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These notes describe stochastic epidemics in a homogenous community. Our main concern is stochastic compartmental models (i.e. models where each individual belongs to a compartment, which stands for its status regarding the epidemic under…

Probability · Mathematics 2020-02-06 Tom Britton , Etienne Pardoux

There is a long history of establishing central limit theorems for Markov chains. Quantitative bounds for chains with a spectral gap were proved by Mann and refined later. Recently, rates of convergence for the total variation distance were…

Probability · Mathematics 2023-08-24 Rafael Chiclana , Yuval Peres

The purpose of this paper is to study a Markovian metapopulation model on a directed graph with edge-supported transfers and deterministic intra-nodal population dynamics. We first state tractable stability conditions for two typical…

Probability · Mathematics 2019-05-28 Pierre Montagnon

We consider an asexually reproducing population on a finite type space whose evolution is driven by exponential birth, death and competition rates, as well as the possibility of mutation at a birth event. On the individual-based level this…

Populations and Evolution · Quantitative Biology 2020-02-10 Anna Kraut , Anton Bovier

We study a variant of Hanski's incidence function model that allows habitat patch characteristics to vary over time following a Markov process. The widely studied case where patches are classified as either suitable or unsuitable is…

Probability · Mathematics 2016-09-15 R. McVinish , P. K. Pollett , Y. S. Chan

We consider a finite number of $N$ statistically equal agents, each moving on a finite set of states according to a continuous-time Markov Decision Process (MDP). Transition intensities of the agents and generated rewards depend not only on…

Probability · Mathematics 2025-09-23 Nicole Bäuerle , Sebastian Höfer

We consider a population with non-overlapping generations, whose size goes to infinity. It is described by a discrete genealogy which may be time non-homogeneous and we pay special attention to branching trees in varying environments. A…

Probability · Mathematics 2013-05-22 Vincent Bansaye , Chunmao Huang

The purpose of this work is to establish a central limit theorem that can be applied to a particular form of Markov chains, including the number of descents in a random permutation of $\mathfrak{S}_n$, two-type generalized P{\'o}lya urns,…

Probability · Mathematics 2021-06-09 Olivier Garet

In this paper, we establish a spatial central limit theorem for a large class of supercritical branching, not necessarily symmetric, Markov processes with spatially dependent branching mechanisms satisfying a second moment condition. This…

Probability · Mathematics 2014-04-02 Yan-Xia Ren , Renming Song , Rui Zhang

We consider a class of density-dependent branching processes which generalises exponential, logistic and Gompertz growth. A population begins with a single individual, grows exponentially initially, and then growth may slow down as the…

Probability · Mathematics 2022-04-11 David Cheek

The structure of heterogeneous networks and human mobility patterns profoundly influence the spreading of endemic diseases. In small-scale communities, individuals engage in social interactions within confined environments, such as homes…

Physics and Society · Physics 2025-05-20 Yusheng Li , Yichao Yao , Minyu Feng , Tina P. Benko , Matjaž Perc , Jernej Završnik

In this paper, we are concerned with centered Markov Additive Processes $\{(X_t,Y_t)\}_{t\in\T}$ where the driving Markov process $\{X_t\}_{t\in\T}$ has a finite state space. Under suitable conditions, we provide a local limit theorem for…

Probability · Mathematics 2013-06-25 Loïc Hervé , James Ledoux

This paper presents a law of large numbers result, as the size of the population tends to infinity, of SIR stochastic epidemic models, for a population distributed over $L$ distinct patches (with migrations between them) and $K$ distinct…

Probability · Mathematics 2022-06-24 Raphaël Forien , Guodong Pang , Étienne Pardoux

Epidemic dynamics in a stochastic network of interacting epidemic centers is considered. The epidemic and migration processes are modelled by Markov's chains. Explicit formulas for probability distribution of the migration process are…

Populations and Evolution · Quantitative Biology 2015-05-05 Igor Sazonov , Mark Kelbert

The aim of this paper is to tackle part of the program set by Diekmann et al. in their seminal paper Diekmann et al. (2001). We quote "It remains to investigate whether, and in what sense, the nonlinear determin-istic model formulation is…

Probability · Mathematics 2018-04-16 Philippe Carmona

We prove a central limit theorem for a sequence of random variables whose means are ambiguous and vary in an unstructured way. Their joint distribution is described by a set of measures. The limit is (not the normal distribution and is)…

Probability · Mathematics 2020-07-01 Zengjing Chen , Larry G. Epstein

Density dependent Markov population processes in large populations of size $N$ were shown by Kurtz (1970, 1971) to be well approximated over finite time intervals by the solution of the differential equations that describe their average…

Probability · Mathematics 2014-10-15 A. D. Barbour , Kais Hamza , Haya Kaspi , Fima Klebaner

In this paper, we establish a version of the central limit theorem for Markov-Feller continuous time processes (with a Polish state space) that are exponentially ergodic in the bounded-Lipschitz distance and enjoy a continuous form of the…

Probability · Mathematics 2023-10-09 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

The paper discusses a family of Markov processes that represent many particle systems, and their limiting behaviour when the number of particles go to infinity. The first part concerns model of biological systems: a model for sympatric…

Probability · Mathematics 2011-04-29 Bernt Wennberg

Fleming-Viot type particle systems represent a classical way to approximate the distribution of a Markov process with killing, given that it is still alive at a final deterministic time. In this context, each particle evolves independently…

Probability · Mathematics 2017-09-21 Bernard Delyon , Frédéric Cérou , Arnaud Guyader , Mathias Rousset