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On forecasting the spread of the COVID-19 in Iran: The second wave
One of the common misconceptions about COVID-19 disease is to assume that we will not see a recurrence after the first wave of the disease has subsided. This completely wrong perception causes people to disregard the necessary protocols and engage in some misbehavior, such as routine socializing or...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7386426/ https://www.ncbi.nlm.nih.gov/pubmed/32834656 http://dx.doi.org/10.1016/j.chaos.2020.110176 |
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author | Ghanbari, Behzad |
author_facet | Ghanbari, Behzad |
author_sort | Ghanbari, Behzad |
collection | PubMed |
description | One of the common misconceptions about COVID-19 disease is to assume that we will not see a recurrence after the first wave of the disease has subsided. This completely wrong perception causes people to disregard the necessary protocols and engage in some misbehavior, such as routine socializing or holiday travel. These conditions will put double pressure on the medical staff and endanger the lives of many people around the world. In this research, we are interested in analyzing the existing data to predict the number of infected people in the second wave of out-breaking COVID-19 in Iran. For this purpose, a model is proposed. The mathematical analysis corresponded to the model is also included in this paper. Based on proposed numerical simulations, several scenarios of progress of COVID-19 corresponding to the second wave of the disease in the coming months, will be discussed. We predict that the second wave of will be most severe than the first one. From the results, improving the recovery rate of people with weak immune systems via appropriate medical incentives is resulted as one of the most effective prescriptions to prevent the widespread unbridled outbreak of the second wave of COVID-19. |
format | Online Article Text |
id | pubmed-7386426 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73864262020-07-29 On forecasting the spread of the COVID-19 in Iran: The second wave Ghanbari, Behzad Chaos Solitons Fractals Article One of the common misconceptions about COVID-19 disease is to assume that we will not see a recurrence after the first wave of the disease has subsided. This completely wrong perception causes people to disregard the necessary protocols and engage in some misbehavior, such as routine socializing or holiday travel. These conditions will put double pressure on the medical staff and endanger the lives of many people around the world. In this research, we are interested in analyzing the existing data to predict the number of infected people in the second wave of out-breaking COVID-19 in Iran. For this purpose, a model is proposed. The mathematical analysis corresponded to the model is also included in this paper. Based on proposed numerical simulations, several scenarios of progress of COVID-19 corresponding to the second wave of the disease in the coming months, will be discussed. We predict that the second wave of will be most severe than the first one. From the results, improving the recovery rate of people with weak immune systems via appropriate medical incentives is resulted as one of the most effective prescriptions to prevent the widespread unbridled outbreak of the second wave of COVID-19. Elsevier Ltd. 2020-11 2020-07-28 /pmc/articles/PMC7386426/ /pubmed/32834656 http://dx.doi.org/10.1016/j.chaos.2020.110176 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Ghanbari, Behzad On forecasting the spread of the COVID-19 in Iran: The second wave |
title | On forecasting the spread of the COVID-19 in Iran: The second wave |
title_full | On forecasting the spread of the COVID-19 in Iran: The second wave |
title_fullStr | On forecasting the spread of the COVID-19 in Iran: The second wave |
title_full_unstemmed | On forecasting the spread of the COVID-19 in Iran: The second wave |
title_short | On forecasting the spread of the COVID-19 in Iran: The second wave |
title_sort | on forecasting the spread of the covid-19 in iran: the second wave |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7386426/ https://www.ncbi.nlm.nih.gov/pubmed/32834656 http://dx.doi.org/10.1016/j.chaos.2020.110176 |
work_keys_str_mv | AT ghanbaribehzad onforecastingthespreadofthecovid19iniranthesecondwave |