Outbreak Size Distribution in Stochastic Epidemic Models
Motivated by recent epidemic outbreaks, including those of COVID-19, we solve the canonical problem of calculating the dynamics and likelihood of extensive outbreaks in a population within a large class of stochastic epidemic models with demographic noise, including the susceptible-infected-recovered (SIR) model and its general extensions. In the limit of large populations, we compute the probability distribution for all extensive outbreaks, including those that entail unusually large or small (extreme) proportions of the population infected. Our approach reveals that, unlike other well-known examples of rare events occurring in discrete-state stochastic systems, the statistics of extreme outbreaks emanate from a full continuum of Hamiltonian paths, each satisfying unique boundary conditions with a conserved probability flux.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:128 |
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| Enthalten in: |
Physical review letters - 128(2022), 7 vom: 18. Feb., Seite 078301 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Hindes, Jason [VerfasserIn] |
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| Anmerkungen: |
Date Completed 08.03.2022 Date Revised 08.03.2022 published: Print Citation Status MEDLINE |
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| doi: |
10.1103/PhysRevLett.128.078301 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM337756007 |
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| 520 | |a Motivated by recent epidemic outbreaks, including those of COVID-19, we solve the canonical problem of calculating the dynamics and likelihood of extensive outbreaks in a population within a large class of stochastic epidemic models with demographic noise, including the susceptible-infected-recovered (SIR) model and its general extensions. In the limit of large populations, we compute the probability distribution for all extensive outbreaks, including those that entail unusually large or small (extreme) proportions of the population infected. Our approach reveals that, unlike other well-known examples of rare events occurring in discrete-state stochastic systems, the statistics of extreme outbreaks emanate from a full continuum of Hamiltonian paths, each satisfying unique boundary conditions with a conserved probability flux | ||
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| 700 | 1 | |a Schwartz, Ira B |e verfasserin |4 aut | |
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