Abstract:
According to World Health Organization 2010 report, there is lack of information on disease geospatial data and insufficient health systems, which is a major global problem particularly in the rural areas of Africa. Though there is a decline of number of deaths to 584,000 in sub-Saharan Africa including Kenya, malaria prevalence has still remained high around Lake Victoria region. This is due to the presence of efficient malaria vectors and persistent mosquito breeding sites. The malaria elimination has also remained a problem due to lack of information on continuous monitoring of malaria cases through geospatial data technique. For effectiveness and successful implementation of the framework for curbing malaria, GIS technology was used to analyze epidemiological and entomological data to show distribution pattern of malaria cases and mosquito breeding sites. The objectives were achieved by conducting two cross-sectional malaria surveys. This was done by screening 2375 and 2,095 individuals using a Rapid Diagnostic Test, collecting social demographic and physical risk factors of malaria in different seasons. A total of 302 mosquito breeding sites were mapped to determine the spatial relationship between the mosquito breeding sites and malaria prevalence using QGIS technique. SatScan v9.4.2 was used to perform hotspot analysis, detected two major hotspots of which one hotspot persisted due to its proximity to mosquito breeding sites during all seasons. In addition, a multiple regression analysis that was performed using Stata version 14, indicated a strong association between the use of mosquito traps (p=0.048), altitude classification (p=0.031) and proximity to mosquito breeding sites (p=0.016) in relation to the distribution pattern of malaria cases. The results further indicated that malaria distribution pattern was heterogeneously spread with households that were near breeding sites reporting more malaria cases. The application of mobile technology in the framework for curbing malaria can be adopted in other similar settings to address operational and implementation challenges in the elimination of malaria. This can be achieved through monitoring the distribution of the mosquito breeding sites and malaria cases to facilitate the identification of hotspots for targeted intervention.
