Containment effort reduction and regrowth patterns of the Covid-19 spreading

TL;DR

This paper presents a macroscopic modeling approach to analyze Covid-19 regrowth patterns after containment efforts are eased, using simple growth models with time-dependent capacity to predict future spread scenarios.

Contribution

It introduces a novel application of time-dependent carrying capacity models to predict Covid-19 regrowth after initial containment, demonstrated on multiple countries.

Findings

Different regrowth scenarios identified for each country.

The model can predict the timing and magnitude of infection resurgence.

Simple growth models effectively capture complex epidemic dynamics.

Abstract

In all Countries the political decisions aim to achieve an almost stable configuration with a small number of new infected individuals per day due to Covid-19. When such a condition is reached, the containment effort is usually reduced in favor of a gradual reopening of the social life and of the various economical sectors. However, in this new phase, the infection spread restarts and a quantitative analysis of the regrowth is very useful. We discuss a macroscopic approach which, on the basis of the collected data in the first lockdown, after few days from the beginning of the new phase, outlines different scenarios of the Covid-19 diffusion for longer time. The purpose of this paper is a demonstration-of-concept: one takes simple growth models, considers the available data and shows how the future trend of the spread can be obtained. The method applies a time dependent carrying capacity, analogously to many macroscopic growth laws in biology, economics and population dynamics. The illustrative cases of Singapore, France, Spain and Italy are analyzed.