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Identifying the outbreak signal of COVID-19 before the response of the traditional disease monitoring system.
Dai, Yaoyao; Wang, Jianming.
  • Dai Y; Department of Infectious Diseases, Center for Disease Control and Prevention of Nantong City, Nantong, China.
  • Wang J; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
PLoS Negl Trop Dis ; 14(10): e0008758, 2020 10.
Article in English | MEDLINE | ID: covidwho-810263
ABSTRACT
SYNOPSIS Early identification of the emergence of an outbreak of a novel infectious disease is critical to generating a timely response. The traditional monitoring system is adequate for detecting the outbreak of common diseases; however, it is insufficient for the discovery of novel infectious diseases. In this study, we used COVID-19 as an example to compare the delay time of different tools for identifying disease outbreaks. The results showed that both the abnormal spike in influenza-like illnesses and the peak of online searches of key terms could provide early signals. We emphasize the importance of testing these findings and discussing the broader potential to use syndromic surveillance, internet searches, and social media data together with traditional disease surveillance systems for early detection and understanding of novel emerging infectious diseases.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Sentinel Surveillance / Disease Notification Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS Negl Trop Dis Journal subject: Tropical Medicine Year: 2020 Document Type: Article Affiliation country: Journal.pntd.0008758

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Sentinel Surveillance / Disease Notification Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS Negl Trop Dis Journal subject: Tropical Medicine Year: 2020 Document Type: Article Affiliation country: Journal.pntd.0008758