Beyond Exploratory Data: Using Cluster Detection Tests to Pinpoint Malaria Hotspots in Nigeria

Abstract

AbstractMalaria is not communicable, but it can deteriorate and even kill a person within a day if treatment is not taken. Plasmodium falciparum is the malaria parasite that is most prevalent and deadly in Africa. This study attempts to identify malaria hotspots and potentially high-risk areas in Oyo state, Nigeria. Data on malaria cases from 2013 to 2016 were provided by the Department of Research, Planning, and Statistics (DPRS) of the Oyo State Ministry of Health. Spatial autocorrelation testing, spatiotemporal analysis, and descriptive statistics were performed using SatScan V9.11 and ArcGIS V10.8. The four-year malaria incidence study was conducted in Oyo West LGA and is geographically focused. Four clusters were found using spatial analysis, with the majority of the clusters located in the Oyo South region. Spatial-temporal research revealed three noteworthy groups. The cluster that happened between January 2013 and December 2014 is located in the Oyo South and Oyo Central region. High-high malaria clusters were identified by spatial autocorrelation analysis, particularly in Oyo Central; the yearly clustered pattern of malaria incidence was not coincidental. In order to better achieve effective disease surveillance, this study suggests employing more cluster detection tests (or CDTs) rather than just exploratory data analysis prior to the implementation of health treatments and regulations.