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2019年美国东北部疫情期间东部马脑炎病毒的动态变化

Dynamics of Eastern equine encephalitis virus during the 2019 outbreak in the Northeast United States.

作者信息

Hill Verity, Koch Robert T, Bialosuknia Sean M, Ngo Kiet, Zink Steven D, Koetzner Cheri A, Maffei Joseph G, Dupuis Alan P, Backenson P Bryon, Oliver JoAnne, Bransfield Angela B, Misencik Michael J, Petruff Tanya A, Shepard John J, Warren Joshua L, Gill Mandev S, Baele Guy, Vogels Chantal B F, Gallagher Glen, Burns Paul, Hentoff Aaron, Smole Sandra, Brown Catherine, Osborne Matthew, Kramer Laura D, Armstrong Philip M, Ciota Alexander T, Grubaugh Nathan D

机构信息

Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.

The Arbovirus Laboratory, New York State Department of Health, Wadsworth Center, Slingerlands, NY, USA.

出版信息

medRxiv. 2023 Mar 6:2023.03.06.23286851. doi: 10.1101/2023.03.06.23286851.

Abstract

Eastern equine encephalitis virus (EEEV) causes a rare but severe disease in horses and humans, and is maintained in an enzootic transmission cycle between songbirds and mosquitoes. In 2019, the largest EEEV outbreak in the United States for more than 50 years occurred, centered in the Northeast. To explore the dynamics of the outbreak, we sequenced 80 isolates of EEEV and combined them with existing genomic data. We found that, like previous years, cases were driven by frequent short-lived virus introductions into the Northeast from Florida. Once in the Northeast, we found that Massachusetts was important for regional spread. We found no evidence of any changes in viral, human, or bird factors which would explain the increase in cases in 2019. By using detailed mosquito surveillance data collected by Massachusetts and Connecticut, however, we found that the abundance of was exceptionally high in 2019, as was the EEEV infection rate. We employed these mosquito data to build a negative binomial regression model and applied it to estimate early season risks of human or horse cases. We found that the month of first detection of EEEV in mosquito surveillance data and vector index (abundance multiplied by infection rate) were predictive of cases later in the season. We therefore highlight the importance of mosquito surveillance programs as an integral part of public health and disease control.

摘要

东部马脑炎病毒(EEEV)可在马匹和人类中引发一种罕见但严重的疾病,并且在鸣禽和蚊子之间的动物疫源性传播循环中持续存在。2019年,美国发生了50多年来规模最大的东部马脑炎病毒疫情,疫情集中在东北部地区。为了探究此次疫情的动态情况,我们对80株东部马脑炎病毒分离株进行了测序,并将其与现有的基因组数据相结合。我们发现,与前几年一样,病例是由病毒频繁且短暂地从佛罗里达州传入东北部地区所驱动的。一旦进入东北部地区,我们发现马萨诸塞州对于病毒的区域传播至关重要。我们没有发现任何病毒、人类或鸟类因素发生变化的证据可以解释2019年病例数的增加。然而,通过使用马萨诸塞州和康涅狄格州收集的详细蚊虫监测数据,我们发现2019年的蚊虫数量异常之多,东部马脑炎病毒感染率也是如此。我们利用这些蚊虫数据建立了一个负二项回归模型,并将其应用于估计人类或马匹病例在季节早期的风险。我们发现,在蚊虫监测数据中首次检测到东部马脑炎病毒的月份以及媒介指数(数量乘以感染率)可以预测该季节后期的病例数。因此,我们强调蚊虫监测项目作为公共卫生和疾病控制不可或缺的一部分的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9789/10029029/fcdfc878e7d5/nihpp-2023.03.06.23286851v1-f0001.jpg

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