Evaluating the impact of quarantine measures on COVID-19 spread
Renquan Zhang, Yu Wang, Zheng Lv, Sen Pei

TL;DR
This study uses mathematical modeling to evaluate how quarantine measures impacted COVID-19 spread in four major cities, highlighting their critical role in outbreak containment and quantifying their effectiveness through counterfactual simulations.
Contribution
The paper develops a SEIR-type model with quarantine components and couples it with data assimilation to quantify quarantine effectiveness during COVID-19 outbreaks.
Findings
Quarantine of susceptible and exposed individuals is crucial for outbreak control.
Faster isolation of confirmed cases can reduce quarantine rates needed.
Without quarantine, cases could be 22-93 times higher within 40 days.
Abstract
During the early stage of the COVID-19 pandemic, many countries implemented non-pharmaceutical interventions (NPIs) to control the transmission of SARS-CoV-2, the causative pathogen of COVID-19. Among those NPIs, quarantine measures were widely adopted and enforced through stay-at-home and shelter-in-place orders. Understanding the effectiveness of quarantine measures can inform decision-making and control planning during the ongoing COVID-19 pandemic and for future disease outbreaks. In this study, we use mathematical models to evaluate the impact of quarantine measures on COVID-19 spread in four cities that experienced large-scale outbreaks in the spring of 2020: Wuhan, New York, Milan, and London. We develop a susceptible-exposed-infected-removed (SEIR)-type model with a component of quarantine and couple this disease transmission model with a data assimilation method. By calibrating…
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Taxonomy
TopicsCOVID-19 epidemiological studies · SARS-CoV-2 and COVID-19 Research
