Appraising Malaria Incidence with Spatial-Oriented Decision Support System in Parts of Zaria, Kaduna State-Nigeria

Prevalence of malaria in certain parts of the world without adequate planning and monitoring based on ill- informed decisions has wreaked havoc on the health system and economy of many developing nations. The purpose of this study is to create a functional Spatial Decision Support System (SDSS) for malaria monitoring in parts of Zaria, Kaduna State. A Geographic Information Systems (GIS) SDSS was created using ArcGIS 10.5 software for the 2019 Malaria data obtained from the Ministry of Health, Kaduna State Roll Back Malaria (RBM) Programme for collation and analysis across 13 political wards in Zaria Local Government Area (LGA) of Kaduna State. The results revealed that a total of 443,852 cases of malaria were reported across the 13 political wards of the study area. The reported cases had predominant occurrences at the Gyellesu ward, followed by the Kwarbai A ward. The spatial incidence was displayed via vector control maps, malaria burden maps, malaria prevalence in Zaria maps, and service area maps. The map of demography indicated a higher prevalence of malaria of 73.35% for the male gender compared to the female (26.65%). However, the independent t-test revealed no significant difference between males' and females' malaria prevalence. It was also revealed that the adult population had the highest malaria prevalence followed by children less than 5 years while pregnant women were the least infected. The study further indicated that 38.5% of the existing political wards recorded a shortfall of at least two (2) healthcare facilities. This study identified areas that required the establishment of health facilities to offset the existing shortfall. The SDSS was able to effectively monitor and appraise malaria incidence for proper surveillance and management that will be required for malaria prevention and elimination activities. The study recommends that policymakers invest in the deployment of an SDSS for better and robust planning, monitoring and execution of their malaria intervention programmes as this aligns with the sustainable development goal (SDG) target 3.