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白尾鹿中新冠病毒的景观尺度流行病学动态

Landscape-Scale Epidemiological Dynamics of SARS-CoV-2 in White-Tailed Deer.

作者信息

Hewitt Joshua, Wilson-Henjum Grete, Collins Derek T, Linder Timothy J, Lenoch Julianna B, Heale Jonathon D, Quintanal Christopher A, Pleszewski Robert, McBride Dillon S, Bowman Andrew S, Chandler Jeffrey C, Shriner Susan A, Bevins Sarah N, Kohler Dennis J, Chipman Richard B, Gosser Allen L, Bergman David L, DeLiberto Thomas J, Pepin Kim M

机构信息

Department of Wildland Resources, Utah State University, Logan, UT, USA.

National Wildlife Disease Program, United States Department of Agriculture, Fort Collins, CO, USA.

出版信息

Transbound Emerg Dis. 2024 Feb 10;2024:7589509. doi: 10.1155/2024/7589509. eCollection 2024.

DOI:10.1155/2024/7589509
PMID:40303065
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12017121/
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 (; 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.

摘要

了解病原体在新宿主物种中的出现情况对于制定人类和动物健康的预防及应对计划至关重要。我们利用了由美国农业部动植物卫生检验局和州自然资源机构协调的大规模监测数据集,以量化严重急性呼吸综合征冠状病毒2(SARS-CoV-2)在美国全境北美白尾鹿(WTD)中的暴发动态。WTD中的局部疫情可以很好地用单一暴发高峰随后消退来近似。疫情在东北部和大西洋中部地区早期达到高峰。SARS-CoV-2的局部有效繁殖率在1至2.5之间。峰值流行率10%的变异性可由人类感染压力解释。这一点,再加上许多县的峰值感染流行时间相似以及单一高峰暴发动态随后消退,表明通过人传鹿溢出的广泛传播可能是这些模式和持续性的一个重要驱动因素。我们提供了一个框架,通过对许多稀疏观察到的局部暴发(景观尺度监测数据)进行联合分析,并将流行病学参数与生态风险因素联系起来,来推断种群水平的流行病学过程。该框架结合了机制模型和统计模型,能够在长期感染监测数据中识别和跟踪局部暴发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/513dcb357f48/TBED2024-7589509.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/f39d9efbef62/TBED2024-7589509.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/a89dcb1ec33d/TBED2024-7589509.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/13c2e12d29ee/TBED2024-7589509.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/4eda257f901e/TBED2024-7589509.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/513dcb357f48/TBED2024-7589509.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/f39d9efbef62/TBED2024-7589509.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/a89dcb1ec33d/TBED2024-7589509.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/13c2e12d29ee/TBED2024-7589509.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/4eda257f901e/TBED2024-7589509.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfea/12017121/513dcb357f48/TBED2024-7589509.005.jpg

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