To characterize the association between the protracted biopsychosocial coronavirus disease 2019 (COVID-19) pandemic exposures and incident suicide attempt rates.

Data were from a nationally representative cohort based on electronic health records from January 2013 to February 2021 (N = 852 233), with an interrupted time series study design. For the primary analysis, the effect of COVID-19 pandemic on incident suicide attempts warranting in-patient hospital treatment was quantified by fitting a Poisson regression and modeling the relative risk (RR) and the corresponding 95% confidence intervals (CIs). Scenarios were forecast to predict attempted suicide rates at 10 months after social mitigation strategies. Fourteen sensitivity analyses were performed to test the robustness of the results.

Despite the increasing trend in the unexposed interval, the interval exposed to the COVID-19 pandemic was statistically significant (p < 0.001) associated with a reduced RR of incident attempted suicide (RR = 0.63, 95% CI 0.52–0.78). Consistent with the primary analysis, sensitivity analysis of sociodemographic groups and methodological factors were statistically significant (p < 0.05). No effect modification was identified for COVID-19 lockdown intervals or COVID-19 illness status. All three forecast scenarios at 10 months projected a suicide attempt rate increase from 12.49 (7.42–21.01) to 21.38 (12.71–35.99).

The interval exposed to the protracted mass social trauma of the COVID-19 pandemic was associated with a lower suicide attempt rate compared to the unexposed interval. However, this trend is likely to reverse 10 months after lifting social mitigation policies, underscoring the need for enhanced implementation of public health policy for suicide prevention.

The present study aims to explore whether a relationship exists between the immediate sharp increase in intensive care unit (ICU) admissions and the mortality rates in Italy.

Official epidemiological data on coronavirus disease (COVID-19) were employed. The forward lagged (0, 3, 7, 14 days) daily variations in the number of deaths according to the number of days after the outbreak started and the daily increases in ICU admissions were estimated.

A direct relationship between the sharp increase of ICU admissions and mortality rates has been shown. Furthermore, the analysis of the forward lagged daily variations in the number of deaths showed that an increase in the daily number of ICU admissions resulted in significantly higher mortality after 3, 7, and 14 days. The most pronounced effect was detected after 7 days, with 250 deaths (95% CI: 108.1-392.8) for the highest increase in the ICU admissions, from 100 to 200.

These results would serve as a warning for the scientific community and the health care decision-makers to prevent a quick and out-of-control saturation of the ICU beds in case of a relapse of the COVID-19 outbreak.

The aim of this study was to examine how sociodemographic variables and frequency of media consumption affect hoarding behavior and food insecurity concerns during the coronavirus disease 2019 (COVID-19) pandemic.

A quantitative, nonexperimental, correlational online survey was administered using a convenience sample of 203 participants from the United Kingdom with no medical issues that affected buying behavior during the pandemic to examine perceptions related to food insecurity, and self-reported food hoarding behavior.

Younger adults and lower income groups reported higher food insecurity perceptions and hoarding behaviors. Consuming COVID-19 information from websites was significantly associated with food insecurity perceptions, while information from social media was significantly associated with more food hoarding behaviors.

Younger adults and lower income groups are vulnerable populations from the perspective of food insecurity and hoarding behavior in times of health disasters like pandemics. While social media can play a positively catalytic role during crises, excessive online information and misinformation can contribute negatively to public panic and feelings of insecurity. Implications for disaster preparedness and future research are discussed. The findings suggest that age is the main predictor of food insecurity and hoarding behavior, with younger adults more likely to be affected. They also suggest that people are turning to National Health Service (NHS) websites, which were deemed more trustworthy than social media, to avoid “news fatigue” and avoiding speculation. Suggestions for future research were made, specifically to examine people’s social support during the pandemic to understand its potential link to stockpiling behavior or food insecurity concerns.

Patients with mental illness are vulnerable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection because of behavioural changes associated with cognitive deterioration, especially without their caregivers. While studies have reported that SARS-CoV-2 infection risk and severe clinical outcomes are high among patients with mental illness, there is a lack of quantitative research supporting this claim. This study investigates if SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19)-related death are higher in patients with mental illness than among those without a mental disorder.

A cohort study was conducted using the COVID-19 database of the National Health Insurance Service in South Korea. A total of 123 480 patients aged ⩾20 years who visited a hospital between 1 January 2020 and 30 May 2020 were analysed. Mental disorder diagnoses and types were determined based on 2019 medical records, and a multivariate logistic regression model was used to calculate the odds ratios (ORs) for SARS-CoV-2 infection and deaths.

The ORs for SARS-CoV-2 infection (OR 1.58; 95% CI 1.45–1.71) and COVID-19-related death (OR 2.18; 95% CI 1.57–3.04) were high among patients with mental illness. The OR of SARS-CoV-2 infection was higher among patients with severe mental illness (OR 2.60; 95% CI 2.21–3.06), dementia (OR 1.90; 95% CI 1.62–2.22) and substance use disorder (OR 4.98, 95% CI 3.60–6.88). The OR for COVID-19-related death was high among patients with severe mental illness (OR 3.53; 95% CI 1.82–6.83) and dementia (OR 2.12; 95% CI 1.39–3.22).

