Shifts in patterns of help-seeking during the COVID-19 pandemic: The case of Hong Kong's younger generation.

RATIONALE: Help-seeking can convert an individual's bonding social capital into social support, which has been shown to buffer the impact of psychological distress. The younger generation (individuals aged 15-35 years) have been the least likely to actively seek help despite facing a rising burden of mental health problems. COVID-19 pandemic restrictions may have altered their help-seeking behaviors, but the extent of such shift remains little understood, particularly in Asian contexts. OBJECTIVE: To understand how the younger generation's patterns of help-seeking (activation of different combinations of support sources) have shifted in pandemic times, who have experienced the shift, and what explanatory factors are involved. METHODS: Data were obtained from two waves (2019, 2020) of online survey responses by 438 community-dwelling younger generation people in Hong Kong, recruited through the authors' affiliated institutions and territory-wide community outreach organizations. Latent class analysis was conducted on participants' self-reported help-seeking behaviors in each survey wave. Constituents' characteristics in each latent class were examined, and between-wave changes in individuals' class membership were identified. Logistic regressions identified explanatory factors that significantly explained the changes. RESULTS: Three consistent patterns of help-seeking were identified in both survey waves. A major shift was observed for individuals with poorer mental health histories who faced moderate distress. They relied on their family, friends, and partner pre-pandemic, but no longer activated these supports during the pandemic. Posting status updates on social media, along with various communication habits and sociodemographic factors that differed by age group, were associated with this shift. CONCLUSIONS: Shifts in the younger generation's patterns of help-seeking may be an early warning signal to invest additional resources in facilitating help-seeking among the younger generation. Findings also serve as a reminder that public health restrictions may have inadvertent mental health implications that should be considered in future scenarios.

Temporal and spatial trends in suicide-related visits before and during the COVID-19 pandemic in the US, 2018-2021.

BACKGROUND: COVID-19 disproportionately impacted mental health in disadvantaged populations and areas. However, disparities in long-term changes in suicide-related visits across the US are unclear. This retrospective study aims to characterize temporal and spatial changes in suicide-related visits in healthcare settings from 2018 to 2021 in the U.S. METHODS: We use electronic health records for 21,860,370 patients from Healthjump through the COVID-19 Research Database Consortium. Healthjump harmonizes EHR data from over 55 national databases across the US. Suicide ideation and suicide attempts between January 1, 2018 and December 12, 2021 were identified by the diagnosis codes in 6 periods in 2021 compared with the same periods in 2018-2020. RESULTS: There was 30,019 suicidal ideation, and 7392 suicide attempt visits from January 2018 to November 2021. 15-20-year-olds were the most represented age group at 6302 suicide ideation visits (21.0 % of suicide ideation visits) and 1326 suicide attempt visits (17.9 % of suicide attempt visits), followed by suicide-related visits among 60+ years old. Compared with pre-pandemic periods, youth aged 15-20, females, White, non-Hispanic, and English speakers had increased suicide-related visits, especially suicidal ideation (P < 0.05). Suicide attempts with non-medical substances increased to 28.0 % in the first 6 months of the pandemic in 2020, compared with the prior year (21.5 %). COVID-19 patients had increased suicidal ideation in 2020. LIMITATIONS: The EHR data is not nationally representative. CONCLUSIONS: This study found significant and disproportionate increases in suicide related visits over the COVID-19 stages. To prevent the next storms of suicides, future interventions shall accommodate needs among vulnerable groups during and after periods of crisis.

The effects of border control and quarantine measures on the spread of COVID-19.

The rapid expansion of coronavirus disease 2019 (COVID-19) has been observed in many parts of the world. Many newly reported cases of COVID-19 during early outbreak phases have been associated with travel history from an epidemic region (identified as imported cases). For those cases without travel history, the risk of wider spreads through community contact is even higher. However, most population models assume a homogeneous infected population without considering that the imported and secondary cases contracted by the imported cases can pose different risks to community spread. We have developed an "easy-to-use" mathematical framework extending from a meta-population model embedding city-to-city connections to stratify the dynamics of transmission waves caused by imported, secondary, and others from an outbreak source region when control measures are considered. Using the cumulative number of the secondary cases, we are able to determine the probability of community spread. Using the top 10 visiting cities from Wuhan in China as an example, we first demonstrated that the arrival time and the dynamics of the outbreaks at these cities can be successfully predicted under the reproduction number R0 = 2.92 and incubation period τ = 5.2 days. Next, we showed that although control measures can gain extra 32.5 and 44.0 days in arrival time through an intensive border control measure and a shorter time to quarantine under a low R0 (1.4), if the R0 is higher (2.92), only 10 extra days can be gained for each of the same measures. This suggests the importance of lowering the incidence at source regions together with infectious disease control measures in susceptible regions. The study allows us to assess the effects of border control and quarantine measures on the emergence and global spread of COVID-19 in a fully connected world using the dynamics of the secondary cases.