TY  - JOUR
A1  - Hindes, Jason
A1  - Assaf, Michael
A1  - Schwartz, Ira B.
T1  - Outbreak size distribution in stochastic epidemic models
T2  - Physical review letters
N2  - 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.
Y1  - 2022
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/63323
SN  - 0031-9007
SN  - 1079-7114
SN  - 1092-0145
VL  - 128
IS  - 7
PB  - American Physical Society
CY  - College Park, Md.
ER  -