SIR epidemics in populations with large sub-communities Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2204.06902
We investigate final outcome properties of an SIR (susceptible $\to$ infective $\to$ recovered) epidemic model defined on a population of large sub-communities in which there is stronger disease transmission within the communities than between them. Our analysis involves approximation of the epidemic process by a chain of within-community large outbreaks spreading between the communities. We derive law of large numbers and central limit type results for the number of individuals and the number of communities affected and the so-called severity of the outbreak. These results are valid as the size of communities tends to infinity, with the number of communities either fixed or also tending to infinity. The weaker between-community connections lead to randomness even in the law of large numbers type limit. As part of our proofs we also obtain a new result concerning the rate of convergence of the expected fraction infected in a standard SIR epidemic to its large-population limit.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2204.06902
- https://arxiv.org/pdf/2204.06902
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4224131878
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4224131878Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2204.06902Digital Object Identifier
- Title
-
SIR epidemics in populations with large sub-communitiesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
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2022-04-14Full publication date if available
- Authors
-
Frank Ball, David Sirl, Pieter TrapmanList of authors in order
- Landing page
-
https://arxiv.org/abs/2204.06902Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2204.06902Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2204.06902Direct OA link when available
- Concepts
-
Randomness, Limit (mathematics), Outbreak, Infinity, Population, Law of large numbers, Epidemic model, Transmission (telecommunications), Population size, Convergence (economics), Central limit theorem, Mathematics, Range (aeronautics), Demography, Geography, Statistics, Biology, Computer science, Economics, Virology, Sociology, Random variable, Economic growth, Telecommunications, Mathematical analysis, Materials science, Composite materialTop 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.or | 102 |
| abstract_inverted_index.to | 93, 105, 112, 149 |
| abstract_inverted_index.we | 128 |
| abstract_inverted_index.Our | 35 |
| abstract_inverted_index.SIR | 7, 147 |
| abstract_inverted_index.The | 107 |
| abstract_inverted_index.and | 60, 70, 76 |
| abstract_inverted_index.are | 85 |
| abstract_inverted_index.for | 65 |
| abstract_inverted_index.its | 150 |
| abstract_inverted_index.law | 56, 117 |
| abstract_inverted_index.new | 132 |
| abstract_inverted_index.our | 126 |
| abstract_inverted_index.the | 30, 40, 52, 66, 71, 77, 81, 88, 96, 116, 135, 140 |
| abstract_inverted_index.also | 103, 129 |
| abstract_inverted_index.even | 114 |
| abstract_inverted_index.lead | 111 |
| abstract_inverted_index.part | 124 |
| abstract_inverted_index.rate | 136 |
| abstract_inverted_index.size | 89 |
| abstract_inverted_index.than | 32 |
| abstract_inverted_index.type | 63, 121 |
| abstract_inverted_index.with | 95 |
| abstract_inverted_index.$\to$ | 9, 11 |
| abstract_inverted_index.These | 83 |
| abstract_inverted_index.chain | 45 |
| abstract_inverted_index.final | 2 |
| abstract_inverted_index.fixed | 101 |
| abstract_inverted_index.large | 20, 48, 58, 119 |
| abstract_inverted_index.limit | 62 |
| abstract_inverted_index.model | 14 |
| abstract_inverted_index.tends | 92 |
| abstract_inverted_index.them. | 34 |
| abstract_inverted_index.there | 24 |
| abstract_inverted_index.valid | 86 |
| abstract_inverted_index.which | 23 |
| abstract_inverted_index.derive | 55 |
| abstract_inverted_index.either | 100 |
| abstract_inverted_index.limit. | 122, 152 |
| abstract_inverted_index.number | 67, 72, 97 |
| abstract_inverted_index.obtain | 130 |
| abstract_inverted_index.proofs | 127 |
| abstract_inverted_index.result | 133 |
| abstract_inverted_index.weaker | 108 |
| abstract_inverted_index.within | 29 |
| abstract_inverted_index.between | 33, 51 |
| abstract_inverted_index.central | 61 |
| abstract_inverted_index.defined | 15 |
| abstract_inverted_index.disease | 27 |
| abstract_inverted_index.numbers | 59, 120 |
| abstract_inverted_index.outcome | 3 |
| abstract_inverted_index.process | 42 |
| abstract_inverted_index.results | 64, 84 |
| abstract_inverted_index.tending | 104 |
| abstract_inverted_index.affected | 75 |
| abstract_inverted_index.analysis | 36 |
| abstract_inverted_index.epidemic | 13, 41, 148 |
| abstract_inverted_index.expected | 141 |
| abstract_inverted_index.fraction | 142 |
| abstract_inverted_index.infected | 143 |
| abstract_inverted_index.involves | 37 |
| abstract_inverted_index.severity | 79 |
| abstract_inverted_index.standard | 146 |
| abstract_inverted_index.stronger | 26 |
| abstract_inverted_index.infective | 10 |
| abstract_inverted_index.infinity, | 94 |
| abstract_inverted_index.infinity. | 106 |
| abstract_inverted_index.outbreak. | 82 |
| abstract_inverted_index.outbreaks | 49 |
| abstract_inverted_index.so-called | 78 |
| abstract_inverted_index.spreading | 50 |
| abstract_inverted_index.concerning | 134 |
| abstract_inverted_index.population | 18 |
| abstract_inverted_index.properties | 4 |
| abstract_inverted_index.randomness | 113 |
| abstract_inverted_index.recovered) | 12 |
| abstract_inverted_index.communities | 31, 74, 91, 99 |
| abstract_inverted_index.connections | 110 |
| abstract_inverted_index.convergence | 138 |
| abstract_inverted_index.individuals | 69 |
| abstract_inverted_index.investigate | 1 |
| abstract_inverted_index.(susceptible | 8 |
| abstract_inverted_index.communities. | 53 |
| abstract_inverted_index.transmission | 28 |
| abstract_inverted_index.approximation | 38 |
| abstract_inverted_index.sub-communities | 21 |
| abstract_inverted_index.large-population | 151 |
| abstract_inverted_index.within-community | 47 |
| abstract_inverted_index.between-community | 109 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.8500000238418579 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile |