VMMC services, and replacement of traditional circumcision with circumcisions in the VMMC program. To address residual inflated coverage following these adjustments we applied county-specific correction factors computed by triangulating model results with coverage estimates from population surveys. RESULTS: A program record review identified duplicate reporting in Homa Bay, Kisumu, and Siaya. Using county population estimates from the Kenya National Bureau of Statistics, we found that adjusting for migration and correcting for replacement of traditional circumcision with VMMC led to lower estimates of 2016 male circumcision coverage especially for Kisumu, Migori, and Siaya. Even after addressing these issues, overestimation of 2016 male circumcision coverage persisted, especially in Homa Bay. We estimated male circumcision coverage in 2016 by applying correction factors. Modeled estimates for 2016 circumcision coverage for the 10- to 14-year age group ranged from 50% in Homa Bay to approximately 90% in Kisumu. Results for the 15- to 19-year age group suggest almost complete coverage in Kisumu, Migori, and Siaya. Coverage for the 20- to 24-year age group ranged from about 80% in Siaya to about 90% in Homa Bay, coverage for those aged 25–29 years ranged from about 60% in Siaya to 80% in Migori, and coverage in those aged 30–34 years ranged from about 50% in Siaya to about 70% in Migori. CONCLUSIONS: Our analysis points to solutions for some of the data issues encountered in Kenya. Kenya is the first country in which these data issues have been encountered because baseline circumcision rates were high. We anticipate that some of the modeling methods we developed for Kenya will be applicable in other countries. Public Library of Science 2018-12-18 /pmc/articles/PMC6298728/ /pubmed/30562394 http://dx.doi.org/10.1371/journal.pone.0209385 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Kripke, Katharine
Opuni, Marjorie
Odoyo-June, Elijah
Onyango, Mathews
Young, Peter
Serrem, Kennedy
Ojiambo, Vincent
Schnure, Melissa
Stegman, Peter
Njeuhmeli, Emmanuel
Data triangulation to estimate age-specific coverage of voluntary medical male circumcision for HIV prevention in four Kenyan counties
title Data triangulation to estimate age-specific coverage of voluntary medical male circumcision for HIV prevention in four Kenyan counties
title_full Data triangulation to estimate age-specific coverage of voluntary medical male circumcision for HIV prevention in four Kenyan counties
title_fullStr Data triangulation to estimate age-specific coverage of voluntary medical male circumcision for HIV prevention in four Kenyan counties
title_full_unstemmed Data triangulation to estimate age-specific coverage of voluntary medical male circumcision for HIV prevention in four Kenyan counties
title_short Data triangulation to estimate age-specific coverage of voluntary medical male circumcision for HIV prevention in four Kenyan counties
title_sort data triangulation to estimate age-specific coverage of voluntary medical male circumcision for hiv prevention in four kenyan counties
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298728/
https://www.ncbi.nlm.nih.gov/pubmed/30562394
http://dx.doi.org/10.1371/journal.pone.0209385
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