Article
Details
Citation
Bate AM, Jones G, Kleczkowski A & Touza J (2021) Modelling the effectiveness of collaborative schemes for disease and pest outbreak prevention. Ecological Modelling, 442, Art. No.: 109411. https://doi.org/10.1016/j.ecolmodel.2020.109411
Abstract
Preventing disease outbreaks has widespread benefits that are dependent on the actions of many agents but can be undermined by the inaction of others. This paper explores whether a voluntary biosecurity-related assurance scheme can be an effective mechanism for curbing the risks of animal and plant pests and diseases. The decision to engage in such schemes is modelled using a coalition game where agents consider both direct costs of infection and regional outbreak costs like trade bans and movement restrictions. We find that government needs to support the scheme through incentives that reduce members’ outbreak costs like pre-agreed outbreak compensation or preferential regulatory treatment. Assurance schemes could provide significant improvements in biosecurity if membership is high; but without government incentives, stable coalitions are either small or ineffective at improving biosecurity. Government support can lead to large coalitions and robust improvement in overall biosecurity, with the optimal level of support being the smallest incentive that leads to a stable grand coalition. Policies that focus on either monetary or non-monetary incentives can lead to more robust improvements in biosecurity. In particular, targeting regional outbreak costs to members like movement restrictions leads to improved biosecurity for all levels of support.
Keywords
Animal health; Biosecurity; Coalition game; Disease control; Disease prevention; Plant health
Journal
Ecological Modelling: Volume 442
Status | Published |
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Funders | National Science Foundation and Biotechnology and Biological Sciences Research Council |
Publication date | 15/02/2021 |
Publication date online | 13/01/2021 |
Date accepted by journal | 03/12/2020 |
Publisher | Elsevier BV |
ISSN | 0304-3800 |