Depression risk among community-dwelling older people is associated with perceived COVID-19 infection risk: effects of news report latency and focusing on number of infected cases.

Awareness of COVID-19 infection risk and oscillation patterns ('waves') may affect older people's mental health. Empirical data from populations experiencing multiple waves of community outbreaks can inform guidance for maintaining mental health. This study aims to investigate the effects of COVID-19 infection risk and oscillations on depression among community-dwelling older people in Hong Kong.A rolling cross-sectional telephone survey method was used. Screening for depression risk was conducted among 8,163 older people (age ≥ 60) using the Patient Health Questionnaire-2 (PHQ-2) from February to August 2020. The relationships between PHQ-2, COVID-19 infection risk proxies - change in newly infected cases and effective reproductive number (Rt), and oscillations - stage of a 'wave' reported in the media, were analysed using correlation and regression.8.4% of survey respondents screened positive for depression risk. Being female (ß = .08), having a pre-existing mental health issue (ß = .21), change in newly infected cases (ß = .05), and screening during the latency period before the media called out new waves (ß = .03), contributed to higher depression risk (R2 = .06, all p <.01).While depression risk does not appear alarming in this sample, our results highlight that older people are sensitive to reporting of infection, particularly among those with existing mental health needs. Future public health communication should balance awareness of infection risks with mental health protection.

Depressive Symptoms and Coping Strategies in Community-Dwelling Older People Amidst the COVID-19 Pandemic: A Mixed-Method Study.

This study aimed to examine depressive symptoms of community-dwelling older people amidst COVID-19 and explore how naturally occurring coping strategies were associated with depression. A mixed-method cross-sectional telephone survey was conducted with 375 older people aged 60 years and above between March and May 2020 in Hong Kong. Trained social workers interviewed participants and assessed depressive symptoms with the Patient Health Questionnaire-9 (PHQ-9). Attribute coding and thematic analysis were adopted for qualitative data analyses. Generalized linear models (GLM) were used to examine the effects of demographics, self-reported risk factors and coping strategies on PHQ-9 scores. Participants' average PHQ-9 score was 1.9 (SD = 2.9), suggesting a low risk for depression in general. Over half of the participants reported adaptive coping strategies, including learning new things, staying physically, mentally, and socially active, and having a positive mind-set. GLM results indicated that living with family members (other than spouse) and/or others, maladaptive coping, and self-reported risk factors were significantly associated with higher PHQ-9 scores, while adaptive coping was significantly associated with lower PHQ-9 scores. Our study contributed to the growing literature on older people's resilience and adaptive coping during the pandemic, and the results may have implications for mental health promotion and community care.

The Moderating Role of Community Capacity for Age-friendly Communication in Mitigating Anxiety of Older Adults During the COVID-19 Infodemic: Cross-sectional Survey.

Background: Older adults were perceived as a vulnerable group during the COVID-19 pandemic due to the health and mental health challenges they faced. The pandemic was accompanied by an "infodemic" of overabundant and questionable information that has affected older adults' mental health. As the infodemic and ageist narratives were prevalent online, more anxiety symptoms have been induced among older adults who used social media. Age-friendly communication, advocated by the World Health Organization's Age-friendly City (AFC) guide, could be an antidote by providing tailored information via appropriate channels for older adults. Objective: This study investigated the role of community capacity for age-friendly communication in mitigating anxiety during the pandemic. We hypothesized that age-friendly communication would moderate the effects of infection risks and social media use on anxiety. A double-moderating effect was hypothesized in the context of diminished trust in traditional media. Methods: Data were collected from a cross-sectional telephone survey conducted in Hong Kong in 2020. Older adults (N=3421, age≥60 years) were interviewed about their well-being and daily lives. Community capacity for age-friendly communication was measured in a living district-based evaluation. It had 2 components: the reach of appropriate information to older adults (AFC-Information) and the age-friendliness of communication technologies (AFC-Communication Technology) in the community. We tested the hypothesized moderation and double-moderation effects with ordinary least squares regressions. Results: Perceived COVID-19 infection risk (b=0.002, P=.02) and use of social media for COVID-19 information (b=0.08, P=.04) were associated with more anxiety symptoms. The effect of using social media was moderated by AFC-Information (b=-0.39, P=.002) and AFC-Communication Technology (b=-1.06, P<.001), and the effect of perceived COVID-19 infection risk was moderated by AFC-Information (b=-0.03, P=.002) and AFC-Communication Technology (b=-0.05, P<.001). Lower trust in traditional media exacerbated anxiety symptoms associated with social media use (b=-0.08, P=.02). Higher AFC-Information alleviated this moderation effect (AFC-Information × media trust b=-0.65, P<.001; AFC-Information × social media use b=-2.18, P<.001; 3-way interaction b=0.40, P=.003). Conclusions: Our findings highlight the role of community age-friendly communication in mitigating anxiety related to the infodemic. Although using social media may have exacerbated the impact of the infodemic on older adults, it has the potential to deliver timely information for an adequate health response. Although the amplifying effects of low media trust was associated with social media use, age-friendly communication determined its strength. Instead of discouraging the use of digital technologies for COVID-19 information, efforts should be made in tailoring information and communication technologies in local communities for older adults.

