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Modelling of malaria risk, rates, and trends: A spatiotemporal approach for identifying and targeting sub-national areas of high and low burden

March 2, 2021 - 15:21 -- Open Access
Author(s): 
Lubinda J, Bi Y, Hamainza B, Haque U, Moore AJ
Reference: 
PLoS Comput Biol. 2021 Mar 1;17(3):e1008669

While mortality from malaria continues to decline globally, incidence rates in many countries are rising. Within countries, spatial and temporal patterns of malaria vary across communities due to many different physical and social environmental factors. To identify those areas most suitable for malaria elimination or targeted control interventions, we used Bayesian models to estimate the spatiotemporal variation of malaria risk, rates, and trends and determine areas of high or low malaria burden compared to their geographical neighbours.

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