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What is the role of scale in the early detection of COVID19 outbreaks?
Topics: Health and Medical
, Spatial Analysis & Modeling
, Geographic Information Science and Systems
Keywords: COVID-19, SaTScan, Space-time clusters, Pandemic, Disease surveillance, Scale Session Type: Virtual Paper Abstract Day: Monday Session Start / End Time: 2/28/2022 08:00 AM (Eastern Time (US & Canada)) - 2/28/2022 09:20 AM (Eastern Time (US & Canada)) Room: Virtual 56
Authors:
Eric Delmelle, University of North Carolina at Charlotte
Michael Desjardins, Johns Hopkins University
Yu Lan, University of North Carolina at Charlotte
Alexander Hohl, University of Utah
Xun Shi, Dartmouth College
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Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first discovered in late 2019 in Wuhan City, China. Although there have been several papers suggesting that using disaggregated data can lead to more accurate models of transmission, most of the data is aggregated to some type of geographic unit (e.g. zip code). This is generally done in an effort to maintain some privacy (e.g. HIPAA), while at the same time it allows researchers to evaluate the importance of covariates, which are generally available at an aggregate level. In this paper, we utilize a prospective Poisson space-time scan statistic to detect daily clusters of COVID-19 cases at three different geographic scales in the state of Wisconsin (USA), from census tracts to zip code and county levels. Our results suggest that finer levels aggregation can provide an initial signal of an increasing incidence of COVID19 which can be particularly useful for public health prevention purposes.
What is the role of scale in the early detection of COVID19 outbreaks?
