As the COVID-19 swept cross the world for an entire year, faculties and students of Department of Media and Communication (COM), City University of Hong Kong, contribute their wisdom in the global fight against the pandemic.
Prof. Christine HUANG and Dr. Guanxiong HUANG serve as Co-Principal Investigators in a major grant (over HK$3 million) under the One-off Collaborative Research Fund Coronavirus Disease and Novel Infectious Disease Exercise 2020/21. The funded project, titled (Mis)communication, Trust, and Information Environments: A Comparative Study of the COVID-19 Infodemics in Four Chinese Societies, will examine the emergence, diffusion, and consequences of misinformation and disinformation during the pandemic across mainland China, Hong Kong, Taiwan, and Singapore. The project is expected to provide policy recommendations for containing and countering infodemics in public health crises.
Dr. Fei SHEN and his PhD advisees studied the effects of government trust, media use, and media trust on preventive behaviors during COVID-19 in China. They found that government trust increased both officially recommended and excessive prevention and that use of central government media and use of WeChat are positively related to compliance with health behaviors, while use of local media and use of Weibo are negatively related to the levels of prevention. In addition, trust in the media amplified the effects of media use on prevention. Their studies have been published in Preventive Medicine  and been accepted by Journal of Health Psychology .
Dr. Xiaofan LIU, teamed with Prof. Xiao-Ke XU (Dalian Minzu University) and Prof. Ye WU (Beijing Normal University), released a massive dataset containing detailed epidemiological information of more than 14,000 COVID-19 cases on Scientific Data . Over the past year, the dataset has been proven a valuable asset for pandemic research and supported publications in many top journals, including Science, Clinical Infectious Disease, and Emerging Infectious Disease. The Chinese version of this dataset has also been released by The Paper (澎湃) press for a data journalism competition. The research team also studied the mechanism, development, and control of the pandemic from multiple perspectives such as data mining, mathematical modeling, and computer simulation. Their results have been published in journals such as Clinical Infectious Disease and Global Media Studies [4-8].
PhD students Yanqing SUN, Jeffry OKTAVIANUS, Sai WANG and Fangcao LU published their study on Health Communication . This study tries to answer the question of which factors motivate social media users to correct COVID-19 related misinformation when they see it circulating online. Through an experiment among U.S. citizens, the authors found that when people perceive that being influenced by COVID-19 related misinformation will bring serious consequences to others, they are likely to anticipate that they will feel guilty if they do nothing to stop the dissemination of misinformation. This feeling of guilt further motivates people to take actions and correct the misinformation. Overall, this study provides important practical implications for health institutions and campaign planners, as well as for willing and informed social media users, particularly in terms of the message design. When posting corrective messages about misinformation, it would be beneficial to stress the threat of misinformation to others. These corrective messages can trigger appropriate emotions and may be effective in motivating informed audiences to rebut misinformation together.
A list of COM’s researches on COVID-19 is appended.
 Min, C.†, Shen, F., Yu, W.†, & Chu, Y. (2020). The relationship between government trust and preventive behaviors during the COVID-19 pandemic in China: Exploring the roles of knowledge and negative emotion. Preventive Medicine, 141, 106288.
 Wu, Y. & Shen, F.* (accepted). Exploring the impacts of traditional media use, social media use, and media trust on health behaviors during the COVID-19 pandemic in China. Journal of Health Psychology.
 Liu, X. F., Xu, X. K.*, & Wu, Y.* (2021). Mobility, Exposure, and Epidemiological Timelines of COVID-19 Infections in China outside Hubei Province. Scientific Data, 8, 54.
 Zhang, L., Zhu, J., Wang, X., Yang, J., Liu, X. F.*, & Xu, X. K.* (2021). Characterizing COVID-19 transmission: incubation period, reproduction rate, and multiple-generation spreading. Frontiers in Physics, 8, 589963.
 Xu, X-K.†, Liu, X. F.†, Wu, Y.†, Ali, S. T.†, Du, Z.†, Bosetti, P., Lau, E. H. Y., Cowling, B. J., & Wang, L.* (2020). Reconstruction of Transmission Pairs for novel Coronavirus Disease 2019 (COVID-19) in China: Estimation of Super-spreading Events, Serial Interval, and Hazard of Infection. Clinical Infectious Diseases, 71(12), 3163—3167.
 Sun, H. C., Liu, X. F., Xu, X. K.*, & Wu, Y.* (2020). Analysis of COVID-19 spreading and prevention strategy in schools based on continuous infection model. Acta Physica Sinica, 69(24), 240201.
 Cao, W. J., Liu, X. F., Han, Z., Feng, X.*, Zhang, L.*, Liu, X. F., Xu, X-K. & Wu, Y. (2020). Statistical analysis and autoregressive modeling of confirmed coronavirus disease 2019 epidemic cases. Acta Physica Sinica, 69(9), 090203.
 刘肖凡, 吴晔, & 许小可(2020). 媒体在流行病暴发事件中的干预作用: 基于传染病模型理论和新型冠状病毒疫情案例的分析. 全球传媒学刊, 7(1), 169-185.
 Sun, Y., Oktavianus, J., Wang, S., & Lu, F. (accepted). The role of influence of presumed influence and anticipated guilt in evoking social correction of COVID-19 misinformation. Health Communication.
†: equally contributed; *: corresponding