![Author ORCID: We display the ORCID iD icon alongside authors names on our website to acknowledge that the ORCiD has been authenticated when entered by the user. To view the users ORCiD record click the icon. [opens in a new tab]](https://www.cambridge.org/engage/assets/public/coe/logo/orcid.png){kind=logo}
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.