Prioritizing emerging zoonoses in the Netherlands

Area of Science:

• Veterinary epidemiology
• Public health
• Risk assessment

Background:

• Emerging zoonotic diseases pose a significant threat to public health.
• Effective early warning and surveillance systems are crucial for managing zoonoses.
• A quantitative, multi-criteria model can aid in prioritizing pathogens for surveillance.

Purpose of the Study:

• To develop and apply a generalizable quantitative, stochastic multi-criteria model.
• To prioritize zoonotic pathogens for surveillance and early warning systems in the Netherlands.

Main Methods:

• A quantitative, stochastic multi-criteria model was developed.
• Seven criteria were used to assess pathogen risk, including epidemiology and societal impact.
• A panel of experts weighted the criteria based on their preferences.

Main Results:

• The model generated a risk score for various zoonotic pathogens.
• Pathogens identified as high-risk include Campylobacter spp., Toxoplasma gondii, Coxiella burnetii, Mycobacterium bovis, BSE prion, Capnocytophaga canimorsus, Japanese encephalitis virus, and West-Nile virus.
• These pathogens represent diverse sources, including livestock, domestic animals, and wildlife.

Conclusions:

• The developed model effectively prioritizes zoonotic pathogens for surveillance in the Netherlands.
• Key target pathogens for early warning systems were identified.
• This approach supports proactive public health strategies against emerging zoonoses.