2023
DOI: 10.21203/rs.3.rs-3018944/v1
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Bayesian belief network modeling approach for predicting and ranking risk factors for malaria infections among children under five years in refugee settlements in Uganda

Abstract: Background Malaria risk factors at household level are known to be complex, uncertain, stochastic, nonlinear, and multidimensional. The interplay among these factors, makes targeted interventions, and resource allocation for malaria control challenging. However, few studies have demonstrated malaria’s transmission complexity, control, and integrated modeling, with no available evidence on Uganda’s refugee settlements. Using the 2018–2019 Uganda’s Malaria Indicator Survey (UMIS) data, an alternative Bayesian b… Show more

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