How mechanistic modelling supports decision making for the control of enzootic infectious diseases

• Published in: Epidemics Vol. 32; p. 100398
• Main Authors: Ezanno, P., Andraud, M., Beaunée, G., Hoch, T., Krebs, S., Rault, A., Touzeau, S., Vergu, E., Widgren, S.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.09.2020; Elsevier
• Subjects: Agriculture - methods; Animal Diseases - epidemiology; Animal Diseases - prevention & control; Animal Diseases - therapy; Animals; Communicable Diseases - epidemiology; Communicable Diseases - transmission; Computer Science; Data; Decision Making; Epidemiological model; Health economics; Humans; Interdisciplinarity; Livestock; Modeling and Simulation; Models, Theoretical; Multiscale; Interdisciplinarity; Livestock; Data; Health economics; Multiscale; Epidemiological model
• ISSN: 1755-4365; 1878-0067
• DOI: 10.1016/j.epidem.2020.100398

[Display omitted] •Multiscale mechanistic models help understanding the spread of enzootic pathogens.•Interdisciplinarity is key in building epidemiological models for enzootics.•Territorial anchorage, fed by field data, ensures prediction realism and robustness.•Model complexity should be balanced by affordable data.•Economic and epidemiological models should be coupled for unregulated enzootics. Controlling enzootic diseases, which generate a large cumulative burden and are often unregulated, is needed for sustainable farming, competitive agri-food chains, and veterinary public health. We discuss the benefits and challenges of mechanistic epidemiological modelling for livestock enzootics, with particular emphasis on the need for interdisciplinary approaches. We focus on issues arising when modelling pathogen spread at various scales (from farm to the region) to better assess disease control and propose targeted options. We discuss in particular the inclusion of farmers’ strategic decision-making, the integration of within-host scale to refine intervention targeting, and the need to ground models on data.