On forecasting the spread of the COVID-19 in Iran: The second wave. (November 2020)
- Record Type:
- Journal Article
- Title:
- On forecasting the spread of the COVID-19 in Iran: The second wave. (November 2020)
- Main Title:
- On forecasting the spread of the COVID-19 in Iran: The second wave
- Authors:
- Ghanbari, Behzad
- Abstract:
- Highlights: A predictive COVID-19 model is considered. The second wave of COVID-19 in Iran is studied. Some predictive results of the peak epidemic outbreak are given. Estimated times of the end of the epidemic in Iran in several scenarios are approximated in the plots. The second wave of COVID-19 is predicated to happen between August and December 2020. Abstract: 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 effectiveHighlights: A predictive COVID-19 model is considered. The second wave of COVID-19 in Iran is studied. Some predictive results of the peak epidemic outbreak are given. Estimated times of the end of the epidemic in Iran in several scenarios are approximated in the plots. The second wave of COVID-19 is predicated to happen between August and December 2020. Abstract: 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. … (more)
- Is Part Of:
- Chaos, solitons and fractals. Volume 140(2020)
- Journal:
- Chaos, solitons and fractals
- Issue:
- Volume 140(2020)
- Issue Display:
- Volume 140, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 140
- Issue:
- 2020
- Issue Sort Value:
- 2020-0140-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11
- Subjects:
- COVID-19 -- The second wave -- Dynamic systems -- Infectious disease -- Forecasting of the epidemic
Chaotic behavior in systems -- Periodicals
Solitons -- Periodicals
Fractals -- Periodicals
Chaotic behavior in systems
Fractals
Solitons
Periodicals
003.7 - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/09600779 ↗ - DOI:
- 10.1016/j.chaos.2020.110176 ↗
- Languages:
- English
- ISSNs:
- 0960-0779
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3129.716000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14938.xml