The potential of remote sensing for improved infectious disease ecology research and practice
Proceedings of the Royal Society B: Biological Sciences
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Abstract
Outbreaks of Covid-19 in humans, Dutch elm disease in forests, and highly pathogenic avian influenza in wild birds and poultry highlight the disruptive impacts of emerging infectious diseases on public health, ecosystems, and economies. Infectious disease dynamics often depend on environmental conditions that drive occurrence, transmission, and outbreaks. Remote sensing can contribute to infectious disease research and management by providing standardized environmental data across broad spatial and temporal extents, often at no cost to the user. Here, we 1) conduct a systematic review of primary literature to quantify current uses of remote sensing in disease ecology and 2) synthesize qualitative information to identify opportunities for further integration of remote sensing into disease ecology. We identify that modern advances in airborne remote sensing are promoting early detection of forest pathogens and that satellite data is contributing to the study of geographically widespread human diseases. We discuss opportunities for increased use of data products that characterize vegetation, surface water, and soil; provide data at high spatio-temporal and spectral resolutions; and quantify uncertainty in measurements. Additionally, combining remote sensing with animal movement telemetry can provide novel insights into wildlife disease. Integrating these opportunities will advance research and management of infectious diseases.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | The potential of remote sensing for improved infectious disease ecology research and practice |
| Series title | Proceedings of the Royal Society B: Biological Sciences |
| DOI | 10.1098/rspb.2024.1712 |
| Volume | 291 |
| Year Published | 2024 |
| Language | English |
| Publisher | The Royal Society Publishing |
| Contributing office(s) | Western Ecological Research Center |
| Description | 20241712, 12 p. |
| Google Analytic Metrics | Metrics page |