Projecting and comparing non-pharmaceutical interventions to contain COVID-19 in major economies
Jingjing He, Xuefei Guan, Xiaochang Duan, Tian Shen, Jing Lin

TL;DR
This study introduces a dynamic pandemic model incorporating policy intensity factors to evaluate and project the impact of non-pharmaceutical interventions on COVID-19 spread across major economies.
Contribution
It develops a variable-rate VR-SEIR model that quantitatively links NPI stringency with pandemic dynamics and projections.
Findings
PIFs correlate with NPI stringency
Model accurately fits and projects pandemic data
Provides quantitative impact estimates of NPIs
Abstract
Non-pharmaceutical interventions (NPIs) such as quarantine, self-isolation, social distancing, and virus-contact tracing can greatly reduce the spread of the virus during a pandemic. In the wave of the COVID-19 pandemic, many countries have implemented various NPIs for infection control and mitigation. However, the stringency of the NPIs and the resulting impact among different countries remain unclear due to the lack of quantitative factors. In this study we took a further step to incorporate the effect of the NPIs into the pandemic dynamics model using the concept of policy intensity factor (PIF). This idea enables us to characterize the transition rates as time varying quantities instead of constant values, and thus capturing the dynamical behavior of the basic reproduction number variation in the pandemic. By leveraging a great amount of data reported by the governments and the…
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Taxonomy
TopicsCOVID-19 epidemiological studies · COVID-19 Pandemic Impacts · COVID-19 Clinical Research Studies
