A quantitative framework for exploring exit strategies from the COVID-19 lockdown

TL;DR

This paper introduces a quantitative framework and a robust numerical algorithm to evaluate COVID-19 exit strategies, enabling policymakers to estimate potential death tolls based on contact increases using reliable death data.

Contribution

It provides a novel mathematical and computational approach for designing COVID-19 exit strategies grounded in quantitative analysis and reliable data.

Findings

The algorithm accurately predicts cumulative deaths for different contact scenarios.

Mathematical results ensure the robustness of the exit strategy assessments.

The framework helps optimize lockdown easing plans based on death projections.

Abstract

Following the highly restrictive measures adopted by many countries for combating the current pandemic, the number of individuals infected by SARS-CoV-2 and the associated number of deaths is steadily decreasing. This fact, together with the impossibility of maintaining the lockdown indefinitely, raises the crucial question of whether it is possible to design an exit strategy based on quantitative analysis. Guided by rigorous mathematical results, we show that this is indeed possible: we present a robust numerical algorithm which can compute the cumulative number of deaths that will occur as a result of increasing the number of contacts by a given multiple, using as input only the most reliable of all data available during the lockdown, namely the cumulative number of deaths.