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Journal Articles Probability, Uncertainty and Quantitative Risk Year : 2022

Multi-patch multi-group epidemic model with varying infectivity

Abstract

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 distinctpatches(withmigrationsbetweenthem)and K distinctgroups(possiblyagegroups). The limit is a set of Volterra-type integral equations, and the result shows the effects of both spatial and population heterogeneity. The novelty of the model is that the infectivity of an infected individual is infection age dependent. More precisely, to each infected individual is attached a random infection-age dependent infectivity function, such that the various random functions attached to distinct individuals are i.i.d. The proof involves a novel construction of a sequence of i.i.d. processes to invoke the law of large numbers for processes in D, by using the solution of a MacKean-Vlasov type Poisson-driven stochastic equation (as in the propagation of chaos theory). We also establish an identity using the Feynman-Kac formula for an adjoint backward ODE. The advantage of this approach is that it assumes much weaker conditions on the random infectivity functions than our earlier work for the homogeneous model in [20], where standard tightness criteria for convergence of stochastic processes were employed. To illustrate this new approach, we first explain the new proof under the weak assumptions for the homogeneous model, and then describe the multipatch-multigroup model and prove the law of large numbers for that model.

Dates and versions

hal-03815881 , version 1 (15-10-2022)

Identifiers

Cite

Raphael Forien, Guodong Pang, Etienne Pardoux. Multi-patch multi-group epidemic model with varying infectivity. Probability, Uncertainty and Quantitative Risk, 2022, 7 (4), pp.333-364. ⟨10.3934/puqr.2022019⟩. ⟨hal-03815881⟩
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