Microscopic Markov Chain Approach for Measuring Mobility Driven SARS-CoV-2 Transmission

DOI10.1007/978-3-030-93413-2_26OpenAlexW4206059039MaRDI QIDQ5050327

Ian McCulloh, Nolan E. Phillips, Heather G. Patsolic, Trevor G. Kent, Viveca Pavon-Harr

Publication date: 15 November 2022

Published in: Complex Networks & Their Applications X (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-93413-2_26

zbMATH Keywords

epidemiologyapproximate Bayesian computationSARS-CoV-2microscopic Markov chain approach

Mathematics Subject Classification ID

Epidemiology (92D30) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20)

Uses Software

• ABCpy

Cites Work

• An adaptive sequential Monte Carlo method for approximate Bayesian computation