COVID-19 Outbreaks and Control Measures Are Associated With Depression Risk Among Older Adults

Local COVID-19 outbreaks and infection control measures may affect mental health in older persons. This study aims to investigate the effects of COVID-19 outbreaks and control measures on depression risk in community-dwelling older adults in Hong Kong. With rolling cross-sectional design, telephone screenings for depressive risk were conducted among 8163 older people using Patient Health Questionnaire-2 (PHQ-2) from February to September 2020. COVID-19 outbreaks across thirty weeks were measured using real-time effective reproductive number (Rt), infected new cases, and change of infected new cases by week. Infection control measures were assessed using four policy indices, including government response, government stringency, containment and health, and economic support. Linear regressions were used to test the associations of depression risk with COVID-19 outbreaks and control measures. We found that being female and higher Rt were associated with higher depression risk in the overall sample. In older adults without pre-existing mental health issues, higher depression risk were related to older age (t=-1.974, 95%CI[-0.006, 0.000], p<0.05), a higher level of government stringency (t=2.954, 95%CI[0.007, 0.033], p<0.01), and less stringent containment and health-related policy (t=-2.599, 95%CI[-0.041, -0.006], p<0.01). In older adults with pre-existing mental health issues, greater changes in newly infected cases were related to higher depression risk (t=2.813, 95%CI[0.002, 0.010], p<0.01). In conclusion, the effects of COVID-19 infection risk and control measures on depression risk differ among older Chinese by pre-existing mental health issues. Future public health communication could build on resilience to balance awareness of infection risks and mental health risks in older persons.

Consuming Information Related to COVID-19 on Social Media Among Older Adults and Its Association With Anxiety, Social Trust in Information, and COVID-Safe Behaviors: Cross-sectional Telephone Survey.

BACKGROUND: COVID-19-related information on social media is overabundant and sometimes questionable, resulting in an "infodemic" during the pandemic. While previous studies suggest social media usage increases the risk of developing anxiety symptoms, how induced anxiety affects attitudes and behaviors is less discussed, let alone during a global pandemic. Little is known about the relationship between older adults using social media during a pandemic and their anxiety, their attitudes toward social trust in information, and behaviors to avoid contracting COVID-19. OBJECTIVE: The goal of this study was to investigate the associations between using social media for COVID-19-related information and anxiety symptoms as well as the mediation effect of anxiety symptoms on social trust in information and COVID-safe behaviors among older adults. METHODS: A cross-sectional telephone survey was conducted in Hong Kong between May and August 2020. A rapid warm-call protocol was developed to train social workers and volunteers from participant nongovernmental organizations to conduct the telephone surveys. Questions related to COVID-safe behaviors, social trust in information, social media use, anxiety and depressive symptoms, and sociodemographic information were asked. The number of confirmed COVID-19 cases at the community level was used to account for the risk of contracting COVID-19. Ordinary least squares regressions examined the associations between social media use and anxiety symptoms, and how they were associated with social trust in information and COVID-safe behaviors. Structural equation modeling further mapped out these relationships to identify the mediation effects of anxiety symptoms. RESULTS: This study collected information regarding 3421 adults aged 60 years and older. Use of social media for COVID-19-related information was associated with more anxiety symptoms and lower social trust in information but had no significant relationship with COVID-safe behaviors. Anxiety symptoms predicted lower social trust in information and higher COVID-safe behaviors. Lower social trust in information was predicted by using social media for COVID-19 information, mediated by anxiety symptoms, while no mediation effect was found for COVID-safe behaviors. CONCLUSIONS: Older adults who rely on social media for COVID-19-related information exhibited more anxiety symptoms, while showing mixed effects on attitudes and behaviors. Social trust in information may be challenged by unverified and contradictory information online. The negligible impact on COVID-safe behaviors suggested that social media may have caused more confusion than consolidating a consistent effort against the pandemic. Media literacy education is recommended to promote critical evaluation of COVID-19-related information and responsible sharing among older adults.

Prediction on transmission trajectory of COVID-19 based on particle swarm algorithm.

This study aimed to predict the transmission trajectory of the 2019 Corona Virus Disease (COVID-19). The particle swarm optimization (PSO) algorithm was combined with the traditional susceptible exposed infected recovered (SEIR) infectious disease prediction model to propose a SEIR-PSO prediction model on the COVID-19. In addition, the domestic epidemic data from February 25, 2020 to March 20, 2020 in China were selected as the training set for analysis. The results showed that when the conversion rate, recovery rate, and mortality rate of the SEIR-PSO model were 1/5, 1/15, and 1/13, its predictive effect on the number of people diagnosed with COVID-19 was the closest to the real data; and the SEIR-PSO model showed a mean-square errors (MSE) value of 1304.35 and mean absolute error (MAE) value of 1069.18, showing the best prediction effect compared with the susceptible infectious susceptible (SIS) model and the SEIR model. In contrary to the standard particle swarm optimization (SPSO) and linear weighted particle swarm optimization (LPSO), which were two classical improved PSO algorithms, the reliability and diversity of the SEIR-PSO model were higher. In summary, the SEIR-PSO model showed excellent performance in predicting the time series of COVID-19 epidemic data, and showed reliable application value for the prevention and control of COVID-19 epidemic.