Temporal dynamics for areal unit-based co-occurrence COVID-19 trajectories
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Published on: February 25, 2013
Gabriel Owusu1, Han Yu1, Hong Huang2
1Department of Applied Statistics and Research Methods, University of Northern Colorado, Greeley, CO 80639, USA.
Abstract:
The dynamic mechanism of the COVID-19 pandemic has been studied for disease prevention and health protection through areal unit-based log-linear Poisson processes to understand the outbreak of the virus with confirmed daily empirical cases. The predictor of the evolution is structured as a function of a short-term dependence and a long-term trend to identify the pattern of exponential growth in the main epicenters of the virus. The study provides insight into the possible pandemic path of each areal unit and a guide to drive policymaking on preventive measures that can be applied or relaxed to mitigate the spread of the virus. It is significant that knowing the trend of the virus is very helpful for institutions and organizations in terms of instituting resources and measures to help provide a safe working environment and support for all workers/staff/students.
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