Geospatial Mapping Of Malaria Susceptibility in Suleja Local Government of Niger State, Nigeria

Abstract

The accurate measurement of malaria incidence is essential to track progress and target high-risk populations. While health management information system (HMIS) data provide counts (occurrences) of malaria cases, quantifying the denominator for incidence using these data is challenging because catchment areas and care-seeking behaviors are not well defined. This study seeks to investigate malaria incidence rate (persons infected with malaria) in Suleja local government area (LGA) of Niger state. Malaria time series datasets data (2014-2022) was retrieve from the Ministry of health, Niger state. The dataset was sorted, filtered and refined for missing data using linear interpolation method. Statistical tools such as Bar chat and simple least square regression analyses tool was used to represent the malaria vector data at each ward and to estimate the malaria occurrence rate in the next ten years. At 95% confidence level, the malaria susceptibility rate was estimate to be fifty-six thousand four hundred and thirty-eight (56,438) persons infected with malaria vector in the LGA in the next ten years. The number of persons to be infected is quite disturbing when compared to the total population density of the LGA. However, the veracity of the research needs to be investigated by the LGA, this will aid in making policies and law relative to the causes of the high breed of female Anopheles mosquitoes in the LGA