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Mechanistic models of Rift Valley fever virus transmission: A systematic review.
Cecilia, Hélène; Drouin, Alex; Métras, Raphaëlle; Balenghien, Thomas; Durand, Benoit; Chevalier, Véronique; Ezanno, Pauline.
Afiliação
  • Cecilia H; Oniris, INRAE, BIOEPAR, Nantes, France.
  • Drouin A; ASTRE, University of Montpellier, CIRAD, INRAE, Montpellier, France.
  • Métras R; Université Paris-Est, Anses, Laboratory for Animal Health, Epidemiology Unit, Maisons-Alfort, France.
  • Balenghien T; Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP, UMRS 1136), Paris, France.
  • Durand B; Department of Infectious Disease Epidemiology, Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Chevalier V; ASTRE, University of Montpellier, CIRAD, INRAE, Montpellier, France.
  • Ezanno P; CIRAD, UMR ASTRE, Rabat, Morocco.
PLoS Negl Trop Dis ; 16(11): e0010339, 2022 11.
Article em En | MEDLINE | ID: mdl-36399500
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Febre do Vale de Rift / Vírus da Febre do Vale do Rift Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Febre do Vale de Rift / Vírus da Febre do Vale do Rift Idioma: En Ano de publicação: 2022 Tipo de documento: Article