Modeling epidemics through ladder operators. (November 2020)
- Record Type:
- Journal Article
- Title:
- Modeling epidemics through ladder operators. (November 2020)
- Main Title:
- Modeling epidemics through ladder operators
- Authors:
- Bagarello, F.
Gargano, F.
Roccati, F. - Abstract:
- Highlights: We propose an operatorial model to describe epidemics. The model describes well the asymptotic numbers of the epidemics. Ladder operators are used to model exchanges between the "actors" of the system. Abstract: We propose a simple model of spreading of some infection in an originally healthy population which is different from other models existing in the literature. In particular, we use an operator technique which allows us to describe in a natural way the possible interactions between healthy and un-healthy populations, and their transformation into recovered and to dead people. After a rather general discussion, we apply our method to the analysis of Chinese data for the SARS-2003 (Severe acute respiratory syndrome; SARS-CoV-1) and the Coronavirus COVID-19 (Corona Virus Disease; SARS-CoV-2) and we show that the model works very well in reproducing the long-time behaviour of the disease, and in particular in finding the number of affected and dead people in the limit of large time. Moreover, we show how the model can be easily modified to consider some lockdown measure, and we deduce that this procedure drastically reduces the asymptotic value of infected individuals, as expected, and observed in real life.
- 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:
- 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.2020.110193 ↗
- 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