Daily surveillance of COVID-19 using the prospective space-time scan statistic in the United States

•Prospective space-time statistics are particularly useful for COVID-19 surveillance.•Daily cluster detection can track the evolution of key hotspots of COVID-19.•Temporal trend towards smaller but more numerous clusters.•Time-periodic surveillance of COVID-19 facilitates decision-making in public h...

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Vydáno v:Spatial and spatio-temporal epidemiology Ročník 34; s. 100354
Hlavní autoři: Hohl, Alexander, Delmelle, Eric M., Desjardins, Michael R., Lan, Yu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Netherlands Elsevier Ltd 01.08.2020
The Authors. Published by Elsevier Ltd
Témata:
Communicable Diseases, Emerging - epidemiology
Coronavirus Infections - diagnosis
Coronavirus Infections - epidemiology
COVID-19
Databases, Factual
Disease Outbreaks - statistics & numerical data
Disease surveillance
Female
Humans
Male
Mass Screening - methods
Models, Statistical
Monte Carlo Method
Pandemic
Pandemics - statistics & numerical data
Pneumonia, Viral - diagnosis
Pneumonia, Viral - epidemiology
Poisson Distribution
Prevalence
Prospective Studies
Public Health
SaTScan
Severe Acute Respiratory Syndrome - diagnosis
Severe Acute Respiratory Syndrome - epidemiology
Space-Time Clustering
Space-time clusters
United States - epidemiology
United States
COVID-19
Disease surveillance
SaTScan
Pandemic
Space-time clusters
ISSN:1877-5845, 1877-5853, 1877-5853
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Shrnutí:•Prospective space-time statistics are particularly useful for COVID-19 surveillance.•Daily cluster detection can track the evolution of key hotspots of COVID-19.•Temporal trend towards smaller but more numerous clusters.•Time-periodic surveillance of COVID-19 facilitates decision-making in public health.•Web application for live results http://covid19scan.net. [Display omitted] The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first discovered in late 2019 in Wuhan City, China. The virus may cause novel coronavirus disease 2019 (COVID-19) in symptomatic individuals. Since December of 2019, there have been over 7,000,000 confirmed cases and over 400,000 confirmed deaths worldwide. In the United States (U.S.), there have been over 2,000,000 confirmed cases and over 110,000 confirmed deaths. COVID-19 case data in the United States has been updated daily at the county level since the first case was reported in January of 2020. There currently lacks a study that showcases the novelty of daily COVID-19 surveillance using space-time cluster detection techniques. In this paper, we utilize a prospective Poisson space-time scan statistic to detect daily clusters of COVID-19 at the county level in the contiguous 48 U.S. and Washington D.C. As the pandemic progresses, we generally find an increase of smaller clusters of remarkably steady relative risk. Daily tracking of significant space-time clusters can facilitate decision-making and public health resource allocation by evaluating and visualizing the size, relative risk, and locations that are identified as COVID-19 hotspots.
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ISSN:1877-5845
1877-5853
1877-5853
DOI:10.1016/j.sste.2020.100354