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Shared component modelling of early childhood anaemia and malaria in Kenya, Malawi, Tanzania and Uganda
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 characteri...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632052/ https://www.ncbi.nlm.nih.gov/pubmed/36329413 http://dx.doi.org/10.1186/s12887-022-03694-4 |
Sumario: | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12887-022-03694-4. |
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