Modelling the Linear and Nonlinear Effects of Malaria Risk Factors on Child Mortality

Generalized additive model was used to analyse data from Nigeria standard demographic and health survey (NDHS) 2018. The sample consists of 10609 children aged 6-59 months who were tested for malaria parasitemia through the rapid diagnostic test (RDT). Child mortality data was obtained by calculating the difference between the number of children ever born and the proportion of children alive during the survey. The analysis was carried out in R version 4.1.1 via mgcv package. The results obtained indicated linear and nonlinear effects of malaria risk factors on child mortality. The findings also revealed mosquito bed net usage, wealth index, maternal education, type of place of residence and malaria test outcome as significant predictors of child malaria mortality.