Emerging infectious diseases continue to pose a significant burden on global public health, and there is a critical need to better understand transmission dynamics arising at the interface of human activity and wildlife habitats. Passive acoustic monitoring (PAM), more typically applied to questions of biodiversity and conservation, provides an opportunity to collect and analyse audio data in relative real time and at low cost. Acoustic methods are increasingly accessible, with the expansion of cloud-based computing, low-cost hardware, and machine learning approaches. Paired with purposeful experimental design, acoustic data can complement existing surveillance methods and provide a novel toolkit to investigate the key biological parameters and ecological interactions that underpin infectious disease epidemiology.
Highlights
- Passive acoustic monitoring (PAM) provides new opportunities to characterise zoonotic and vector-borne disease dynamics in changing landscapes.
- Acoustic data can inform our understanding of variables that drive transmission risk, including human and wildlife occupancy over space and time and changes in habitat quality.
- With low-cost hardware, cloud-based computing, and open-source platforms, acoustic data collection and analysis methods are increasingly accessible to nonspecialist users.
- Key considerations for epidemiologists include the availability of complementary data sources and the technical requirements for acoustic data storage and analysis.
- Acoustic monitoring is a cost-effective, noninvasive tool which could be effectively combined with existing data to strengthen early warning systems and integrated disease surveillance.