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Modelling distances travelled to government health services in Kenya

Modelling distances travelled to government health services in Kenya
Modelling distances travelled to government health services in Kenya
Objective: To systematically evaluate descriptive measures of spatial access to medical treatment, as part of the millennium development goals to reduce the burden of HIV/AIDS, tuberculosis and malaria.
Methods We obtained high-resolution spatial and epidemiological data on health services, population, transport network, topography, land cover and paediatric fever treatment in four Kenyan districts to develop access and use models for government health services in Kenya. Community survey data were used to model use of government health services by febrile children. A model based on the transport network was then implemented and adjusted for actual use patterns. We compared the predictive accuracy of this refined model to that of Euclidean distance metrics.
Results: Higher-order facilities were more attractive to patients (54%, 58% and 60% in three scenarios) than lower-order ones. The transport network model, adjusted for competition between facilities, was most accurate and selected as the best-fit model. It estimated that 63% of the population of the study districts were within the 1 h national access benchmark, against 82% estimated by the Euclidean model.
Conclusions: Extrapolating the results from the best-fit model in study districts to the national level shows that approximately six million people are currently incorrectly estimated to have access to government health services within 1 h. Simple Euclidean distance assumptions, which underpin needs assessments and against which millennium development goals are evaluated, thus require reconsideration.
Health service, Kenya, travel distances, modelling
1360-2276
188-196
Noor, Abdisalan M.
06d32991-29fe-47a5-a62b-fe584c753414
Amin, Abdinasir A.
2d9a4fe1-c527-4264-9377-bb7fa89cf797
Gething, Peter W.
6afb7d8c-8816-4c03-ae73-55951c8b197f
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Hay, Simon I.
471d3ae4-a3c1-4d29-93e3-a90d44471b00
Snow, Robert W.
7ff98228-6657-4b33-9793-b7f91a06c187
Noor, Abdisalan M.
06d32991-29fe-47a5-a62b-fe584c753414
Amin, Abdinasir A.
2d9a4fe1-c527-4264-9377-bb7fa89cf797
Gething, Peter W.
6afb7d8c-8816-4c03-ae73-55951c8b197f
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Hay, Simon I.
471d3ae4-a3c1-4d29-93e3-a90d44471b00
Snow, Robert W.
7ff98228-6657-4b33-9793-b7f91a06c187

Noor, Abdisalan M., Amin, Abdinasir A., Gething, Peter W., Atkinson, Peter M., Hay, Simon I. and Snow, Robert W. (2006) Modelling distances travelled to government health services in Kenya. Tropical Medicine & International Health, 11 (2), 188-196. (doi:10.1111/j.1365-3156.2005.01555.x).

Record type: Article

Abstract

Objective: To systematically evaluate descriptive measures of spatial access to medical treatment, as part of the millennium development goals to reduce the burden of HIV/AIDS, tuberculosis and malaria.
Methods We obtained high-resolution spatial and epidemiological data on health services, population, transport network, topography, land cover and paediatric fever treatment in four Kenyan districts to develop access and use models for government health services in Kenya. Community survey data were used to model use of government health services by febrile children. A model based on the transport network was then implemented and adjusted for actual use patterns. We compared the predictive accuracy of this refined model to that of Euclidean distance metrics.
Results: Higher-order facilities were more attractive to patients (54%, 58% and 60% in three scenarios) than lower-order ones. The transport network model, adjusted for competition between facilities, was most accurate and selected as the best-fit model. It estimated that 63% of the population of the study districts were within the 1 h national access benchmark, against 82% estimated by the Euclidean model.
Conclusions: Extrapolating the results from the best-fit model in study districts to the national level shows that approximately six million people are currently incorrectly estimated to have access to government health services within 1 h. Simple Euclidean distance assumptions, which underpin needs assessments and against which millennium development goals are evaluated, thus require reconsideration.

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More information

Published date: February 2006
Keywords: Health service, Kenya, travel distances, modelling

Identifiers

Local EPrints ID: 38940
URI: http://eprints.soton.ac.uk/id/eprint/38940
ISSN: 1360-2276
PURE UUID: dc07841c-dca8-4d52-afb5-d7bc2efc55c1
ORCID for Peter M. Atkinson: ORCID iD orcid.org/0000-0002-5489-6880

Catalogue record

Date deposited: 16 Jun 2006
Last modified: 16 Mar 2024 02:46

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Contributors

Author: Abdisalan M. Noor
Author: Abdinasir A. Amin
Author: Peter W. Gething
Author: Peter M. Atkinson ORCID iD
Author: Simon I. Hay
Author: Robert W. Snow

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