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Temporal dynamics for areal unit-based co-occurrence COVID-19 trajectories.
Owusu, Gabriel; Yu, Han; Huang, Hong.
  • Owusu G; Department of Applied Statistics and Research Methods, University of Northern Colorado, Greeley, CO 80639, USA.
  • Yu H; Department of Applied Statistics and Research Methods, University of Northern Colorado, Greeley, CO 80639, USA.
  • Huang H; School of Information, University of South Florida, Tampa, FL, 33620, USA.
AIMS Public Health ; 9(4): 703-717, 2022.
Article in English | MEDLINE | ID: covidwho-2110358
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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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: AIMS Public Health Year: 2022 Document Type: Article Affiliation country: Publichealth.2022049

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: AIMS Public Health Year: 2022 Document Type: Article Affiliation country: Publichealth.2022049