Identifying potential undocumented COVID-19 using publicly reported influenza-like-illness and laboratory-confirmed influenza disease in the United States: An approach to syndromic surveillance?

被引:9
作者
Wiemken, Timothy L. [1 ,2 ,3 ]
Shacham, Enbal [3 ,4 ]
机构
[1] St Louis Univ, Ctr Hlth Outcomes Res, St Louis, MO 63104 USA
[2] St Louis Univ, Div Infect Dis Allergy & Immunol, St Louis, MO 63104 USA
[3] St Louis Univ, Geospatial Inst, St Louis, MO 63104 USA
[4] St Louis Univ, Dept Behav Sci & Hlth Educ, Coll Publ Hlth & Social Justice, St Louis, MO 63104 USA
关键词
SARS-CoV-2; Coronavirus; Syndrome; Influenza; Contact tracing;
D O I
10.1016/j.ajic.2020.05.007
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
In the absence of widespread testing, syndromic surveillance approaches may be useful for understanding potential undocumented coronavirus disease 2019 (COVID-19) in the United States. We used publicly available data from the Centers for Disease Control and Prevention FluView Interactive to evaluate its potential for COVID-19 syndromic surveillance. Unlike the prior 3 influenza seasons, we found a 76% decrease in influenza positive tests and a 27% increase in influenza like illness during the weeks since COVID-19 outbreaks began in the United States, which suggests FluView's potential utility for COVID-19 syndromic surveillance. (C) 2020 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:961 / 963
页数:3
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