Free Content Modelling distances travelled to government health services in Kenya

You have access to the full text article on a website external to ingentaconnect.

Please click here to view this article on Wiley Online Library.

You may be required to register and activate access on Wiley Online Library before you can obtain the full text. If you have any queries please visit Wiley Online Library

Download Article:

Abstract:

Summary 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.

Keywords: Kenya; access; distance models; health services; millennium development goals; use

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1365-3156.2005.01555.x

Affiliations: 1: Malaria Public Health & Epidemiology Group, Kenya Medical Research Institute/Wellcome Trust Research Laboratories, Nairobi, Kenya 2: School of Geography, University of Southampton, UK

Publication date: February 1, 2006

Related content

Tools

Favourites

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more