Patients with mental illness are at high risk for SARS-CoV-2 infection and COVID-19-related death. Behavioural changes associated with cognitive deterioration and long-term care facility residence increase SARS-CoV-2 infection risk, and severe medical conditions and delayed treatment increase the COVID-19-related mortality risk in patients with mental illness. Patients with mental illness are a priority target population for COVID-19 prevention and treatment, and it is important to plan prevention measures that address their needs.

Conspiracy beliefs are associated with detrimental health attitudes during the coronavirus disease 2019 (Covid-19) pandemic. Most prior research on these issues was cross-sectional, however, and restricted to attitudes or behavioral intentions. The current research was designed to examine to what extent conspiracy beliefs predict health behavior and well-being over a longer period of time.

In this preregistered multi-wave study on a large Dutch research panel (weighted to provide nationally representative population estimates), we examined if conspiracy beliefs early in the pandemic (April 2020) would predict a range of concrete health and well-being outcomes eight months later (December 2020; N = 5745).

The results revealed that Covid-19 conspiracy beliefs prospectively predicted a decreased likelihood of getting tested for corona; if tested, an increased likelihood of the test coming out positive; and, an increased likelihood of having violated corona regulations, deteriorated economic outcomes (job loss; reduced income), experiences of social rejection, and decreased overall well-being. Most of these effects generalized to a broader susceptibility to conspiracy theories (i.e. conspiracy mentality).

These findings suggest that conspiracy beliefs are associated with a myriad of negative life outcomes in the long run. Conspiracy beliefs predict how well people have coped with the pandemic over a period of eight months, as reflected in their health behavior, and their economic and social well-being.

Understanding factors associated with post-discharge sleep quality among COVID-19 survivors is important for intervention development.

This study investigated sleep quality and its correlates among COVID-19 patients 6 months after their most recent hospital discharge.

Healthcare providers at hospitals located in five different Chinese cities contacted adult COVID-19 patients discharged between 1 February and 30 March 2020. A total of 199 eligible patients provided verbal informed consent and completed the interview. Using score on the single-item Sleep Quality Scale as the dependent variable, multiple linear regression models were fitted.

Among all participants, 10.1% reported terrible or poor sleep quality, and 26.6% reported fair sleep quality, 26.1% reported worse sleep quality when comparing their current status with the time before COVID-19, and 33.7% were bothered by a sleeping disorder in the past 2 weeks. After adjusting for significant background characteristics, factors associated with sleep quality included witnessing the suffering (adjusted B = −1.15, 95% CI = −1.70, −0.33) or death (adjusted B = −1.55, 95% CI = −2.62, −0.49) of other COVID-19 patients during hospital stay, depressive symptoms (adjusted B = −0.26, 95% CI = −0.31, −0.20), anxiety symptoms (adjusted B = −0.25, 95% CI = −0.33, −0.17), post-traumatic stress disorders (adjusted B = −0.16, 95% CI = −0.22, −0.10) and social support (adjusted B = 0.07, 95% CI = 0.04, 0.10).

COVID-19 survivors reported poor sleep quality. Interventions and support services to improve sleep quality should be provided to COVID-19 survivors during their hospital stay and after hospital discharge.

The prevalence of serious psychological distress (SPD) was elevated during the COVID-19 pandemic in the USA, but the relationships of SPD during the pandemic with pre-pandemic SPD, pre-pandemic socioeconomic status, and pandemic-related social stressors remain unexamined.

A probability-based sample (N = 1751) of the US population age 20 and over was followed prospectively from February 2019 (T1), with subsequent interviews in May 2020 (T2) and August 2020 (T3). Multinomial logistic regression was used to assess prospective relationships between T1 SPD with experiences of disruption of employment, health care, and childcare at T2. Binary logistic regression was then used to assess relationships of T1 SPD, and socioeconomic status and T2 pandemic-related stressors with T3 SPD.

At T1, SPD was associated with age, race/ethnicity, and household income. SPD at T1 predicted disruption of employment (OR 4.5, 95% CI 1.4–3.8) and health care (OR 3.2, 95% CI 1.4–7.1) at T2. SPD at T1 (OR 10.2, 95% CI 4.5–23.3), low household income at T1 (OR 2.6, 95% CI 1.1–6.4), disruption of employment at T2 (OR 3.2, 95% CI 1.4–7.6), and disruption of healthcare at T2 (OR 3.3, 95% CI 1.5–7.2) were all significantly associated with elevated risk for SPD at T3.

Elevated risk for SPD during the COVID-19 pandemic is related to multiple psychological and social pathways that are likely to interact over the life course. Policies and interventions that target individuals with pre-existing mental health conditions as well as those experiencing persistent unemployment should be high priorities in the mental health response to the pandemic.