Wild animals encounter a wide range of threats, some of which pose risks to human and domestic animal health and our shared environment. Our team developed an early detection surveillance system for wildlife that helps identify unusual patterns of illness and death in near real-time by assimilating data from wildlife rehabilitation organizations across California. As frontline responders for injured and sick wild animals, wildlife rehabilitators are the first to receive and care for wildlife.
CHALLENGE: Their medical records hold valuable information that, when compiled and shared, aid in detecting unusual patterns and timely response to emerging health threats. Because wildlife morbidity and mortality events can indicate ecological disturbances, data generated through these organizations also provide valuable early warnings for ecosystem-wide threats including local pollution, climate change, invasive species, and emerging infectious diseases.
SOLUTION: So, our team developed a first-of-its-kind early detection surveillance system that helps identify unusual patterns of illness and death in near real-time by assimilating data from wildlife rehabilitation organizations across California.
Check the WIRED article featuring our system here: This AI Helps Detect Wildlife Health Issues in Real Time
HOW IT WORKS: This system, the Wildlife Morbidity and Mortality Event Alert System (WMMEAS), which was developed in collaboration with the Wild Neighbors Database Project, California Department of Fish and Wildlife, and a network of wildlife rehabilitation organizations is the first of its kind, to facilitate real-time monitoring of threats with the potential to be scaled nationally and globally. It has already proven useful in the early detection of both common and emerging disease threats in California wildlife, facilitating important investigation and response efforts.
The system aggregates data from a wide diversity of species. From 2013-2018, 453 unique species were represented in the system.
Songbirds make up a large portion of the caseload admitted to the rehabilitation organization network with several birds presenting with injuries/illness resulting from human activities.
WMMEAS dashboard displaying data for songbirds admitted as a result of eye disease. The system will alert the user if an outbreak associated with eye disease is detected in songbirds.
The system is innovative in that it uses natural language processing and machine learning methods to classify cases and generate automatic alerts when anomalies are detected across the network, providing an efficient and cost-effective tool for wildlife disease surveillance. Funds raised through this campaign will be used to develop a more sophisticated anomaly detection algorithm that will allow for higher accuracy in detection and to provide open access to the system’s online dashboard where users can query and visualize trends in wildlife morbidity and mortality events and sign up to receive alerts to wildlife health anomalies.
Any donation amount is greatly appreciated and will go directly to early detection and response efforts. By providing a gift, you are contributing to the health and conservation of our wildlife.