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

Hélène Cecilia (1, 2) , Alex Drouin (3, 4) , Raphaëlle Métras (5, 6) , Thomas Balenghien (3, 7, 8) , Benoit Durand (4) , Véronique Chevalier (3, 7, 9) , Pauline Ezanno (1)

1 BIOEPAR - Biologie, Epidémiologie et analyse de risque en Santé Animale
2 ONIRIS - École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique
3 UMR ASTRE - Animal, Santé, Territoires, Risques et Ecosystèmes
4 EPI - Epidémiologie
5 SUMO - Surveillance et modélisation des maladies transmissibles [iPLesp]
6 LSHTM - London School of Hygiene and Tropical Medicine
7 Cirad-BIOS - Département Systèmes Biologiques
8 IAV Hassan II - Institut Agronomique et Vétérinaire Hassan II
9 Institut Pasteur de Madagascar

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: Rift Valley Fever; Rift Valley Fever Virus; Arbovirosis; Africa; Epidemiology

Domaines: Maladies infectieuses; Mathématiques [math]; Médecine vétérinaire et santé animale; Maladies émergentes; Santé publique et épidémiologie

Hélène Cecilia, Alex Drouin, Raphaëlle Métras, Thomas Balenghien, Benoit Durand, et al.. Mechanistic models of Rift Valley fever virus transmission: A systematic review. PLoS Neglected Tropical Diseases, 2022, 16 (11), pp.e0010339. ⟨10.1371/journal.pntd.0010339⟩. ⟨hal-03886982⟩