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In the Africa Continent, diphtheria remains a pressing public health concern. Despite advancements in healthcare infrastructure and vaccination efforts, several countries continue to report cases and outbreaks, indicating ongoing transmission of the disease. This research aimed at utilizing GIS application in diphtheria outbreak in the Ojo Local Government Area (LGA) of Lagos State, Nigeria, with the following objectives: (i) obtain the spatial distribution pattern of the spread of diphtheria outbreak. (ii) determine the area requiring immediate attention and response in the study area. (iii) showcase areas that are vulnerable within the study area. In the pursuance of this both primary data, including geographical coordinates of confirmed diphtheria cases, and secondary data such as recorded cases, population density, vaccination coverage, and transportation networks, the research utilizes ArcGIS for visualization and analysis, Differential Global Positioning System (DGPS) receivers ensured accurate spatial data collection, supplemented by ground truthing of secondary data. The result revealed significant clusters of diphtheria cases in Akesan-Obadore and Ijegun, indicating a higher concentration of infections. The study applied average nearest neighbor analysis, which indicated a dispersed pattern of outbreaks within the LGA. Furthermore, a risk assessment using Analytic Hierarchical Process (AHP), in identifying the southern parts and Iba ward of Ojo LGA as areas with highest risk. The study recommends to the Lagos State Government to enhance vaccination efforts and improve sanitation infrastructure in these high-risk areas to mitigate the spread of diphtheria.
Ayodele et al. (Sat,) studied this question.