ABSTRACT
This paper employs regression with ARIMA errors (RegARIMA) to quantify the impacts of multiple non-pharmaceutical interventions, daily new cases, seasonal and calendar effects, and other factors on activity trends across the timeline of the ongoing COVID-19 pandemic in Japan. The discussion focuses on two controversial policy sets imposed by the Japanese government that aim to contain the pandemic and to stimulate the recovery of the economy. The containing effect was achieved by stay-at-home requests and declaring a "State of Emergency" in the combat against the first waves of infectious cases. After observing reduced cases, Go-to-travel and Go-to-eat campaigns were launched in July 2020 to encourage recreational travel and to revive the economy. To better understand the impact of the policies we utilize "Google trends" which measure how much these policies are looked up online. We suggest this reflects how much they are part of the public discussion. A case study is conducted in Kyoto, a city famous for tourism. The proposed RegARIMA model is compared with linear regression and time series models. The outperformances in measuring the magnitude of intervention impacts and forecasting the future trends are confirmed by using a total of twelve activity and mobility indices as the dependent variable. Nine indices are released by Google and Apple and three are obtained from local Wi-Fi packet sensors. The effect of the State of Emergency declaration is found to erode at the second implementation, and the second stage of the Go-to-travel campaign successfully stimulated travel demand in the autumn sighting season of 2020.
ABSTRACT
Background: The coronavirus disease-2019 (COVID-19) outbreak and a 3-month lockdown of Wuhan may have had a long-term impact on the mental health of frontline healthcare workers (HWs). However, there is still a lack of comparative studies on the mental health of front-line HWs in the initial phase of the lockdown and 1 month after the lifting of the lockdown. Methods: We recruited 1717 HWs during the initial phase of the lockdown and 2214 HWs 1 month after the lifting of the lockdown, and their baseline characteristics and psychiatric health in these two phases were compared. Furthermore, Pearson's Chi-square test and multivariate logistic regression analysis were used to determine the possible risk factors associated with depressive symptoms in the front-line HWs. Results: Compared with the initial phase of the lockdown, the proportion of HWs with anxiety symptoms and stress decreased, while the proportion of HWs with depressive symptoms increased a month after the lifting of the lockdown. Male sex, exercise habit, comorbidities, and having family members or relatives with suspected or confirmed COVID-19 infection were significantly related to the increased incidence of depressive symptoms during the initial phase of the lockdown. Comorbidities, negative effect of media coverage, working >4 days a week, lower annual household income, and deteriorating relationships with family members were associated with depressive symptoms a month after the lifting of the lockdown. Conclusion: The increased proportion of HWs with depressive symptoms 1 month after the lifting of the lockdown suggested that mental health of front-line HWs should be a top-priority issue, not only during, but also after the pandemic.
ABSTRACT
BACKGROUND: The outbreak of COVID-19 has laid unprecedented threats and challenges to health workers (HWs) in Wuhan, China. We aimed to assess the sociodemographic characteristics and hospital support measures associated with the immediate psychological impact on HWs at Tongji Hospital in Wuhan during COVID-19 outbreak. METHODS: We conducted a single-center, cross-sectional survey of HWs via online questionnaires between February 8th and 10th, 2020. We evaluated stress, depression and anxiety by IES-R, PHQ-9, and GAD-7, respectively. We also designed a questionnaire to assess the perceptions of threat of COVID-19, and the satisfactions of the hospital's support measures. Multivariate logistic regressions were used to identify associated variables of acute stress, depression, and anxiety. FINDINGS: We received 5062 completed questionnaires (response rate, 77.1%). 29.8%, 13.5% and 24.1% HWs reported stress, depression and anxiety symptoms. Women (odds ratio [OR], 1.31; 95% CI, 0.47-0.97; p = 0.032), years of working >10 years (OR, 2.02; 95% CI, 1.47-2.79; p<0.001), concomitant chronic diseases (OR, 1.51; 95% CI, 1.27-1.80; p<0.001), history of mental disorders (OR, 3.27; 95% CI, 1.77-6.05; p<0.001), family members or relatives confirmed or suspected (OR, 1.23; 95% CI, 1.02-1.48; p = 0.03), hospital-based and department-based care (OR, 0.76; 95% CI, 0.60-0.97; p = 0.024) and full coverage of all departments for avoiding nosocomial infection (OR, 0.69; 95% CI, 0.53-0.89; p = 0.004) were associated with stress. INTERPRETATION: Women and those who have more than 10 years of working, concomitant chronic diseases, history of mental disorders, and family members or relatives confirmed or suspected are susceptible to stress, depression and anxiety among HWs during the pandemic. In addition, since HWs often have a greater stigma against mental problems than the general public, it is worthwhile to address the needs of the HWs during this pandemic and to provide appropriate psychological supports for those people at high risk of mental problems.