Spatio-temporal modeling of malaria cases in Tanzania

Abstract: Malaria continues to pose a significant global health challenge, affecting approximately 200 million individuals annually and causing an estimated 600,000 deaths worldwide. Environmental factors are key drivers of malaria transmission dynamics, influencing disease patterns at local and regional scales. This talk focuses on data from Tanzania to explore the impact of climatic factors and vector control interventions on malaria incidence.

Using Standardized Incidence Ratio (SIR) metrics and Bayesian spatio-temporal modeling approaches, we analyze regionally aggregated monthly malaria cases, stratified into two age groups: children under five and individuals aged five years and above. The models incorporate a Conditional Autoregressive (CAR) structure to capture spatial dependencies, a second-order random walk (RW2) for temporal trends, and independent and identically distributed (iid) random effects to account for unstructured spatial and temporal variability. Specific results on the influence of environmental factors, including precipitation and temperature, on malaria cases will be presented during the talk, highlighting their role in transmission dynamics and informing targeted intervention strategies.

machine learningprobabilitystatistics theory

Audience: researchers in the discipline

Comments: Results are not yet published, please make them confidential.

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Gothenburg statistics seminar

Series comments: Gothenburg statistics seminar is open to the interested public, everybody is welcome. It usually takes place in MVL14 (http://maps.chalmers.se/#05137ad7-4d34-45e2-9d14-7f970517e2b60, see specific talk). Speakers are asked to prepare material for 35 minutes excluding questions from the audience.

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