Assessment of the Benefits of Targeted Interventions for Pandemic Control in China Based on Machine Learning Method and Web Service for COVID-19 Policy Simulation

• Published in: Biomedical and environmental sciences Vol. 35; no. 5; pp. 412 - 418
• Main Authors: WU, Jie Wen, JIAO, Xiao Kang, DU, Xin Hui, JIAO, Zeng Tao, LIANG, Zuo Ru, PANG, Ming Fan, JI, Han Ran, CHENG, Zhi Da, CAI, Kang Ning, QI, Xiao Peng
• Format: Journal Article
• Language: English
• Published: China Elsevier B.V 01.05.2022; Center for Global Public Health, Chinese Center for Disease Control and Prevention, Beijing 102206, China%Yidu Cloud (Beijing) Technology Co., Ltd., Beijing 100083, China; The Editorial Board of Biomedical and Environmental Sciences. Published by Elsevier (Singapore) Pte Ltd
• Subjects: China - epidemiology; Compartment model; COVID-19; COVID-19 - epidemiology; COVID-19 - prevention & control; Humans; Intervention policy simulation; Machine Learning; Pandemics - prevention & control; Policy; Policy Forum; Reproducibility of Results; SARS-CoV-2; China; COVID-19; Compartment model; Intervention policy simulation; Machine learning; Machine learning; Compartment model; Intervention policy simulation
• ISSN: 0895-3988; 2214-0190
• DOI: 10.3967/bes2022.057

Taking the Chinese city of Xiamen as an example, simulation and quantitative analysis were performed on the transmissions of the Coronavirus Disease 2019 (COVID-19) and the influence of intervention combinations to assist policymakers in the preparation of targeted response measures. A machine learning model was built to estimate the effectiveness of interventions and simulate transmission in different scenarios. The comparison was conducted between simulated and real cases in Xiamen. A web interface with adjustable parameters, including choice of intervention measures, intervention weights, vaccination, and viral variants, was designed for users to run the simulation. The total case number was set as the outcome. The cumulative number was 4,614,641 without restrictions and 78 under the strictest intervention set. Simulation with the parameters closest to the real situation of the Xiamen outbreak was performed to verify the accuracy and reliability of the model. The simulation model generated a duration of 52 days before the daily cases dropped to zero and the final cumulative case number of 200, which were 25 more days and 36 fewer cases than the real situation, respectively. Targeted interventions could benefit the prevention and control of COVID-19 outbreak while safeguarding public health and mitigating impacts on people's livelihood.