A four-compartment model for the COVID-19 infection—implications on infection kinetics, control measures, and lockdown exit strategies

摘要

Objective To analyse the impact and repercussions of the surge in healthcare demand in response to the COVID-19 pandemic, assess the potential effectiveness of various infection/disease control measures, and make projections on the best approach to exit from the current lockdown. Design A four-compartment model was constructed for SARS-CoV-2 infection based on the Wuhan data and validated with data collected in Italy, the UK, and the US. The model captures the effectiveness of various disease suppression measures in three modifiable factors: (a) the per capita contact rate (β) that can be lowered by means of social distancing, (b) infection probability upon contacting infectious individuals that can be lowered by wearing facemasks, personal hygiene, etc., and (c) the population of infectious individuals in contact with the susceptible population, which can be lowered by quarantine. The model was used to make projections on the best approach to exit from the current lockdown. Results The model was applied to evaluate the epidemiological data and hospital burden in Italy, the UK, and the US. The control measures were identified as the key drivers for the observed epidemiological data through sensitivity analyses. Analysing the different lockdown exit strategies showed that a lockdown exit strategy with a combination of social separation/general facemask use may work, but this needs to be supported by intense monitoring which would allow re-introduction/tightening of the control measures if the number of new infected subjects increases again. Conclusions and relevance Governments should act early in a swift and decisive manner for containment policies. Any lockdown exit will need to be monitored closely, with regards to the potential of lockdown reimplementation. This mathematical model provides a framework for major pandemics in the future. Introduction The novel coronavirus (SARS-CoV-2) and the infection-related disease (COVID-19) were declared a public health emergency of international concern by the World Health Organization in early 2020, and have since grown into a pandemic. , COVID-19 has created an unprecedent global health problem, for which most healthcare systems were not well prepared. Policies such as case isolation, social distancing, travel restriction, and quarantine represent the key measures adopted by various governments to control the outbreak. However, such measures also carry significant impact to individual psychological well-being and social/economic costs. Many epidemiological models have been proposed to describe the dynamics of the transmission and simulate the course of the outbreak. However, few studies have assessed the impact of the effectiveness of various measures in the control of viral spread. A four-compartment model was established to describe the SARS-CoV-2 infection, assess the potential effectiveness of various infection control measures, and make projections on the best approach to exit lockdown. Methods The population is divided into the following states: susceptible subjects (S), had close contacts (C, those exposed to infected subjects/pathogen but not necessarily infected), latent (E, infected and infectious but asymptomatic), infected (I; and symptomatic), recovered (V), and dead (D) (Fig. and ). Figure 1. Flow diagram of the model. The four-compartment model of disease transmission incorporates the viral transmissibility and the impact of quarantine and social distancing. The population is divided into the following states: susceptible subject(s) (S), had close contact(s) (C, those that were exposed to the infected subjects/pathogen but not necessarily infected), latent (E, infected and infectious but asymptomatic), infected (I; and symptomatic), recovered (V), and dead (D). CM is the portion of the contact cases that are missed by contact tracing and will not be quarantined. Individuals in states C, CM, and C.