Abstract
Background Local villages in the Vhembe district of South Africa have experienced high malaria infection rates and a high variability of malaria case mortality rates over the past 20 years. This research project sets out to determine if specific socioeconomic factors have influence on the varying malaria case mortality rates. Methods The study used existing malaria records of all reported malaria cases in the Vhembe district between 1998 and 2017. The data set was sampled using maximum variation sampling combined with a stratified sampling approach to select the source locations with the highest reported variations in malaria case mortality. The number of medical facilities used, distances to the medical facilities, and proximity to significant water sources were subsequently spatially and statistically analysed for potential correlations between these factors and the malaria case fatality rates of the source locations. Results Within the period of study, a total of 57,974 malaria infections were reported from 850 source locations across the villages and neighbourhoods. The result of the sampling methods gave 30 source locations with highest reported variations in malaria case mortality. The statistical analysis indicated a significant negative correlation between the case mortality rates and the number of medical facilities used, the number of infections reported, and the maximum and mean distances travelled to the medical facilities used. In addition, the analysis indicated a positive correlation between the minimum distances travelled to the medical facilities used and the case mortality rates. The spatial analysis supported the majority of the findings from the statistical analysis. Proximity to significant water bodies was not found to have any significant impact on case mortality rates. Conclusion The results suggested that malaria patients from larger communities, those who had financial or other means to consult more advanced facilities, or those with a larger variety of services had a significantly lower risk of mortality. The findings of this study could assist societies and authorities in mitigating the negative effects of malaria infections on human life expectancies through improved socioeconomic development.
Highlights
Malaria is a significant vector-borne disease that influences the global population and places a detrimental health care burden on many communities globally [1]. e spatial distribution of malaria infections is significantly influenced by climate conditions and the ability of communities to prevent and treat the disease [2]
Previous studies have investigated the impact of climate change on vector-borne diseases with significantly conclusive results, indicating that climate change can have a major impact on the spreading of vector-borne diseases, malaria [3]. is has been recorded in multiple areas, including the Northwest Frontier Province of Pakistan, Eastern Africa, and South Sudan, Journal of Environmental and Public Health where a direct link was found between humidity increases due to climate change and the instances of malaria infections and death [4, 5]
Parham et al [6] conducted intensive research to determine the link between malaria cases and climatic factors through a semi-parametric econometric model. e findings indicated that a marginal change in temperature and precipitation could result in a substantial change in the number of malaria cases, and further research was recommended, which indicates that spatial scales of available climate prediction need to be overlaid with socioeconomic data on a local scale to determine if infrastructure and other economic development aspects will affect the level of anticipated transmissions
Summary
Malaria is a significant vector-borne disease that influences the global population and places a detrimental health care burden on many communities globally [1]. e spatial distribution of malaria infections is significantly influenced by climate conditions and the ability of communities to prevent and treat the disease [2]. E findings indicated that a marginal change in temperature and precipitation could result in a substantial change in the number of malaria cases, and further research was recommended, which indicates that spatial scales of available climate prediction need to be overlaid with socioeconomic data on a local scale to determine if infrastructure and other economic development aspects will affect the level of anticipated transmissions. E number of medical facilities used, distances to the medical facilities, and proximity to significant water sources were subsequently spatially and statistically analysed for potential correlations between these factors and the malaria case fatality rates of the source locations. E result of the sampling methods gave 30 source locations with highest reported variations in malaria case mortality. E statistical analysis indicated a significant negative correlation between the case mortality rates and the number of medical facilities used, the number of infections reported, and the maximum and mean distances travelled to the medical facilities used. Conclusion. e results suggested that malaria patients from larger communities, those who had financial or other means to consult more advanced facilities, or those with a larger variety of services had a significantly lower risk of mortality. e findings of this study could assist societies and authorities in mitigating the negative effects of malaria infections on human life expectancies through improved socioeconomic development
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