Development of health density indicators in South Africa using GIS
PUBLICATION YEAR: 2012
TITLE AUTHOR(S): T.Mokhele, G.Weir-Smith, D.Labadarios
KEYWORDS: GEOGRAPHIC INFORMATION SYSTEMS (GIS), PUBLIC HEALTH
Intranet: HSRC Library: shelf number 7455
HANDLE: 20.500.11910/3226
URI: http://hdl.handle.net/20.500.11910/3226
If you would like to obtain a copy of this Research Output, please contact Hanlie Baudin at researchoutputs@hsrc.ac.za.
Abstract
The scope and emphasis of a public health program are necessarily influenced by the changing characteristics of the population it serves. In South Africa, population growth between 2004 and 2009 has outstripped the availability of health facilities. GIS provides ideal platforms for decision makers to easily visualize problems in relation to existing health services as well as distribution of health facilities and their surrounding populations. Therefore this research was aimed at developing health density indicators in South Africa at a sub-provincial level using GIS in order for decision makers to target appropriate populations and areas for intervention. This research used the existing (5043) public health facilities data (2010) together with some additional data from the Department of Health and Stats SA Community Survey 2007 population estimates at municipality level to develop two health facilities density indicators. The first indicator, health facilities per population, was calculated by dividing the number of health facilities by the total population (per 10 000) at a municipal level. The second indicator was calculated by dividing the number of health facilities by square kilometre. Findings showed that most municipalities that had a low coverage in terms of the number of health facilities per 10000 population are located in the eastern part of the country as well as in urban areas even though there are more health facilities in these urban areas as the total population is also much higher due to migration. Therefore, the combination of the two indicators is of high importance in final decision making in prioritizing areas for health care interventions for large municipalities characterized with low populations.-
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