2020arXiv (Cornell University)Open access

Is Time to Intervention in the COVID-19 Outbreak Really Important? A Global Sensitivity Analysis Approach

Emanuele Borgonovo, Xuefei Lu

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Abstract

Italy has been one of the first countries timewise strongly impacted by the COVID-19 pandemic. The adoption of social distancing and heavy lockdown measures is posing a heavy burden on the population and the economy. The timing of the measures has crucial policy-making implications. Using publicly available data for the pandemic progression in Italy, we quantitatively assess the effect of the intervention time on the pandemic expansion, with a methodology that combines a generalized susceptible-exposed-infectious-recovered (SEIR) model together with statistical learning methods. The modeling shows that the lockdown has strongly deviated the pandemic trajectory in Italy. However, the difference between the forecasts and real data up to 20 April 2020 can be explained only by the existence of a time lag between the actual issuance date and the full effect of the measures. To understand the relative importance of intervention with respect to other factors, a thorough uncertainty quantification of the model predictions is performed. Global sensitivity indices show that the the time of intervention is 4 times more relevant than quarantine, and eight times more important than intrinsic features of the pandemic such as protection and infection rates. The relevance of their interactions is also quantified and studied.

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Italy has been one of the first countries timewise strongly impacted by the COVID-19 pandemic. The adoption of social distancing and heavy lockdown measures is posing a heavy burden on the population and the economy. The timing of the measures has crucial policy-making implications. Using publicly available data for the pandemic progression in Italy, we quantitatively assess the effect of the intervention time on the pandemic expansion, with a methodology that combines a generalized susceptible-exposed-infectious-recovered (SEIR) model together with statistical learning methods. The modeling shows that the lockdown has strongly deviated the pandemic trajectory in Italy. However, the difference between the forecasts and real data up to 20 April 2020 can be explained only by the existence of a time lag between the actual issuance date and the full effect of the measures. To understand the relative importance of intervention with respect to other factors, a thorough uncertainty quantification of the model predictions is performed. Global sensitivity indices show that the the time of intervention is 4 times more relevant than quarantine, and eight times more important than intrinsic features of the pandemic such as protection and infection rates. The relevance of their interactions is also quantified and studied.

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Available abstract

Italy has been one of the first countries timewise strongly impacted by the COVID-19 pandemic. The adoption of social distancing and heavy lockdown measures is posing a heavy burden on the population and the economy. The timing of the measures has crucial policy-making implications. Using publicly available data for the pandemic progression in Italy, we quantitatively assess the effect of the intervention time on the pandemic expansion, with a methodology that combines a generalized susceptible-exposed-infectious-recovered (SEIR) model together with statistical learning methods. The modeling shows that the lockdown has strongly deviated the pandemic trajectory in Italy. However, the difference between the forecasts and real data up to 20 April 2020 can be explained only by the existence of a time lag between the actual issuance date and the full effect of the measures. To understand the relative importance of intervention with respect to other factors, a thorough uncertainty quantification of the model predictions is performed. Global sensitivity indices show that the the time of intervention is 4 times more relevant than quarantine, and eight times more important than intrinsic features of the pandemic such as protection and infection rates. The relevance of their interactions is also quantified and studied.

Key concepts: Coronavirus disease 2019 (COVID-19), Outbreak, Sensitivity (control systems), 2019-20 coronavirus outbreak, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Intervention (counseling), Pandemic, Virology

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