The predicted trend of COVID-19 in the United States of America under the policy of "Opening Up America Again"

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Author(s)
Yan, Kejia
Yan, Huqin
Gupta, Rakesh
Griffith University Author(s)
Year published
2021
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COVID-19 virus has been spreading worldwide for more than a year. At present, the situation of the new crown pneumonia epidemic remains full of tension and uncertainty. It is of concern is that the worst outbreak in the world is in the United States. The total number of confirmed new cases of COVID-19 and the total number of new deaths in the United States have entered their second and third cyclical peaks since the White House announced the “Open America Again” guidelines on April 16, 2020, and the start of the US presidential election season in August 2020. This paper combines the generalized exponential model (EXPM) with ...
View more >COVID-19 virus has been spreading worldwide for more than a year. At present, the situation of the new crown pneumonia epidemic remains full of tension and uncertainty. It is of concern is that the worst outbreak in the world is in the United States. The total number of confirmed new cases of COVID-19 and the total number of new deaths in the United States have entered their second and third cyclical peaks since the White House announced the “Open America Again” guidelines on April 16, 2020, and the start of the US presidential election season in August 2020. This paper combines the generalized exponential model (EXPM) with Chebyshev polynomials to develop a special generalized growth model (GGM) to predict the total number of daily new confirmed cases and the total number of new deaths in the United States for three periods under a 14-day sensitivity regression model. In this paper, the US epidemic is divided into three periods from early January 2020 to early January 2021, and three forecasts are made for the three periods. The first two prediction periods have already occurred and the predictions match well with known results, and the third period predicts that the total number of new confirmed cases of COVID-19 and the total number of new deaths in the United States will fall to a minimum level by next July, when the supply of COVID-19 vaccine has already begun. The results suggest that the “Open America Again” policy and the events of the 2020 US presidential election season have contributed to the worsening of the COVID-19 in the United States.
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View more >COVID-19 virus has been spreading worldwide for more than a year. At present, the situation of the new crown pneumonia epidemic remains full of tension and uncertainty. It is of concern is that the worst outbreak in the world is in the United States. The total number of confirmed new cases of COVID-19 and the total number of new deaths in the United States have entered their second and third cyclical peaks since the White House announced the “Open America Again” guidelines on April 16, 2020, and the start of the US presidential election season in August 2020. This paper combines the generalized exponential model (EXPM) with Chebyshev polynomials to develop a special generalized growth model (GGM) to predict the total number of daily new confirmed cases and the total number of new deaths in the United States for three periods under a 14-day sensitivity regression model. In this paper, the US epidemic is divided into three periods from early January 2020 to early January 2021, and three forecasts are made for the three periods. The first two prediction periods have already occurred and the predictions match well with known results, and the third period predicts that the total number of new confirmed cases of COVID-19 and the total number of new deaths in the United States will fall to a minimum level by next July, when the supply of COVID-19 vaccine has already begun. The results suggest that the “Open America Again” policy and the events of the 2020 US presidential election season have contributed to the worsening of the COVID-19 in the United States.
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Journal Title
Infectious Disease Modelling
Volume
6
Copyright Statement
© 2021 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International (CC BY-NC-ND 4.0) License, which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
Subject
Epidemiology
Public health
Applied statistics
Science & Technology
Life Sciences & Biomedicine
Mathematical & Computational Biology
Infectious Diseases
COVID-19