Not all interventions are equal for the height of the second peak. (October 2020)
- Record Type:
- Journal Article
- Title:
- Not all interventions are equal for the height of the second peak. (October 2020)
- Main Title:
- Not all interventions are equal for the height of the second peak
- Authors:
- Jorritsma, Joost
Hulshof, Tim
Komjáthy, Júlia - Abstract:
- Highlights: Epidemic spread on spatial scale-free networks. Flattening the curve via interventions. Temporary immunity causing second peaks. Abstract: In this paper we conduct a simulation study of the spread of an epidemic like COVID-19 with temporary immunity on finite spatial and non-spatial network models. In particular, we assume that an epidemic spreads stochastically on a scale-free network and that each infected individual in the network gains a temporary immunity after its infectious period is over. After the temporary immunity period is over, the individual becomes susceptible to the virus again. When the underlying contact network is embedded in Euclidean geometry, we model three different intervention strategies that aim to control the spread of the epidemic: social distancing, restrictions on travel, and restrictions on maximal number of social contacts per node. Our first finding is that on a finite network, a long enough average immunity period leads to extinction of the pandemic after the first peak, analogous to the concept of "herd immunity". For each model, there is a critical average immunity duration Lc above which this happens. Our second finding is that all three interventions manage to flatten the first peak (the travel restrictions most efficiently), as well as decrease the critical immunity duration Lc, but elongate the epidemic. However, when the average immunity duration L is shorter than Lc, the price for the flattened first peak is often a highHighlights: Epidemic spread on spatial scale-free networks. Flattening the curve via interventions. Temporary immunity causing second peaks. Abstract: In this paper we conduct a simulation study of the spread of an epidemic like COVID-19 with temporary immunity on finite spatial and non-spatial network models. In particular, we assume that an epidemic spreads stochastically on a scale-free network and that each infected individual in the network gains a temporary immunity after its infectious period is over. After the temporary immunity period is over, the individual becomes susceptible to the virus again. When the underlying contact network is embedded in Euclidean geometry, we model three different intervention strategies that aim to control the spread of the epidemic: social distancing, restrictions on travel, and restrictions on maximal number of social contacts per node. Our first finding is that on a finite network, a long enough average immunity period leads to extinction of the pandemic after the first peak, analogous to the concept of "herd immunity". For each model, there is a critical average immunity duration Lc above which this happens. Our second finding is that all three interventions manage to flatten the first peak (the travel restrictions most efficiently), as well as decrease the critical immunity duration Lc, but elongate the epidemic. However, when the average immunity duration L is shorter than Lc, the price for the flattened first peak is often a high second peak: for limiting the maximal number of contacts, the second peak can be as high as 1/3 of the first peak, and twice as high as it would be without intervention. Thirdly, interventions introduce oscillations into the system and the time to reach equilibrium is, for almost all scenarios, much longer. We conclude that network-based epidemic models can show a variety of behaviors that are not captured by the continuous compartmental models. … (more)
- Is Part Of:
- Chaos, solitons and fractals. Volume 139(2020)
- Journal:
- Chaos, solitons and fractals
- Issue:
- Volume 139(2020)
- Issue Display:
- Volume 139, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 139
- Issue:
- 2020
- Issue Sort Value:
- 2020-0139-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-10
- Subjects:
- Theoretical epidemiology -- COVID-19 Intervention strategies -- Temporary immunity -- Spatio-temporal network analysis -- Agent-based epidemic modeling
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.2020.109965 ↗
- 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:
- 14730.xml