人群移動和接觸率在形成傳染病（例如COVID-19）的傳播模式方面起著根本作用。因此，流動資料被用作衡量干預措施有效性的代理，例如留在家中的命令和其他社會疏遠措施。這一主題旨在建立人類流動與疾病傳播之間的關係，以便在不同的干預情況下類比疾病傳播。由於流動性與個人的年齡及其社會經濟地位密切相關，因此應調查與移動性和移動網路有關的更多細節。這些發現可能有助於制定針對某些社區和人群的更相關的公共衛生政策。

另一方面，關於疾病傳播的錯誤資訊的傳播可能會影響人們的預防/健康行為、戰勝疾病的信心和對政府的信任。應充分瞭解這種動態，以促進預防性決策。 

項目：

評估和實施非藥物干預措施以避免COVID-19反彈: 利用大資料和小資料考慮人的移動、接觸和行為變化 (2021-2022)
項目來源：香港研資局合作研究基金（C4139-20GF）
專案統籌者：黃波教授

In this proposed project, we aim to overcome the abovementioned problems by developing methods to derive social contacts directly from anonymized population-level mobility data.

We will thus measure the intensity of physical distancing in terms of mobility data and derived social contacts data, using Wuhan and other Chinese cities as study areas. We also propose to conduct online surveys to collect data on human contact and behavior before, during and after the COVID-19 outbreak. These data will be integrated with the above big mobility data and incorporated into a modified susceptible-exposed-infectious-recovered (SEIR) model to simulate the effect of various scenarios of government interventions. 

This proposed project will ultimately provide a novel methodology by which spatial mobility and human behavioral data can be processed and analyzed to yield a more precise modeling of COVID-19 transmission, and strategies and evidence to guide COVID-19 interventions and preparedness across the world during the post-lockdown period.

新冠病毒資訊在四個華人社會傳播之比較研究： (假)傳播、信任與資訊環境如何影響華人對抗疫情 (2021-2023)
項目來源：香港研資局合作研究基金（C4158-20GF）
專案統籌者：魏然教授

A hallmark of the COVID-19 global pandemic is rising infodemics, which refers to “information epidemics” or “epidemics of rumors”—“the rapid dispersal of information of all kinds, including rumors, gossip, and unreliable information” spread “instantly and internationally” through communication technologies such as mobile phones, social media, and the Internet. The “over-abundance of information” that makes it hard for the general public “to find trustworthy sources and reliable guidance when they need it”. Infodemics often appear to be mis, dis and mal-information. Like a virus itself, infodemics can cause public distrust, panic, and fear. This project aims to take a holistic approach to examine the emergence and spread of false and misleading information about the COVID-19 pandemic on digital media in four Chinese societies: Mainland China, Hong Kong, Singapore and Taiwan. It also explores how some widely diffused informedic messages on social media affect the publics’ perceived risks and measures taken to protect themselves. Methodologically, we combine big data analytics with social scientific research methods such as surveys and focus groups to explore, clarify, and theorize the dynamics of infodemic diffusion during the COVID-19 pandemic, which includes the dimensions of emergence, diffusion, and consequences. Based on the proposed model and empirical evidences, the deliverables of this project include (1) valuable and immediate policy suggestions to spot and contain infodemic messages at the early stage of a public health crisis; (2) a user-friendly online application to monitor future emerging infectious diseases; (3) policy recommendations for containing and countering the COVID-19 infodemics with correction messages.

共同負責人：