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Risk prioritization as a tool to Guide Veterinary Public Health activities at the regional level in Italy

Keywords

Public health
Animal diseases
Infectious diseases
Zoonosis
Risk prioritization
Food safety

How to Cite

Zecconi, A., Scali, F., Bonizzi, L., Ferrari, N., Ferrero, F., Grillo, G., Lanfranchi, P., Mortarino, M., Sala, V., Taloni, D., & Frazzi, P. (2019). Risk prioritization as a tool to Guide Veterinary Public Health activities at the regional level in Italy. Veterinaria Italiana, 55(2), 113–121. https://doi.org/10.12834/VetIt.172.518.2

Abstract

In this study we developed a model for risk prioritisation and characterisation focused on zoonoses and food safety for diseases of interest in veterinary public health at a regional level in Italy. A previous model (Discontools) based on scorecards was used as a basis to develop the new model. A Formalised Consensus Process approach involving academics and veterinary officers was used to develop scorecards and relative form and guidelines. Scorecards include several areas of interest, with different categories and coefficient of importance. The following areas were identified: relevance of the disease, socio-economic impact, impact on public health, impact on trade, impact on animal welfare, control tools. A guide and a form were finalised in order to fill scorecards. Scorecards were filled by consulting available data, literature, and expert opinions. Among bovine diseases, mastitis (Salmonella aureus) showed the highest score; Q fever was the highest among small ruminants; among swine diseases the highest was salmonellosis; while among other animal diseases, toxoplasmosis had the highest score. The approach described in this study is designed to aid professionals in risk prioritisation, decision-making, and to improve disease control systems at a regional level in Italy. It also facilitates risk characterisation in different backgrounds and the identification of data holes in specific areas of interest for the diseases considered. This approach is conceived to aid professionals in risk prioritization, decision-making and to improve disease control systems at a regional level. It also allows to perform risk characterization in different backgrounds and to identify lacks of data in specific areas of interest for the diseases considered.

https://doi.org/10.12834/VetIt.172.518.2

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