Abstract
BackgroundAlthough effective treatment for malaria is now available, approximately half of the global population remain at risk of the disease particularly in developing countries. To design effective malaria control strategies there is need to understand the pattern of malaria heterogeneity in an area. Therefore, the main objective of this study was to explore the spatial and spatio-temporal pattern of malaria cases in Zimbabwe based on malaria data aggregated at district level from 2011 to 2016.MethodsGeographical information system (GIS) and spatial scan statistic were applied on passive malaria data collected from health facilities and aggregated at district level to detect existence of spatial clusters. The global Moran’s I test was used to infer the presence of spatial autocorrelation while the purely spatial retrospective analyses were performed to detect the spatial clusters of malaria cases with high rates based on the discrete Poisson model. Furthermore, space-time clusters with high rates were detected through the retrospective space-time analysis based on the discrete Poisson model.ResultsResults showed that there is significant positive spatial autocorrelation in malaria cases in the study area. In addition, malaria exhibits spatial heterogeneity as evidenced by the existence of statistically significant (P < 0.05) spatial and space-time clusters of malaria in specific geographic regions. The detected primary clusters persisted in the eastern region of the study area over the six year study period while the temporal pattern of malaria reflected the seasonality of the disease where clusters were detected within particular months of the year.ConclusionsGeographic regions characterised by clusters of high rates were identified as malaria high risk areas. The results of this study could be useful in prioritizing resource allocation in high-risk areas for malaria control and elimination particularly in resource limited settings such as Zimbabwe. The results of this study are also useful to guide further investigation into the possible determinants of persistence of high clusters of malaria cases in particular geographic regions which is useful in reducing malaria burden in such areas.
Highlights
Effective treatment for malaria is available, approximately half of the global population remain at risk of the disease in developing countries
Annual incidence of malaria An analysis of annual malaria cases shows that over the 6 years, the northern, north-eastern, eastern and southeastern districts of the country were characterised by high malaria incidence (Fig. 3)
The results indicated that high risk areas for malaria are concentrated in the northern, eastern, and south-eastern part of the country
Summary
Effective treatment for malaria is available, approximately half of the global population remain at risk of the disease in developing countries. As a result of the substantial decline in malaria cases in Zimbabwe, the country adopted the global and regional agenda for malaria elimination by 2030 [14]. As malaria transmission continue to decline, prevention and control interventions will increasingly rely on accurate knowledge of the spatial distribution of high-risk geographic areas to support malaria elimination. This could be useful in optimal allocation of limited resources to ensure that areas with the highest malaria burden are given priority [16, 17]. Mapping malaria spatial heterogeneity is important to better understand transmission dynamics [18, 19]
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