COVID-19 Italian and Europe Epidemic Evolution: A SEIR Model with Lockdown-Dependent Transmission Rate Based on Chinese Data
25 Pages Posted: 6 Apr 2020More...
Background: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that has already taken on pandemic proportions, leading to 191 127 confirmed cases and 7807 deaths up to March 18th, 2020. Understanding the dynamics of the infection and evaluating the effectiveness of the public health lockdown measures introduced in some countries, primarily China and Italy, is crucial for assessing the impact of this new epidemic, which poses a huge threat to health care systems worldwide.
Methods: To this aim, we introduce a lockdown-dependent version of the SEIR model with a transmission rate that decreases over time, as an effect of the protective measures applied by the government authorities. The model is calibrated using data from the evolution of the COVID-19 epidemic in China and subsequently applied to predict the number of infected and recovered individuals in different Italian regions and European countries.
Findings: The lockdown-dependent SEIR model describing the evolution of Chinese COVID-19 epidemic is reasonable with a MAPE of 31%. Its application for the modelling ofpublic health measures gave satisfactory results applied to the Italian context with MAPEs ranging from 36% to 53% in different regions and a consistent improvement of its performance over time. The parameter b, describing the transmission rate, obtained from the model and ranging from 0·82 to 2·71 is comparable to the one derived from COVID-19 literature data ranging from 0·8 to 2·1.
Interpretation: This model allows to estimate the impact of the protective measures implemented by public health authorities with different strengths and timings in different countries. If Community Containment measures are introduced to control the epidemic, their early and fast application seems to guarantee better results in terms of epidemic control.
Funding Statement: None.
Declaration of Interests: The authors declare no competing interests.
Keywords: SEIR; covid19; SARS-CoV-2; coronavirus; prediction; mathematical model; public health; epidemiology; lockdown
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