Review: Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic – detecting and evaluating emerging clusters

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Review: Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic – detecting and evaluating emerging clusters

Review: Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic – detecting and evaluating emerging clusters

This article utilized a prospective space-time scan statistic to detect emerging clusters of COVID-19 in the United States at the county level. Results can inform public health officials and decision makers about where to improve the allocation of resources, testing sites; also, where to implement stricter quarantines and travel bans.

It is critical to detect clusters of COVID-19 to better allocate resources and improve decision-making as the outbreaks continue to grow.

In this study, the authors used daily case data at the county level provided by Johns Hopkins University to conduct a prospective spatial-temporal analysis with SaTScan. They detected statistically significant space-time clusters of COVID-19 at the county level in the U.S. between January 22nd-March 9th, 2020, and January 22nd-March 27th, 2020.

Their space-time prospective scan statistic detected “active” and emerging clusters present at the end of our study periods. Notably, 18 more clusters were detected when adding the updated case data. The authors recommend prioritizing counties belonging to emerging clusters when allocating resources and implementing various quarantine and isolation measures to slow viral transmission.

 

|2020-04-15T10:55:58-04:00April 15th, 2020|COVID-19 Literature|Comments Off on Review: Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic – detecting and evaluating emerging clusters

About the Author: Erika Cheng

Erika Cheng

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