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University of Basel (2021)

Estimating the patterns and consequences of malaria transmission dynamics on fine spatial scales

Malinga, Josephine

Titre : Estimating the patterns and consequences of malaria transmission dynamics on fine spatial scales

Auteur : Malinga, Josephine.

Université de soutenance : University of Basel

Grade : Doctor of Philosophy (PhD) 2021

Résumé partiel
Plasmodium falciparum is the leading cause of malaria infection and a major cause of morbidity and mortality across the globe, particularly in the African region. The burden of malaria is unevenly distributed, with some countries, districts or even households within villages harboring a disproportionally higher burden. There is an intricate relationship between the mosquito vector, humans and the parasites they carry, and how they interact with the environment. Small movements on a fine-scale lead to the patterns observed in the community. Quantifying transmission dynamics on a fine-scale, how malaria infections spread locally and the processes leading to the observed spatial and temporal distribution patterns is important for many aspects of malaria epidemiology, in particular, the design of targeted interventions against malaria, the design of studies to evaluate the effectiveness of vector control in the field, and the parameterization of mathematical models to predict the likely impact of interventions for settings where data is not available. Mathematical and statistical models have been developed to quantify fine scale malaria transmission dynamics and investigate the effects of interventions. Since data on the spread of vectors and parasites is challenging to collect, it is not available from many endemic settings for analytic methods to provide estimates, or to validate model predictions. Due to variability between settings, findings from one setting cannot be easily generalized. There is thus a need to involve methods that can extract information from imperfect but available datasets, to make the most of the existing data sources from settings with a variety of characteristics. The overall aim of this thesis was to use statistical and mathematical modelling approaches to characterize fine scale malaria transmission dynamics and their consequences on the measurement of heterogeneity on a local scale for targeted interventions.

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Page publiée le 28 mai 2021