The spread of diseases has been studied for many years, but it receives a particular focus recently due to the outbreak and spread of COVID-19. Studies show that the spread of COVID-19 can be characterized by the Susceptible-Infectious-Recovered-Deceased (SIRD) model with containment coefficients (due to quarantine and keeping social distance). This project aims to apply the machine learning technique to predict the severity of COVID-19 and the effect of quarantine, keeping social distance, working from home, and wearing masks on the transmission of the disease. This work deepens our understanding of disease transmission and reveals the importance of following policies.
@article{arxiv.2204.04364,
title = {Application of machine learning for predicting the spread of COVID-19},
author = {Xiaoxu Zhong and Yukun Ye},
journal= {arXiv preprint arXiv:2204.04364},
year = {2022}
}