Using wild-animal tracking for detecting and managing disease outbreaks

Area of Science:

• Ecology
• Epidemiology
• Conservation Biology

Background:

• Zoonotic diseases pose increasing threats to human and wildlife health, evidenced by widespread outbreaks like avian influenza and COVID-19.
• Global mass-mortality events highlight the urgent need for advanced disease detection and management strategies.

Purpose of the Study:

• To introduce a general framework for early detection and management of pathogen outbreaks.
• To integrate animal movement and sensory biologging data with disease surveillance.

Main Methods:

• Utilizing animal movement and sensory biologging data for early outbreak detection.
• Providing near-real-time updates on sentinel host health and mortality.
• Analyzing infection-induced behavioral changes in animal populations.

Main Results:

• The framework enables enhanced early outbreak detection and near-real-time monitoring of sentinel hosts.
• Integration of biologging and surveillance data allows for prospective spatiotemporal outbreak assessments.
• Identified infection-induced behavioral changes provide insights into disease dynamics.

Conclusions:

• The proposed framework supports improved management decisions for disease control and wildlife conservation.
• It helps mitigate zoonotic spillover risks by providing timely and actionable data.
• This integrated approach offers a powerful tool for addressing global health security challenges.