Abstract
BACKGROUND: Malaria is a major public health problem in Tanzania, accounting for 3.1% of the global cases, with under-five children being particularly vulnerable. Over half of malaria deaths in Tanzania occurred among under-five children. Identifying the spatial determinants of malaria is crucial for optimizing targeted interventions to reduce morbidity and mortality in this vulnerable population. Therefore, this study aimed to assess the spatial determinants of malaria and factors associated with malaria infection among under-five children in Tanzania. METHODS: A secondary data analysis was carried out using the Tanzanian Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) 2022 data. A total weighted sample of 4971 under-five children was included in the analysis. Spatial determinants of malaria were identified by ordinary least square and geographically weighted regression analysis. A multilevel binary logistic regression model was fitted to identify factors associated with malaria infection among under-five children. RESULTS: Malaria among under-five children was spatially clustered in Tanzania (Moran's Index = 0.14, p-value < 0.0001). Significant primary clusters of malaria were identified in the Northwestern part of the country (western and Lake zones) (log-likelihood ratio (LLR = 80.22, p < 0.0001) and secondary clusters in the Mtwara region (LLR = 16.04, p < 0.0001). Wealth index and access to health care were significant determinants of spatial clustering of malaria among under-five children. In the multilevel analysis, maternal education [primary level (AOR = 0.71, 95% CI 0.52-0.97)], child age of 48-59 months (AOR = 3.17, 95% CI: 1.80-5.62), family size of 5 to 10 (AOR = 1.69, 95%CI 1.12, 2.54), being in poor wealth index (AOR = 2.56, 95% CI 1.18-5.57), and unimproved roof (AOR = 1.49, 95% CI 1.04-2.16) were significantly associated with malaria infection among under-five children. CONCLUSION AND RECOMMENDATION: Malaria among under-five children in Tanzania shows significant spatial clustering, particularly in the Northwestern and Southern parts of the country. This spatial clustering of malaria was attributed to poor socioeconomic status and lack of access to health care. Improving access to health care and enhancing malaria prevention measures for the economically disadvantaged group could have a better impact on reducing the burden of malaria.