Suppr超能文献

人兽界面新兴病原体监测框架:以猪和冠状病毒为例。

A framework for surveillance of emerging pathogens at the human-animal interface: Pigs and coronaviruses as a case study.

机构信息

National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, 4101 Laporte Ave., Fort Collins, CO, 80526, United States.

Centers for Epidemiology and Animal Health, Veterinary Services, Animal and Plant Health Inspection Service, United States Department of Agriculture, 2150 Center Ave., Fort Collins, CO, 80526, United States.

出版信息

Prev Vet Med. 2021 Mar;188:105281. doi: 10.1016/j.prevetmed.2021.105281. Epub 2021 Jan 27.

Abstract

Pigs (Sus scrofa) may be important surveillance targets for risk assessment and risk-based control planning against emerging zoonoses. Pigs have high contact rates with humans and other animals, transmit similar pathogens as humans including CoVs, and serve as reservoirs and intermediate hosts for notable human pandemics. Wild and domestic pigs both interface with humans and each other but have unique ecologies that demand different surveillance strategies. Three fundamental questions shape any surveillance program: where, when, and how can surveillance be conducted to optimize the surveillance objective? Using theory of mechanisms of zoonotic spillover and data on risk factors, we propose a framework for determining where surveillance might begin initially to maximize a detection in each host species at their interface. We illustrate the utility of the framework using data from the United States. We then discuss variables to consider in refining when and how to conduct surveillance. Recent advances in accounting for opportunistic sampling designs and in translating serology samples into infection times provide promising directions for extracting spatio-temporal estimates of disease risk from typical surveillance data. Such robust estimates of population-level disease risk allow surveillance plans to be updated in space and time based on new information (adaptive surveillance) thus optimizing allocation of surveillance resources to maximize the quality of risk assessment insight.

摘要

猪(Sus scrofa)可能是对新兴人畜共患病进行风险评估和基于风险的控制规划的重要监测目标。猪与人类和其他动物的接触率很高,传播与人类相似的病原体,包括 CoV,并作为重要的人类大流行的储存宿主和中间宿主。野生和家养猪都与人类和彼此相互作用,但具有独特的生态,需要不同的监测策略。三个基本问题塑造了任何监测计划:在哪里、何时以及如何进行监测才能优化监测目标?利用人畜共患病溢出机制理论和风险因素数据,我们提出了一个框架,用于确定在哪里可以开始初始监测,以最大限度地提高每个宿主物种在其界面上的检测率。我们使用来自美国的数据说明了该框架的实用性。然后,我们讨论了在何时以及如何进行监测时需要考虑的变量。最近在机会抽样设计和将血清学样本转化为感染时间方面的进展为从典型监测数据中提取疾病风险的时空估计提供了有希望的方向。这种对人群疾病风险的稳健估计允许根据新信息(适应性监测)在空间和时间上更新监测计划,从而优化监测资源的分配,以最大限度地提高风险评估洞察力的质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/76c9/7839430/804b98ab9f5e/gr1_lrg.jpg

相似文献

1
A framework for surveillance of emerging pathogens at the human-animal interface: Pigs and coronaviruses as a case study.
Prev Vet Med. 2021 Mar;188:105281. doi: 10.1016/j.prevetmed.2021.105281. Epub 2021 Jan 27.
4
Deadly pig virus slips through US borders.
Nature. 2013 Jul 25;499(7459):388. doi: 10.1038/499388a.
6
Prioritization of zoonotic viral diseases in feral pigs, domestic pigs and humans interface.
Biomedica. 2015 Dec 4;36(0):56-68. doi: 10.7705/biomedica.v36i0.2950.
8
The problem of scale in the prediction and management of pathogen spillover.
Philos Trans R Soc Lond B Biol Sci. 2019 Sep 30;374(1782):20190224. doi: 10.1098/rstb.2019.0224. Epub 2019 Aug 12.
9
Adaptive risk-based targeted surveillance for foreign animal diseases at the wildlife-livestock interface.
Transbound Emerg Dis. 2022 Sep;69(5):e2329-e2340. doi: 10.1111/tbed.14576. Epub 2022 May 10.
10
Leveraging natural history biorepositories as a global, decentralized, pathogen surveillance network.
PLoS Pathog. 2021 Jun 3;17(6):e1009583. doi: 10.1371/journal.ppat.1009583. eCollection 2021 Jun.

引用本文的文献

1
Surveillance Analysis and Sample Size Explorer (SASSE): Learning How to Plan Disease Surveillance in Wildlife.
Ecol Evol. 2025 Aug 15;15(8):e71991. doi: 10.1002/ece3.71991. eCollection 2025 Aug.
2
Landscape-Scale Epidemiological Dynamics of SARS-CoV-2 in White-Tailed Deer.
Transbound Emerg Dis. 2024 Feb 10;2024:7589509. doi: 10.1155/2024/7589509. eCollection 2024.
3
Risk of African swine fever virus transmission among wild boar and domestic pigs in Poland.
Front Vet Sci. 2023 Nov 6;10:1295127. doi: 10.3389/fvets.2023.1295127. eCollection 2023.
5
Adaptive risk-based targeted surveillance for foreign animal diseases at the wildlife-livestock interface.
Transbound Emerg Dis. 2022 Sep;69(5):e2329-e2340. doi: 10.1111/tbed.14576. Epub 2022 May 10.
6
A pan-coronavirus RT-PCR assay for rapid viral screening of animal, human, and environmental specimens.
One Health. 2021 Dec;13:100274. doi: 10.1016/j.onehlt.2021.100274. Epub 2021 Jun 6.

本文引用的文献

2
The Potential Intermediate Hosts for SARS-CoV-2.
Front Microbiol. 2020 Sep 30;11:580137. doi: 10.3389/fmicb.2020.580137. eCollection 2020.
3
Swine acute diarrhea syndrome coronavirus replication in primary human cells reveals potential susceptibility to infection.
Proc Natl Acad Sci U S A. 2020 Oct 27;117(43):26915-26925. doi: 10.1073/pnas.2001046117. Epub 2020 Oct 12.
4
Susceptibility of swine cells and domestic pigs to SARS-CoV-2.
Emerg Microbes Infect. 2020 Dec;9(1):2278-2288. doi: 10.1080/22221751.2020.1831405.
5
Emergence of SARS-CoV-2 through recombination and strong purifying selection.
Sci Adv. 2020 Jul 1;6(27). doi: 10.1126/sciadv.abb9153. Print 2020 Jul.
6
Possibility for reverse zoonotic transmission of SARS-CoV-2 to free-ranging wildlife: A case study of bats.
PLoS Pathog. 2020 Sep 3;16(9):e1008758. doi: 10.1371/journal.ppat.1008758. eCollection 2020 Sep.
7
Broad host range of SARS-CoV-2 predicted by comparative and structural analysis of ACE2 in vertebrates.
Proc Natl Acad Sci U S A. 2020 Sep 8;117(36):22311-22322. doi: 10.1073/pnas.2010146117. Epub 2020 Aug 21.
8
SARS-CoV-2 infection in farmed minks, the Netherlands, April and May 2020.
Euro Surveill. 2020 Jun;25(23). doi: 10.2807/1560-7917.ES.2020.25.23.2001005.
10
An open source tool to infer epidemiological and immunological dynamics from serological data: serosolver.
PLoS Comput Biol. 2020 May 4;16(5):e1007840. doi: 10.1371/journal.pcbi.1007840. eCollection 2020 May.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验