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18th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2021 ; 2021-May:218-227, 2021.
Article in English | Scopus | ID: covidwho-1589570

ABSTRACT

The devastating economic and societal impacts of COVID-19 can be substantially compounded by other secondary events that increase individuals' exposure through mass gatherings such as protests or sheltering due to a natural disaster. Based on the Crichton's Risk Triangle model, this paper proposes a Markov Chain Monte Carlo (MCMC) simulation framework to estimate the impact of mass gatherings on COVID-19 infections by adjusting levels of exposure and vulnerability. To this end, a case study of New York City is considered, at which the impact of mass gathering at public shelters due to a hypothetical hurricane will be studied. The simulation results will be discussed in the context of determining effective policies for reducing the impact of multi-hazard generalizability of our approach to other secondary events that can cause mass gatherings during a pandemic will also be discussed. © 2021 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.

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