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To compare the mental health burden before and during the COVID-19 outbreak and identify the vulnerable groups by sociodemographic factors. Methods: We analyzed repeated cross-sectional data from the Hong Kong Family and Health Information Trend Survey (FHInTS) in 2016 (N = 4036) and 2017 (N = 4051) and the COVID-19 Health Information Survey (CoVHInS) in April 9-23, 2020 (N = 1501) using population-based random samples of general adults by landline telephone and online panel. Stress (Perceived Stress Scale 4), anxiety symptoms (General Anxiety Disorders 2), depression symptoms (Patient Health Questionnaire-2), subjective happiness (4-point Likert item), and sociodemographic factors were collected. Results: Compared with 2016 and 2017, the stress level increased by 28.3%, prevalence of anxiety increased by 42.3%, and the depression symptoms and unhappiness have doubled (all P for trends <0.001) during the COVID-19 outbreak. The increases in stress levels were significantly larger among older and less educated respondents (P for interactions <0.001). Conclusion: Hong Kong had a mental health emergency even with no lockdown and well-managed outbreaks. Older and underprivileged people will suffer most. Public mental health interventions are urgently needed particularly for the older adults and individuals with primary or lower education attainment.

Introduction: Children are widely recognized as a vulnerable population during disasters and emergencies. The COVID-19 pandemic, like a natural disaster, brought uncertainties and instability to the economic development of the society and social distancing, which might lead to child maltreatment. This study aims to investigate whether job loss, income reduction and parenting affect child maltreatment. Methods: We conducted a cross-sectional online survey of 600 randomly sampled parents aged 18 years or older who had and lived with a child under 10 years old in Hong Kong between 29 May to 16 June 2020. Participants were recruited from a random list of mobile phone numbers of a panel of parents. Of 779 recruited target parents, 600 parents completed the survey successfully via a web-based system after obtaining their online consent for participating in the survey. Results: Income reduction was found significantly associated with severe (OR = 3.29, 95% CI = 1.06, 10.25) and very severe physical assaults (OR = 7.69, 95% CI = 2.24, 26.41) towards children. Job loss or large income reduction were also significantly associated with severe (OR= 3.68, 95% CI = 1.33, 10.19) and very severe physical assaults (OR = 4.05, 95% CI = 1.17, 14.08) towards children. However, income reduction (OR = 0.29, 95% CI = 0.15, 0.53) and job loss (OR = 0.47, 95% CI = 0.28, 0.76) were significantly associated with less psychological aggression. Exposure to intimate partner violence between parents is a very strong and significant factor associated with all types of child maltreatment. Having higher levels of difficulty in discussing COVID-19 with children was significantly associated with more corporal punishment (OR = 1.19, 95% CI = 1.05, 1.34), whereas having higher level of confidence in managing preventive COVID-19 behaviors with children was negatively associated with corporal punishment (OR = 0.87, 95% CI = 0.76, 0.99) and very severe physical assaults (OR = 0.74, 95% CI = 0.58, 0.93). Conclusions: Income instability such as income reduction and job loss amplified the risk of severe and very severe child physical assaults but protected children from psychological aggression. Also, confidence in teaching COVID-19 and managing preventive COVID-19 behaviors with children was significantly negatively associated with corporal punishment during pandemic.

The World Health Organization considered the widespread of COVID-19 over the world as a pandemic. There is still a lack of understanding of its origin, transmission, and treatment methods. Understanding the influencing factors of the COVID-19 can help mitigate its spread, but little research on the spatial factors has been conducted. Therefore, this study explores the effects of urban geometry and socio-demographic factors on the COVID-19 cases in Hong Kong. For each patient, the places they visited during the incubation period before going to hospital were identified, and matched with corresponding attributes of urban geometry (i.e., building geometry, road network, greenspace) and socio-demographic factors (i.e., demographic, educational, economic, household and housing characteristics) based on the coordinates. The local cases were then compared with the imported cases using the stepwise logistic regression, the logistic regression with case-control of time, and the least absolute shrinkage and selection operator regression to identify factors influencing local disease transmission. Results show that the building geometry, road network and certain socio-economic characteristics are significantly associated with COVID-19 cases. In addition, the results indicate that urban geometry is playing a more important role than the socio-demographic characteristics in affecting the COVID-19 incidences. These findings provide a useful reference to the government and the general public as to the spatial vulnerability of the COVID-19 transmission and to take appropriate preventive measures in high-risk areas.