ReviewProceedings. Biological sciences2024
The potential of remote sensing for improved infectious disease ecology research and practice.
Review in Proceedings. Biological sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- GIS-based neural network framework for zoonotic cutaneous leishmaniasis risk mapping in Western Iran.Environmental monitoring and assessment · 2026Article
- Forecasting Influenza Epidemics and Pandemics in the Age of AI and Machine Learning.Reviews in medical virology · 2026Review
- Upscaling effects on infectious disease emergence risk emphasize the need for local planning in primary prevention within biodiversity hotspots.Scientific reports · 2025Article
- The Challenge of Lyssavirus Infections in Domestic and Other Animals: A Mix of Virological Confusion, Consternation, Chagrin, and Curiosity.Pathogens (Basel, Switzerland) · 2025Review
- Closing the air gap: the use of drones for studying wildlife ecophysiology.Biological reviews of the Cambridge Philosophical Society · 2025Review
- Wildlife hunting and the increased risk of leprosy transmission in the tropical Americas: a pathogeographical study.Infectious diseases of poverty · 2025Article
- Advance Warning and Response Systems in Kenya: A Scoping Review.medRxiv : the preprint server for health sciences · 2025Article
- The potential of remote sensing for improved infectious disease ecology research and practice.Proceedings. Biological sciences · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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 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 (i) conduct a review of primary literature to quantify current uses of remote sensing in disease ecology; and (ii) 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 enabling early detection of forest pathogens and that satellite data are most commonly used to study geographically widespread human diseases. Opportunities remain 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 telemetry can support decision-making for disease management by providing insights into wildlife disease dynamics. Integrating these opportunities will advance both research and management of infectious diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.