Prospective Spatial-Temporal Clusters of COVID-19 in Local Communities: Case Study of Kansas City, Missouri, United States

29 September 2021, Version 1
This content is an early or alternative research output and has not been peer-reviewed by Cambridge University Press at the time of posting.

Abstract

Just in the United States (U.S.), the COVID-19 cases reached over 37 million as of August 2021. Kansas City in Missouri State has become one of the major U.S. hot spots for COVID-19 due to an increase in the rate of positive COVID-19 test results. Despite the large numbers of COVID-19 cases in Kansas City, the Spatio-temporal analysis of data has been less investigated. In this study, we conducted a prospective Poisson spatial-temporal analysis of Kansas City, MO, COVID-19 data at the zip code level. The analysis focused on daily COVID-19 cases in four equal periods of three months. We detected temporal patterns of emerging and reemerging space-time clusters between March 2020 and February 202. The statistical results were communicated with local health officials and provided the necessary guidance for decision-making and the allocation of resources.

Keywords

COVID-19
Pandemic
Periodic surveillance
Cluster analysis
Space-time clusters
SatScan

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