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Reproduction number, discrete forecasting model, and chaos analytics for Coronavirus Disease 2019 outbreak in India, Bangladesh, and Myanmar

Reproduction number, discrete forecasting model, and chaos analytics for Coronavirus Disease 2019... Emerging Infectious Disease of Coronavirus 2019 is a catastrophe of human beings. Controlling, monitoring, and forecasting the COVID-19 outbreak is very important for the authorities to make a decision on launching the policy for suppressing it. Reproduction numbers of epidemiology models and forecasting models have been developed to control and monitor the COVID-19 outbreak via policies of authorities, such as social distancing and wearing mask. Thus, the purposes of this research are to estimate the reproduction number of susceptible infectious recovered models and forecast the number of total COVID-19 cases every day based on discrete logistic models. Moreover, chaos analysis and spreading power of the number of COVID-19 cases by day are investigated with regard to COVID-19 situation in India, Bangladesh, and Myanmar. The results showed that its spread was highest in India and the transmission potential of COVID-19 in Myanmar is higher compared to India and Bangladesh. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biostatistics & Epidemiology Taylor & Francis

Reproduction number, discrete forecasting model, and chaos analytics for Coronavirus Disease 2019 outbreak in India, Bangladesh, and Myanmar

Reproduction number, discrete forecasting model, and chaos analytics for Coronavirus Disease 2019 outbreak in India, Bangladesh, and Myanmar

Abstract

Emerging Infectious Disease of Coronavirus 2019 is a catastrophe of human beings. Controlling, monitoring, and forecasting the COVID-19 outbreak is very important for the authorities to make a decision on launching the policy for suppressing it. Reproduction numbers of epidemiology models and forecasting models have been developed to control and monitor the COVID-19 outbreak via policies of authorities, such as social distancing and wearing mask. Thus, the purposes of this research are to...
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Publisher
Taylor & Francis
Copyright
© 2021 International Biometric Society – Chinese Region
ISSN
2470-9379
eISSN
2470-9360
DOI
10.1080/24709360.2021.1960122
Publisher site
See Article on Publisher Site

Abstract

Emerging Infectious Disease of Coronavirus 2019 is a catastrophe of human beings. Controlling, monitoring, and forecasting the COVID-19 outbreak is very important for the authorities to make a decision on launching the policy for suppressing it. Reproduction numbers of epidemiology models and forecasting models have been developed to control and monitor the COVID-19 outbreak via policies of authorities, such as social distancing and wearing mask. Thus, the purposes of this research are to estimate the reproduction number of susceptible infectious recovered models and forecast the number of total COVID-19 cases every day based on discrete logistic models. Moreover, chaos analysis and spreading power of the number of COVID-19 cases by day are investigated with regard to COVID-19 situation in India, Bangladesh, and Myanmar. The results showed that its spread was highest in India and the transmission potential of COVID-19 in Myanmar is higher compared to India and Bangladesh.

Journal

Biostatistics & EpidemiologyTaylor & Francis

Published: Jan 2, 2022

Keywords: Coronavirus disease 2019; parameter estimation; biostatistics; chaos analysis

References