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?

利用美国公开报告的流感样疾病和实验室确诊的流感病例来识别潜在的未记录的 COVID-19 病例:一种综合征监测方法?

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Abstract

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.

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