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A semi-quantitative model for ranking the risk of incursion of exotic animal pathogens into a European Union Member State
Microbial Risk Analysis ; : 100175, 2021.
Article in English | ScienceDirect | ID: covidwho-1267338
ABSTRACT
Risk ranking tools to prioritise the impact of exotic animal diseases in a country or area are useful to assist risk managers in optimising the allocation of available resources for the prevention and control of infectious diseases. Although several such tools have already been developed, few focus on the probability of entry of an exotic pathogen into a territory and even fewer are able to rank multiple pathogens at the same time. We developed a semi-quantitative multi-criteria model to estimate the probability of incursion of an exotic pathogen into a European country and use Italy as a case study. We consider the import of 37 animal diseases of importance to Italy, based on OIE notification guidelines, and determine a disease status around the world based on current country-level reporting to the OIE. We identify seven possible pathways for the introduction of a pathogen and for each of them we determine a scoring system to assess for each disease the probability of introduction via each pathway. These scores, alongside the disease status, are used to calculate an overall risk score for each pathogen. The results indicate that the risk of incursion of Echinococcus multilocularis, African swine fever virus, Trichinella sp., lumpy skin disease and foot and mouth disease virus are ranked the highest. Additional analyses identified that the disease ranking is sensitive to the relative importance of the pathways of entry and also the impact of potential mitigation measures. The model is designed to be periodically updated with new data as they become available, e.g. global disease prevalence and trade volume. Therefore, it can be used by official authorities on a regular basis to obtain up-to-date results and consequentially strengthen surveillance towards those pathogens with the highest probability of entry.

Full text: Available Collection: Databases of international organizations Database: ScienceDirect Type of study: Prognostic study Language: English Journal: Microbial Risk Analysis Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Type of study: Prognostic study Language: English Journal: Microbial Risk Analysis Year: 2021 Document Type: Article