City-Level Structured Prediction and Simulation Model of COVID-19

It is important for social public security and urban management to explore the spread of infectious diseases. A city-level structured prediction and simulation model for COVID-19 is proposed. This model is consisted of SEIR and social network model on the basis of latest infectious disease dynamics theory and real geographic networks. The prediction region is divided into multiple levels. Specifically, a bipartite network is applied to simulate the relationship between public facilities and community nodes at the macro level, and a modified SEIR is applied to simulate the infection within nodes at the micro level. Besides, intelligent agent is applied to track the individual transmission process. The contrast experimental results based on the confirmed and cursed cases of Wuhan and Beijing in 2020 published by National Health Commission, show that the proposed model has better flexibility and higher accuracy, and reflects the distribution and movement of people more directly. © 2022 Institute of Computing Technology. All rights reserved.

Estimating the Optimal Parameters of SEIR model for Predicting the Trajectory of COVID-19 Pandemic in Japan

A system that uses the susceptible-exposed-infectious-removed (SEIR) model and some methods to predict COVID-19 (SARS-Cov-2) trajectory of the pandemic which is currently prevalent. This paper reports on how to estimate the optimal parameters of the SEIR model, which can predict the pandemics of infectious diseases. © 2021 IEEE.