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Impact of traffic congestion on spatial access to healthcare services in Nairobi

BACKGROUND: Geographic accessibility is an important determinant of healthcare utilization and is critical for achievement of universal health coverage. Despite the high disease burden and severe traffic congestion in many African cities, few studies have assessed how traffic congestion impacts geog...

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Autores principales: Mutono, Nyamai, Wright, Jim A., Mutunga, Mumbua, Mutembei, Henry, Thumbi, S. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012710/
https://www.ncbi.nlm.nih.gov/pubmed/36925766
http://dx.doi.org/10.3389/frhs.2022.788173
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author Mutono, Nyamai
Wright, Jim A.
Mutunga, Mumbua
Mutembei, Henry
Thumbi, S. M.
author_facet Mutono, Nyamai
Wright, Jim A.
Mutunga, Mumbua
Mutembei, Henry
Thumbi, S. M.
author_sort Mutono, Nyamai
collection PubMed
description BACKGROUND: Geographic accessibility is an important determinant of healthcare utilization and is critical for achievement of universal health coverage. Despite the high disease burden and severe traffic congestion in many African cities, few studies have assessed how traffic congestion impacts geographical access to healthcare facilities and to health professionals in these settings. In this study, we assessed the impact of traffic congestion on access to healthcare facilities, and to the healthcare professionals across the healthcare facilities. METHODS: Using data on health facilities obtained from the Ministry of Health in Kenya, we mapped 944 primary, 94 secondary and four tertiary healthcare facilities in Nairobi County. We then used traffic probe data to identify areas within a 15-, 30- and 45-min drive from each health facility during peak and off-peak hours and calculated the proportion of the population with access to healthcare in the County. We employed a 2-step floating catchment area model to calculate the ratio of healthcare and healthcare professionals to population during these times. RESULTS: During peak hours, <70% of Nairobi's 4.1 million population was within a 30-min drive from a health facility. This increased to >75% during off-peak hours. In 45 min, the majority of the population had an accessibility index of one health facility accessible to more than 100 people (<0.01) for primary health care facilities, one to 10,000 people for secondary facilities, and two health facilities per 100,000 people for tertiary health facilities. Of people with access to health facilities, a sub-optimal ratio of <4.45 healthcare professionals per 1,000 people was observed in facilities offering primary and secondary healthcare during peak and off-peak hours. CONCLUSION: Our study shows access to healthcare being negatively impacted by traffic congestion, highlighting the need for multisectoral collaborations between urban planners, health sector and policymakers to optimize health access for the city residents. Additionally, growing availability of traffic probe data in African cities should enable similar analysis and understanding of healthcare access for city residents in other countries on the continent.
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spelling pubmed-100127102023-03-15 Impact of traffic congestion on spatial access to healthcare services in Nairobi Mutono, Nyamai Wright, Jim A. Mutunga, Mumbua Mutembei, Henry Thumbi, S. M. Front Health Serv Health Services BACKGROUND: Geographic accessibility is an important determinant of healthcare utilization and is critical for achievement of universal health coverage. Despite the high disease burden and severe traffic congestion in many African cities, few studies have assessed how traffic congestion impacts geographical access to healthcare facilities and to health professionals in these settings. In this study, we assessed the impact of traffic congestion on access to healthcare facilities, and to the healthcare professionals across the healthcare facilities. METHODS: Using data on health facilities obtained from the Ministry of Health in Kenya, we mapped 944 primary, 94 secondary and four tertiary healthcare facilities in Nairobi County. We then used traffic probe data to identify areas within a 15-, 30- and 45-min drive from each health facility during peak and off-peak hours and calculated the proportion of the population with access to healthcare in the County. We employed a 2-step floating catchment area model to calculate the ratio of healthcare and healthcare professionals to population during these times. RESULTS: During peak hours, <70% of Nairobi's 4.1 million population was within a 30-min drive from a health facility. This increased to >75% during off-peak hours. In 45 min, the majority of the population had an accessibility index of one health facility accessible to more than 100 people (<0.01) for primary health care facilities, one to 10,000 people for secondary facilities, and two health facilities per 100,000 people for tertiary health facilities. Of people with access to health facilities, a sub-optimal ratio of <4.45 healthcare professionals per 1,000 people was observed in facilities offering primary and secondary healthcare during peak and off-peak hours. CONCLUSION: Our study shows access to healthcare being negatively impacted by traffic congestion, highlighting the need for multisectoral collaborations between urban planners, health sector and policymakers to optimize health access for the city residents. Additionally, growing availability of traffic probe data in African cities should enable similar analysis and understanding of healthcare access for city residents in other countries on the continent. Frontiers Media S.A. 2022-11-16 /pmc/articles/PMC10012710/ /pubmed/36925766 http://dx.doi.org/10.3389/frhs.2022.788173 Text en Copyright © 2022 Mutono, Wright, Mutunga, Mutembei and Thumbi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Health Services
Mutono, Nyamai
Wright, Jim A.
Mutunga, Mumbua
Mutembei, Henry
Thumbi, S. M.
Impact of traffic congestion on spatial access to healthcare services in Nairobi
title Impact of traffic congestion on spatial access to healthcare services in Nairobi
title_full Impact of traffic congestion on spatial access to healthcare services in Nairobi
title_fullStr Impact of traffic congestion on spatial access to healthcare services in Nairobi
title_full_unstemmed Impact of traffic congestion on spatial access to healthcare services in Nairobi
title_short Impact of traffic congestion on spatial access to healthcare services in Nairobi
title_sort impact of traffic congestion on spatial access to healthcare services in nairobi
topic Health Services
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10012710/
https://www.ncbi.nlm.nih.gov/pubmed/36925766
http://dx.doi.org/10.3389/frhs.2022.788173
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