Description du sujet de thèse

Schistosoma mansoni is a major parasite responsible for schistosomiasis, a disease that affects around 250 million people worldwide, particularly in tropical and subtropical regions. Since 2014, the disease has also become endemic in Corsica and is expected to spread further into the European continent. Schistosomiasis, one of the neglected tropical diseases, is transmitted through freshwater snails. It has a severe impact on public health, causing chronic illness and, in some cases, fatal outcomes. Effective control of this parasite would not only improve health but also contribute to better socio-economic conditions in affected regions.

Gene drive is a genetic engineering technology designed to bias the inheritance of specific genes, thereby increasing their prevalence within a population. This approach can be used to disseminate a genetic modification through a target species, with the potential to control or eliminate undesirable traits or organisms. In the case of Schistosoma mansoni, gene drive could be employed to introduce a gene that is either lethal or reduces the parasite's lifespan, thereby lowering transmission rates.

This PhD project focuses on developing a mathematical model to predict and analyze the effects of using a gene-drive strategy to control Schistosoma mansoni directly, rather than through its snail intermediate host. Mathematical modeling is essential for anticipating the long-term impacts of gene drive interventions, optimizing strategies before implementation, and evaluating both their effectiveness and potential risks. The model will be calibrated using data from experimental characterization of the gene drive system and will guide the design of mesocosm experiments. In turn, results from these experiments will help refine and improve the model. Finally, the model will be placed within a broader societal context to assess the feasibility of applying gene drive technology for schistosomiasis control in different endemic regions, taking into account varying levels of public acceptance.

Contexte de travail

The PhD student will be supervised by Dr. Bart Haegeman (mathematical modeling in ecology, LOMIC, Banyuls-sur-Mer) and Prof. Christoph Grunau (Host-Pathogen-Environment Interactions, IHPE, Perpignan). Both laboratories are equipped with all the necessary computational resources to carry out the PhD project. This PhD is part of an interdisciplinary research project, involving mathematicians, molecular biologists, parasitologists, and philosophers from France, the Netherlands, the United States, and Brazil, combining theoretical, experimental, and societal expertise.

Contraintes et risques

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Informations complémentaires

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