ArticleEpidemiology and infection2022
Prospective spatial-temporal clusters of COVID-19 in local communities: case study of Kansas City, Missouri, United States.
Article in Epidemiology and infection, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Bayesian inference of nosocomial meticillin-resistant Staphylococcus aureus transmission rates in an urban safety-net hospital.The Journal of hospital infection · 2025Article
- An agent-based model to assess the impact of shared staff and occupancy rate on infectious disease burden in nursing homes.BMC infectious diseases · 2025Article
- Utility of compartmental models to test the competing hypotheses of pathogen evolution and human intervention.Frontiers in public health · 2025Article
- Estimating the Relative Risks of Spatial Clusters Using a Predictor-Corrector Method.Mathematics (Basel, Switzerland) · 2025Article
- Article
- Incorporating global dynamics to improve the accuracy of disease models: Example of a COVID-19 SIR model.PloS one · 2022Article
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Authors and funding
5 authors.
Funding
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Abstract
Kansas City, Missouri, became one of the major United States hotspots for COVID-19 due to an increase in the rate of positive COVID-19 test results. Despite the large numbers of positive cases in Kansas City, MO, the spatial-temporal analysis of data has been less investigated. However, it is critical to detect emerging clusters of COVID-19 and enforce control and preventive policies within those clusters. We conducted a prospective Poisson spatial-temporal analysis of Kansas City, MO data to detect significant space-time clusters of COVID-19 positive cases at the zip code level in Kansas City, MO. The analysis focused on daily infected cases in four equal periods of 3 months. We detected temporal patterns of emerging and re-emerging space-time clusters between March 2020 and February 2021. Three statistically significant clusters emerged in the first period, mainly concentrated in downtown. It increased to seven clusters in the second period, spreading across a broader region in downtown and north of Kansas City. In the third period, nine clusters covered large areas of north and downtown Kansas City, MO. Ten clusters were present in the last period, further extending the infection along the State Line Road. The statistical results were communicated with local health officials and provided the necessary guidance for decision-making and allocating resources (e.g., vaccines and testing sites). As more data become available, statistical clustering can be used as a COVID-19 surveillance tool to measure the effects of vaccination.
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