Comparison of pandemic intervention policies in several building types using heterogeneous population model

Teddy Lazebnik, Ariel Alexi

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

In a world where pandemics are a matter of time and increasing urbanization of the world's population, governments should be prepared with pandemic intervention policies (IPs) to minimize the crisis's direct and indirect adverse effects while keeping normal life as much as possible. Successful pandemic IPs have to take into consideration the heterogeneous behavior of individuals in different types of buildings and social contexts. In this study, we propose a spatio-temporal, heterogeneous population model and in silico simulation to evaluate pandemic IPs in four types of buildings — home, office, school, and mall. We show that indeed each building type has a unique pandemic spread and therefore a different optimal IP. Moreover, we show that temporal-based IPs (such as mask-wearing) have a similar influence on the pandemic spread in all four building types while spatial-based IPs (such as social distance) highly differ.

Original languageEnglish
Article number106176
JournalCommunications in Nonlinear Science and Numerical Simulation
Volume107
DOIs
StatePublished - Apr 2022
Externally publishedYes

Keywords

  • Agent-based simulation
  • Indoor pandemic
  • Socio-epidemiological model
  • Stochastic spatio-temporal SIR model

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