Chu Helen Y, Boeckh Michael, Englund Janet A, Famulare Michael, Lutz Barry, Nickerson Deborah A, Rieder Mark, Starita Lea M, Adler Amanda, Brandstetter Elisabeth, Frazer Chris D, Han Peter D, Gulati Reena K, Hadfield James, Jackson Michael, Kiavand Anahita, Kimball Louise E, Lacombe Kirsten, Newman Kira, Sibley Thomas R, Logue Jennifer K, Lyon Victoria Rachel, Wolf Caitlin R, Zigman Suchsland Monica, Shendure Jay, Bedford Trevor
Department of Medicine, University of Washington, Seattle, Washington, USA
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
BMJ Open. 2020 Oct 7;10(10):e037295. doi: 10.1136/bmjopen-2020-037295.
Influenza epidemics and pandemics cause significant morbidity and mortality. An effective response to a potential pandemic requires the infrastructure to rapidly detect, characterise, and potentially contain new and emerging influenza strains at both an individual and population level. The objective of this study is to use data gathered simultaneously from community and hospital sites to develop a model of how influenza enters and spreads in a population.
Starting in the 2018-2019 season, we have been enrolling individuals with acute respiratory illness from community sites throughout the Seattle metropolitan area, including clinics, childcare facilities, Seattle-Tacoma International Airport, workplaces, college campuses and homeless shelters. At these sites, we collect clinical data and mid-nasal swabs from individuals with at least two acute respiratory symptoms. Additionally, we collect residual nasal swabs and data from individuals who seek care for respiratory symptoms at four regional hospitals. Samples are tested using a multiplex molecular assay, and influenza whole genome sequencing is performed for samples with influenza detected. Geospatial mapping and computational modelling platforms are in development to characterise the regional spread of influenza and other respiratory pathogens.
The study was approved by the University of Washington's Institutional Review Board (STUDY00006181). Results will be disseminated through talks at conferences, peer-reviewed publications and on the study website (www.seattleflu.org).
流感流行和大流行会导致严重的发病和死亡。要有效应对潜在的大流行，需要具备在个体和人群层面快速检测、鉴定并可能控制新出现流感毒株的基础设施。本研究的目的是利用从社区和医院场所同时收集的数据，建立一个流感在人群中传入和传播方式的模型。
从2018 - 2019年流感季开始，我们一直在西雅图都会区的社区场所招募患有急性呼吸道疾病的个体，这些场所包括诊所、儿童保育设施、西雅图 - 塔科马国际机场、工作场所、大学校园和无家可归者收容所。在这些场所，我们从至少有两种急性呼吸道症状的个体中收集临床数据和中鼻拭子。此外，我们从四家地区医院中因呼吸道症状就诊的个体那里收集剩余鼻拭子和数据。样本使用多重分子检测法进行检测，对检测出流感的样本进行流感全基因组测序。正在开发地理空间绘图和计算建模平台，以描述流感和其他呼吸道病原体的区域传播情况。
本研究已获得华盛顿大学机构审查委员会（STUDY00006181）的批准。研究结果将通过在会议上的报告、同行评审出版物以及研究网站（www.seattleflu.org）进行传播。
