Mechanistic models of Rift Valley fever virus transmission dynamics: A systematic review.

Cecilia Hélène, Drouin Alex, Métras Raphaëlle, Balenghien Thomas, Durand Benoit, Chevalier Véronique, Ezanno Pauline. 2022. Mechanistic models of Rift Valley fever virus transmission dynamics: A systematic review.. PLoS Neglected Tropical Diseases, 16 (11):e0010339, 32 p.

https://doi.org/10.1371/journal.pntd.0010339

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Résumé : Rift Valley fever (RVF) is a zoonotic arbovirosis which has been reported across Africa including the northernmost edge, South West Indian Ocean islands, and the Arabian Peninsula. The virus is responsible for high abortion rates and mortality in young ruminants, with economic impacts in affected countries. To date, RVF epidemiological mechanisms are not fully understood, due to the multiplicity of implicated vertebrate hosts, vectors, and ecosystems. In this context, mathematical models are useful tools to develop our understanding of complex systems, and mechanistic models are particularly suited to data-scarce settings. Here, we performed a systematic review of mechanistic models studying RVF, to explore their diversity and their contribution to the understanding of this disease epidemiology. Researching Pubmed and Scopus databases (October 2021), we eventually selected 48 papers, presenting overall 49 different models with numerical application to RVF. We categorized models as theoretical, applied, or grey, depending on whether they represented a specific geographical context or not, and whether they relied on an extensive use of data. We discussed their contributions to the understanding of RVF epidemiology, and highlighted that theoretical and applied models are used differently yet meet common objectives. Through the examination of model features, we identified research questions left unexplored across scales, such as the role of animal mobility, as well as the relative contributions of host and vector species to transmission. Importantly, we noted a substantial lack of justification when choosing a functional form for the force of infection. Overall, we showed a great diversity in RVF models, leading to important progress in our comprehension of epidemiological mechanisms. To go further, data gaps must be filled, and modelers need to improve their code accessibility.

Mots-clés Agrovoc : épidémiologie, transmission des maladies, Virus de la fièvre de la vallée du Rift, zoonose, surveillance épidémiologique, modélisation, modèle mathématique

Mots-clés libres : Rift valley fever, Modelling, Transmission, Review

Classification Agris : L73 - Maladies des animaux
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

Agences de financement hors UE : Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Conseil Régional des Pays de la Loire, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Ministère de l'Agriculture et de l'Alimentation

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