Identifying childhood malaria hotspots and risk factors in a Nigerian city using geostatistical modelling approach.

ABSTRACT: Malaria ranks high among prevalent and ravaging infectious diseases in sub-Saharan Africa (SSA). The negative impacts, disease burden, and risk are higher among children and pregnant women as part of the most vulnerable groups to malaria in Nigeria. However, the burden of malaria is not even in space and time. This study explores the spatial variability of malaria prevalence among children under five years (U5) in medium-sized rapidly growing city of Akure, Nigeria using model-based geostatistical modeling (MBG) technique to predict U5 malaria burden at a 100 × 100 m grid, while the parameter estimation was done using Monte Carlo maximum likelihood method. The non-spatial logistic regression model shows that U5 malaria prevalence is significantly influenced by the usage of insecticide-trea

SUBMITTER: Bayode T 

PROVIDER: S-EPMC10914794 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature