Non-Analytic Behaviour in Large-deviations of the SIR model under the influence of Lockdowns Article Swipe
Leo Patrick Mulholland
,
Yannick Feld
,
Alexander K. Hartmann
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2307.13521
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2307.13521
We numerically investigate the dynamics of an SIR model with infection level-based lockdowns on Small-World networks. Using a large-deviation approach, namely the Wang-Landau algorithm, we study the distribution of the cumulative fraction of infected individuals. We are able to resolve the density of states for values as low as $10^{-85}$. Hence, we measure the distribution on its full support giving a complete characterization of this quantity. The lockdowns are implemented by severing a certain fraction of the edges in the Small-World network, and are initiated and released at different levels of infection, which are varied within this study. We observe points of non-analytical behaviour for the pdf and discontinuous transitions for correlations with other quantities such as the maximum fraction of infected and the duration of outbreaks. Further, empirical rate functions were calculated for different system sizes, for which a convergence is clearly visible indicating that the large-deviation principle is valid for the system with lockdowns.
Related Topics
Concepts
Fraction (chemistry)
Statistical physics
Measure (data warehouse)
Convergence (economics)
Empirical measure
Distribution (mathematics)
Mathematics
Large deviations theory
Standard deviation
Rate function
Statistics
Applied mathematics
Physics
Mathematical analysis
Computer science
Chemistry
Economics
Database
Economic growth
Organic chemistry
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2307.13521
- https://arxiv.org/pdf/2307.13521
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4385292638
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https://openalex.org/W4385292638Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2307.13521Digital Object Identifier
- Title
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Non-Analytic Behaviour in Large-deviations of the SIR model under the influence of LockdownsWork title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-07-25Full publication date if available
- Authors
-
Leo Patrick Mulholland, Yannick Feld, Alexander K. HartmannList of authors in order
- Landing page
-
https://arxiv.org/abs/2307.13521Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2307.13521Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2307.13521Direct OA link when available
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Fraction (chemistry), Statistical physics, Measure (data warehouse), Convergence (economics), Empirical measure, Distribution (mathematics), Mathematics, Large deviations theory, Standard deviation, Rate function, Statistics, Applied mathematics, Physics, Mathematical analysis, Computer science, Chemistry, Economics, Database, Economic growth, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.infection | 10 |
| abstract_inverted_index.initiated | 84 |
| abstract_inverted_index.lockdowns | 12, 67 |
| abstract_inverted_index.networks. | 15 |
| abstract_inverted_index.principle | 148 |
| abstract_inverted_index.quantity. | 65 |
| abstract_inverted_index.algorithm, | 23 |
| abstract_inverted_index.calculated | 132 |
| abstract_inverted_index.cumulative | 30 |
| abstract_inverted_index.indicating | 144 |
| abstract_inverted_index.infection, | 91 |
| abstract_inverted_index.lockdowns. | 155 |
| abstract_inverted_index.outbreaks. | 126 |
| abstract_inverted_index.quantities | 114 |
| abstract_inverted_index.$10^{-85}$. | 49 |
| abstract_inverted_index.Small-World | 14, 80 |
| abstract_inverted_index.Wang-Landau | 22 |
| abstract_inverted_index.convergence | 140 |
| abstract_inverted_index.implemented | 69 |
| abstract_inverted_index.investigate | 2 |
| abstract_inverted_index.level-based | 11 |
| abstract_inverted_index.numerically | 1 |
| abstract_inverted_index.transitions | 109 |
| abstract_inverted_index.correlations | 111 |
| abstract_inverted_index.distribution | 27, 54 |
| abstract_inverted_index.individuals. | 34 |
| abstract_inverted_index.discontinuous | 108 |
| abstract_inverted_index.non-analytical | 102 |
| abstract_inverted_index.large-deviation | 18, 147 |
| abstract_inverted_index.characterization | 62 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/17 |
| sustainable_development_goals[0].score | 0.4399999976158142 |
| sustainable_development_goals[0].display_name | Partnerships for the goals |
| citation_normalized_percentile |