Approximation methods for analyzing multiscale stochastic vector-borne epidemic models

DOI10.1016/j.mbs.2019.01.003zbMath1409.92242arXiv1806.03778OpenAlexW2964097150WikidataQ91112074 ScholiaQ91112074MaRDI QIDQ669187

Anuj Mubayi, Dominik Reinhold, Liu Zhu, Xin Liu

Publication date: 20 March 2019

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1806.03778

zbMATH Keywords

functional central limit theoremmultiscale analysisquasi-stationary distributionstime to extinctionfast and slow dynamicsfunctional law of large numbersSIS compartment modelvector-borne disease model

Mathematics Subject Classification ID

Epidemiology (92D30)

Related Items (1)

A martingale formulation for stochastic compartmental susceptible-infected-recovered (SIR) models to analyze finite size effects in COVID-19 case studies

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