Stochastic two-patch epidemic model with nonlinear recidivism

Fuente: arXiv
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Autori principali: Calvo, Juan G., Simoy, Mario I., Aparicio, Juan P., Chacón, José E., Sanchez, Fabio
Natura: Preprint
Pubblicazione: 2024
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author Calvo, Juan G.
Simoy, Mario I.
Aparicio, Juan P.
Chacón, José E.
Sanchez, Fabio
author_facet Calvo, Juan G.
Simoy, Mario I.
Aparicio, Juan P.
Chacón, José E.
Sanchez, Fabio
contents We develop a stochastic two-patch epidemic model with nonlinear recidivism to investigate infectious disease dynamics in heterogeneous populations. Extending a deterministic framework, we introduce stochasticity to account for random transmission, recovery, and inter-patch movement fluctuations. We showcase the interplay between local dynamics and migration effects on disease persistence using Monte Carlo simulations and three stochastic approximations-discrete-time Markov chain (DTMC), Poisson, and stochastic differential equations (SDE). Our analysis shows that stochastic effects can cause extinction events and oscillations near critical thresholds like the basic reproduction number, R0, phenomena absent in deterministic models. Numerical simulations highlight source-sink dynamics, where one patch is a persistent infection source while the other experiences intermittent outbreaks.
format Preprint
id arxiv_https___arxiv_org_abs_2405_10998
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Stochastic two-patch epidemic model with nonlinear recidivism
Calvo, Juan G.
Simoy, Mario I.
Aparicio, Juan P.
Chacón, José E.
Sanchez, Fabio
Populations and Evolution
Dynamical Systems
60J20, 92D30, 92-08, 60H15
We develop a stochastic two-patch epidemic model with nonlinear recidivism to investigate infectious disease dynamics in heterogeneous populations. Extending a deterministic framework, we introduce stochasticity to account for random transmission, recovery, and inter-patch movement fluctuations. We showcase the interplay between local dynamics and migration effects on disease persistence using Monte Carlo simulations and three stochastic approximations-discrete-time Markov chain (DTMC), Poisson, and stochastic differential equations (SDE). Our analysis shows that stochastic effects can cause extinction events and oscillations near critical thresholds like the basic reproduction number, R0, phenomena absent in deterministic models. Numerical simulations highlight source-sink dynamics, where one patch is a persistent infection source while the other experiences intermittent outbreaks.
title Stochastic two-patch epidemic model with nonlinear recidivism
topic Populations and Evolution
Dynamical Systems
60J20, 92D30, 92-08, 60H15
url https://arxiv.org/abs/2405.10998