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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

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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 & Epidemiology – Taylor & Francis

Published: Jan 2, 2022

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

References

  • The basic reproduction number of the new coronavirus pandemic with mortality for India, the Syrian Arab Republic, the United States, Yemen, China, France, Nigeria and Russia with different rate of cases
  • The basic reproduction number of SARS-CoV-2 in Wuhan is about to die out, how about the rest of the world?
  • Basic reproduction number and predicted trends of coronavirus disease 2019 epidemic in the mainland of China
  • The reproduction number of COVID-19 and its correlation with public health interventions
  • Implementation of An online COVID-19 epidemic calculator for tracking the spread of the Coronavirus in Singapore and other countries
  • A machine learning forecasting model for COVID-19 pandemic in India
  • Real-Time forecasting of the COVID-19 outbreak in Chinese provinces: machine learning approach using novel digital data and estimates from mechanistic models
  • Forecasting the spread of the COVID-19 pandemic in Saudi Arabia using ARIMA prediction model under current public health interventions
  • Coronavirus pandemic forecasting daily confirmed COVID-19 cases in Malaysia using ARIMA models
  • Modeling and forecasting for the number of cases of the COVID-19 pandemic with the curve estimation models, the Box-Jenkins and exponential smoothing methods
  • Short-term forecasting of daily COVID-19 cases in Brazil by using the Holt’s model
  • Route to chaos in generalized logistic map
  • One-Dimensional nonlinear model for producing chaos
  • A simple method for detecting chaos in nature
  • A contribution to the mathematical theory of epidemics
  • Forecasting COVID-19 epidemic in India and high incidence states using SIR and logistic growth models
  • The forecasting of COVID-19 with mortality using SIRD epidemic model for the United States, Russia, China, and the Syrian Arab Republic