The transmission rate of COVID-19 pandemic under different mobility control in Europe

ABSTRACT

COVID-19 pandemic captured the full attention of the world in 2020, and the government declared a series of non-pharmacological interventions (NPIs) to curb the influence of social movement on transmission. In different countries, different policies bring about different results. Quantifying the effect of the movement becomes a vital issue for evaluating the effectiveness of these actions. The transmission rate changes and is hard to computer after altering activity. Therefore, this research sets some European countries as the research objects, collects mobility data and daily cases during some periods, and proposes a mobility-susceptible-exposure-infectious-recovery (M-SEIR) model. Unlike the SEIR model, the movement change is quantified as a variable (σ(t)) and added in the M-SEIR model. With random sampling to get the number of people in different initial states, this research iterates the model. The iterative filtering ensemble adjustment Kalman filter (IF-EAKF) is used to adjust the subsequent iterative results. In the research, it receives the changing trend of parameters and the daily new estimation in the end. Set the first round as the fitting period and repeat the experiment 100 times in the fitting part. The result confirms the feasibility and robustness of the model. In addition, this study makes a reasonable forecast for European countries about the second round. By controlling the strength and the time point of applying non-pharmacological interventions, the research predicts the impact of these actions on the pandemic and provides some suggestions for the deployment of relevant policies in the future. Finally the study eliminates the external factors such as motion and temperature, and obtains an interesting discovery Despite the daily case in the third round higher than that in the first round, the transmission parameter in the former appears lower than that in the latter. The further survey shows that it might be related to vaccination. © 2021, Editorial Department of Journal of University of Science and Technology of China. All rights reserved.