Abstract
Developing countries face a huge burden of infectious diseases, a number of which co-exist. This paper estimates the pattern and variation of malaria and diarrhea coexistence in Chikhwawa, a district in Southern Malawi using bivariate multilevel modelling with Bayesian estimation. A probit link was employed to examine hierarchically built data from a survey of individuals (n = 6,727) nested within households (n = 1,380) nested within communities (n = 33). Results show significant malaria [ ] and diarrhea [ ] variations with a strong correlation between them [] at household level. There are significant malaria [] and diarrhea [] variations at community level but with a small correlation [] between them. There is also significant correlation between malaria and diarrhea at individual level [0.241]. These results suggest a close association between reported malaria-like illness and diarrheal illness especially at household and individual levels in Southern Malawi.
Highlights
While the World Health Organisation Millennium Development Goals (MDGs) propose to reduce the burden of morbidity and mortality by 2015 [1,2], establishing the cause of disease or death may not be straightforward
In this study the aim was to determine the concurrence of reported ML disease and diarrheal illness in Chikhwawa, Southern Malawi by identifying patterns of variation and their common risk factors
Individuals who experienced ML disease were likely to have suffered from diarrheal illness during the same period
Summary
While the World Health Organisation Millennium Development Goals (MDGs) propose to reduce the burden of morbidity and mortality by 2015 [1,2], establishing the cause of disease or death may not be straightforward. The complex nature of underlying risk factors, often leading to concurrent infections in sick individuals [3], is a challenge in many settings In developing countries, this phenomenon is highly prevalent at the community level and among children seeking care [4]. United Nations Children’s Fund (UNICEF) with the aim, among others, of addressing such coexistence of diseases in children [3,4] For programmes such as the IMCI to be successful empirical methods to determine characteristics of diseases that coexist are necessary. This study employs a bivariate multilevel modelling technique with the aim of analysing the coexistence between malaria and diarrhea in Chikhwawa by identifying patterns of variation and their common risk factors. 41.7% for malaria and 18% for diarrhea [7,15]
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