Modelling the deceleration of COVID-19 spreading

TL;DR

This paper analyzes COVID-19 spread deceleration using a novel SHIR model that incorporates social awareness and hidden susceptible populations, explaining early deceleration trends before lockdowns.

Contribution

It introduces a simplified SHIR model with partial hiding mechanisms to accurately reproduce observed deceleration patterns in multiple countries.

Findings

Deceleration occurred before lockdowns, likely due to increased social awareness.

The SHIR model with partial hiding explains diverse deceleration trends.

Model aligns well with observed COVID-19 data across countries.

Abstract

By characterising the time evolution of COVID-19 in term of its "velocity" (log of the new cases per day) and its rate of variation, or "acceleration", we show that in many countries there has been a deceleration even before lockdowns were issued. This feature, possibly due to the increase of social awareness, can be rationalised by a susceptible-hidden-infected-recovered (SHIR) model introduced by Barnes, in which a hidden (isolated from the virus) compartment $H$ is gradually populated by susceptible people, thus reducing the effectiveness of the virus spreading. By introducing a partial hiding mechanism, for instance due to the impossibility for a fraction of the population to enter the hidden state, we obtain a model that, although still sufficiently simple, faithfully reproduces the different deceleration trends observed in several major countries.