Shared component modelling of early childhood anaemia and malaria in Kenya, Malawi, Tanzania and Uganda

Abstract

Abstract Background Malaria and anaemia contribute substantially to child morbidity and mortality. In this study, we sought to jointly model the residual spatial variation in the likelihood of these two correlated diseases, while controlling for individual-level, household-level and environmental characteristics. Methods A child-level shared component model was utilised to partition shared and disease-specific district-level spatial effects. Results The results indicated that the spatial variation in the likelihood of malaria was more prominent compared to that of anaemia, for both the shared and specific spatial components. In addition, approximately 30% of the districts were associated with an increased likelihood of anaemia but a decreased likelihood of malaria. This suggests that there are other drivers of anaemia in children in these districts, which warrants further investigation. Conclusions The maps of the shared and disease-specific spatial patterns provide a tool to allow for more targeted action in malaria and anaemia control and prevention, as well as for the targeted allocation of limited district health system resources.

Keywords

• Adjusted posterior odds ratios
• Bayesian inference
• Conditional autoregressive
• Joint modelling
• Spatial modelling