United States Department of Agriculture: Animal and Plant Health Inspection Service
United States Department of Agriculture Wildlife Services: Staff Publications
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ORCID IDs
Hewitt https://orcid.org/0000-0002-0844-7769
Wilson-Henjum https://orcid.org/0000-0002-2284-8745
Collins https://orcid.org/0000-0002-3723-2353
Linder https://orcid.org/0000-0003-3440-0574
Lenoch https://orcid.org/0000-0002-3995-8895
Quintanal https://orcid.org/0000-0003-0687-0528
Pleszewski https://orcid.org/0000-0003-1481-0242
McBride https://orcid.org/0000-0002-7408-3959
Bowman https://orcid.org/0000-0002-0738-8453
Chandler https://orcid.org/0000-0002-3318-135X
Shriner https://orcid.org/0000-0003-0349-7182
Bevins https://orcid.org/0000-0002-4999-6836
Kohler https://orcid.org/0000-0001-6712-505X
Chipman https://orcid.org/0000-0002-4145-678X
Bergman https://orcid.org/0000-0002-6757-643X
DeLiberto https://orcid.org/0000-0003-1115-1472
Pepin https://orcid.org/0000-0002-9931-8312
Document Type
Article
Date of this Version
2024
Citation
Transboundary and Emerging Diseases (2024) 2024: 7589509, 11 pages
doi: 10.1155/2024/7589509
Academic editor: Shao-Lun Zhai
Abstract
Understanding pathogen emergence in new host species is fundamental for developing prevention and response plans for human and animal health. We leveraged a large-scale surveillance dataset coordinated by United States Department of Agriculture, Animal and Plant Health Inspection Service and State Natural Resources Agencies to quantify the outbreak dynamics of SARS-CoV-2 in North American white-tailed deer (Odocoileus virginianus; WTD) throughout its range in the United States. Local epidemics in WTD were well approximated by a single-outbreak peak followed by fade out. Outbreaks peaked early in the northeast and mid- Atlantic. Local effective reproduction ratios of SARS-CoV-2 were between 1 and 2.5. Ten percent of variability in peak prevalence was explained by human infection pressure. This, together with the similar peak infection prevalence times across many counties and single-peak outbreak dynamics followed by fade out, suggest that widespread transmission via human-to-deer spillover may have been an important driver of the patterns and persistence. We provide a framework for inferring population-level epidemiological processes through joint analysis of many sparsely observed local outbreaks (landscape-scale surveillance data) and linking epidemiological parameters to ecological risk factors. The framework combines mechanistic and statistical models that can identify and track local outbreaks in long-term infection surveillance monitoring data.
Included in
Natural Resources and Conservation Commons, Natural Resources Management and Policy Commons, Other Environmental Sciences Commons, Other Veterinary Medicine Commons, Population Biology Commons, Terrestrial and Aquatic Ecology Commons, Veterinary Infectious Diseases Commons, Veterinary Microbiology and Immunobiology Commons, Veterinary Preventive Medicine, Epidemiology, and Public Health Commons, Zoology Commons
Comments
United States government work