Impacts of biodiversity on the emergence and transmission of infectious diseases
Open accessAbstract
Current unprecedented declines in biodiversity reduce the ability of ecological communities to provide many fundamental ecosystem services. Here we evaluate evidence that reduced biodiversity affects the transmission of infectious diseases of humans, other animals and plants. In principle, loss of biodiversity could either increase or decrease disease transmission. However, mounting evidence indicates that biodiversity loss frequently increases disease transmission. In contrast, areas of naturally high biodiversity may serve as a source pool for new pathogens. Overall, despite many remaining questions, current evidence indicates that preserving intact ecosystems and their endemic biodiversity should generally reduce the prevalence of infectious diseases.
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Under some conditions, high biological diversity can decrease the transmission of zoonotic diseases that have already become established.
“But for decades, we have also known that under some conditions, high biological diversity can decrease the transmission of zoonotic diseases that have already become established (8, 9).”
From Impacts of biodiversity and biodiversity loss on zoonotic diseases (2021) · cites this paper as [8]
Human impacts like land-use change have been linked to emerging infectious diseases of humans in many studies.
“Human impacts like land-use change have been linked to emerging infectious diseases of humans in many studies (e.g., refs. 5, 8, 29, 38, and 39).”
From Impacts of biodiversity and biodiversity loss on zoonotic diseases (2021) · cites this paper as [8]
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Biodiversity Can Help Prevent Malaria Outbreaks in Tropical Forests
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- Authors
- Keesing, F., Belden, L. K., Daszak, P., Dobson, A., Harvell, C. D., Holt, R. D., Hudson, P., Jolles, A., Jones, K. E., Mitchell, C. E., Myers, S. S., Bogich, T., & Ostfeld, R. S.
- Affiliations
- Bard College (US)
- Virginia Tech (US)
- EcoHealth Alliance (US)
- Princeton University (US)
- Cornell University (US)
- University of Florida (US)
- Pennsylvania State University (US)
- Oregon State University (US)
- Zoological Society of London (GB)
- University of North Carolina at Chapel Hill (US)
- Harvard University (US)
- Cary Institute of Ecosystem Studies (US)
- Corresponding author
- Keesing, Felicia
- ORCID
- Venue
- Nature
- Published
- 2010-12-01
- Volume
- 468
- Issue
- 7324
- Pages
- 647-652
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC7094913
- OpenAlex
- W2037309013
- Semantic Scholar
- 547770e6d841c9cecd1c7cb99620ff50586ec726
- Cited by
- 2,043
- References
- 75
- Citations by year
- 2026: 83 · 2025: 127 · 2024: 136 · 2023: 156 · 2022: 166 · 2021: 245 · 2020: 170 · 2019: 120 · 2018: 103 · 2017: 100 · 2016: 89 · 2015: 120 · 2014: 111 · 2013: 129 · 2012: 113
- FWCI
- 14.53
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- National Science Foundation
- National Institutes of Health
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Zoonotic diseases and public health
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
- Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
- Keywords
- biodiversity loss, infectious disease transmission, emerging infectious diseases, disease emergence, biodiversity conservation, ecosystem services, host-pathogen interaction, vectors, plant pathogens, zoonoses, endemic biodiversity
- MeSH terms
- Animals, Communicable Diseases, Orthohantavirus, Humans, Lyme Disease, Species Specificity, Zoonoses, Communicable Diseases, Emerging, Biodiversity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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