Years of life lost due to the psychosocial consequences of COVID-19 mitigation strategies based on Swiss data.

BACKGROUND: The pandemic caused by coronavirus disease 2019 (COVID-19) has forced governments to implement strict social mitigation strategies to reduce the morbidity and mortality from acute infections. These strategies, however, carry a significant risk for mental health, which can lead to increased short-term and long-term mortality and is currently not included in modeling the impact of the pandemic. METHODS: We used years of life lost (YLL) as the main outcome measure, applied to Switzerland as an example. We focused on suicide, depression, alcohol use disorder, childhood trauma due to domestic violence, changes in marital status, and social isolation, as these are known to increase YLL in the context of imposed restriction in social contact and freedom of movement. We stipulated a minimum duration of mitigation of 3 months based on current public health plans. RESULTS: The study projects that the average person would suffer 0.205 YLL due to psychosocial consequence of COVID-19 mitigation measures. However, this loss would be entirely borne by 2.1% of the population, who will suffer an average of 9.79 YLL. CONCLUSIONS: The results presented here are likely to underestimate the true impact of the mitigation strategies on YLL. However, they highlight the need for public health models to expand their scope in order to provide better estimates of the risks and benefits of mitigation.

Attempted suicide rates before and during the COVID-19 pandemic: interrupted time series analysis of a nationally representative sample.

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

Rates of Spontaneous Abortion in Israel Before and During the COVID-19 Pandemic.

This cross-sectional study uses electronic health record data to compare monthly incidence rates of spontaneous abortion in Israel before and during the COVID-19 pandemic.

Increased incident rates of antidepressant use during the COVID-19 pandemic: interrupted time-series analysis of a nationally representative sample.

BACKGROUND: The COVID-19 pandemic has been associated with increased levels of depression and anxiety with implications for the use of antidepressant medications. METHODS: The incident rate of antidepressant fills before and during the COVID-19 pandemic were compared using interrupted time-series analysis followed by comprehensive sensitivity analyses on data derived from electronic medical records from a large health management organization providing nationwide services to 14% of the Israeli population. The dataset covered the period from 1 January 2013 to 1 February 2021, with 1 March 2020 onwards defined as the period of the COVID-19 pandemic. Forecasting analysis was implemented to test the effect of the vaccine roll-out and easing of social restrictions on antidepressant use. RESULTS: The sample consisted of 852 233 persons with a total antidepressant incident fill count of 139 535.4 (total cumulative rate per 100 000 = 16 372.91, 95% CI 16 287.19-16 459.01). We calculated the proportion of antidepressant prescription fills for the COVID-19 period, and the counterfactual proportion for the same period, assuming COVID-19 had not occurred. The difference in these proportions was significant [Cohen's h = 10-3 (0.16), 95% CI 10-3 ( - 0.71 to 1.03)]. The pandemic was associated with a significant increase in the slope of the incident rate of antidepressant fills (slope change = 0.01, 95% CI 0.00-0.03; p = 0.04) and a monthly increase of 2% compared to the counterfactual (the estimated rate assuming no pandemic occurred). The increased rate was more pronounced in women, and was not modified by lockdown on/off periods, socioeconomic or SARS-CoV-2 status. The rate of observed antidepressant fills was similar to that forecasted under the assumption of ongoing COVID-19 distress. CONCLUSION: These findings underscore the toll of the pandemic on mental health and inform mental health policy and service delivery during and after implementing COVID-19 attenuation strategies.

Biopsychosocial exposure to the COVID-19 pandemic and the relative risk of schizophrenia: Interrupted time-series analysis of a nationally representative sample.

BACKGROUND: Studies of COVID-19 pandemic biopsychosocial exposure and schizophrenia risk showed contradictory results, were undertaken early in the pandemic, and did not consider lockdowns or COVID-19 infection. Hence, we examined the association between COVID-19 biopsychosocial exposure and incident schizophrenia. METHODS: An interrupted time-series study design was implemented based on Israeli electronic health records from 2013 to 2021 with national coverage. The period coinciding with the COVID-19 pandemic biopsychosocial exposures from March 2020 to February 2021 was classified as exposed, otherwise unexposed. The effect of the COVID-19 pandemic on incident schizophrenia was quantified by fitting a Poisson regression and modeling the relative risk (RR) and corresponding 95% confidence intervals (CI). Three scenarios were projected from the third lockdown to 10 months to forecast incident schizophrenia rates and their associated 95% prediction intervals (PI). RESULTS: The total population (N = 736,356) yielded 4,310 cases of incident schizophrenia over time. The primary analysis showed that the period exposed to the COVID-19 pandemic was associated with a reduced RR (RR = 0.81, 95% CI = 0.73, 0.91, p < 0.001). This conclusion was supported in 12 sensitivity analyses, including scrutinizing lockdowns and COVID-19 infection status. Two of three forecast scenarios projected an incident increase (6.74, 95% PI = 5.80, 7.84; 7.40, 95% PI = 6.36, 8.60). CONCLUSIONS: The reduced risk of schizophrenia during the pandemic suggests no immediate triggering of new onsets either by the virus or the pandemic-induced psychosocial adversities. Once restrictions are lifted, the increased projected presentations have implications for clinicians and healthcare policy.