ArticleVeterinary research2015
Ecological approaches in veterinary epidemiology: mapping the risk of bat-borne rabies using vegetation indices and night-time light satellite imagery.
Article in Veterinary research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
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Who cites it
11 citing papers in PubMed, 27 citations in OpenAlex.
- Patterns of Animal Rabies Prevalence in Northern South Africa between 1998 and 2022.Tropical medicine and infectious disease · 2024Article
- An integrated system for the management of environmental data to support veterinary epidemiology.Frontiers in veterinary science · 2023Article
- Incidence of dog bite injuries and its associated factors in Punjab province of Pakistan.Science in One Health · 2022Article
- The Potential Distribution ofFrontiers in veterinary science · 2021Article
- Modeling the Potential Distribution of the Malaria VectorFrontiers in public health · 2021Article
- Applying species distribution models in public health research by predicting snakebite risk using venomous snakes' habitat suitability as an indicating factor.Scientific reports · 2020Article
- Collinearity in ecological niche modeling: Confusions and challenges.Ecology and evolution · 2019Article
- Assessing changing weather and the El Niño Southern Oscillation impacts on cattle rabies outbreaks and mortality in Costa Rica (1985-2016).BMC veterinary research · 2018Article
- Detection of potentially novel paramyxovirus and coronavirus viral RNA in bats and rats in the Mekong Delta region of southern Viet Nam.Zoonoses and public health · 2018Article
- Ecological niche modeling of rabies in the changing Arctic of Alaska.Acta veterinaria Scandinavica · 2017Article
- Advances and Limitations of Disease Biogeography Using Ecological Niche Modeling.Frontiers in microbiology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rabies remains a disease of significant public health concern. In the Americas, bats are an important source of rabies for pets, livestock, and humans. For effective rabies control and prevention, identifying potential areas for disease occurrence is critical to guide future research, inform public health policies, and design interventions. To anticipate zoonotic infectious diseases distribution at coarse scale, veterinary epidemiology needs to advance via exploring current geographic ecology tools and data using a biological approach. We analyzed bat-borne rabies reports in Chile from 2002 to 2012 to establish associations between rabies occurrence and environmental factors to generate an ecological niche model (ENM). The main rabies reservoir in Chile is the bat species Tadarida brasiliensis; we mapped 726 occurrences of rabies virus variant AgV4 in this bat species and integrated them with contemporary Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The correct prediction of areas with rabies in bats and the reliable anticipation of human rabies in our study illustrate the usefulness of ENM for mapping rabies and other zoonotic pathogens. Additionally, we highlight critical issues with selection of environmental variables, methods for model validation, and consideration of sampling bias. Indeed, models with weak or incorrect validation approaches should be interpreted with caution. In conclusion, ecological niche modeling applications for mapping disease risk at coarse geographic scales have a promising future, especially with refinement and enrichment of models with additional information, such as night-time light data, which increased substantially the model's ability to anticipate human rabies.
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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.