Temporal dynamics for areal unit-based co-occurrence COVID-19 trajectories.

Gabriel Owusu, Han Yu, Hong Huang
Author Information
  1. Gabriel Owusu: Department of Applied Statistics and Research Methods, University of Northern Colorado, Greeley, CO 80639, USA.
  2. Han Yu: Department of Applied Statistics and Research Methods, University of Northern Colorado, Greeley, CO 80639, USA.
  3. Hong Huang: School of Information, University of South Florida, Tampa, FL, 33620, 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.

Keywords

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