Internet searches for "insomnia" and "suicide" mediated by stay-at-home behaviors in 45 countries during the first 12 months of the COVID-19 pandemic.

BACKGROUND: This study aimed to investigate (1) the mental health impacts (i.e., insomnia and suicide ideas) of the COVID-19 pandemic and (2) the mediation effects of stay-at-home levels on those impacts. METHODS: This study investigated monthly national COVID-19 deaths, stay-at-home levels, and internet searches for words for "insomnia" and "suicide" across 45 countries during the first year of the COVID-19 pandemic (March 1, 2020, to February 28, 2021). We used the changes of internet search volumes for "insomnia" and "suicide" (from the Google Trends database) to represent the mental health impacts, and the time of cell phone activity at the residence (from Google Location History) to estimate the stay-at-home effects. We computed the proportion mediated (PM) caused by stay-at-home levels in the COVID-19 impacts on insomnia and suicide ideas, respectively. RESULTS: Throughout the first year of the COVID-19 pandemic, national COVID-19 deaths significantly correlated to increased internet searches for "insomnia" but decreased searches for "suicide". In addition, the mediation effect was significant in the first six-month of COVID-19-related increases in insomnia (PM = 42.6 %, p = 0.016), but this effect was not significant (PM = 13.1 %, p = 0.270) in the second six-month. By contrast, the mediation effect was not significant in the first six-month of COVID-19-related decrease in suicide ideation (PM = 8.1 %, p = 0.180), but this effect was significant (PM = 39.6 %, p = 0.014) in the second six-month. CONCLUSIONS: Stay-at-home levels significantly mediated both increased insomnia and decreased suicide ideas, but within different time frames.

Utilizing Internet Search Volume to Monitor Stages of Change in Vaccine Hesitancy During the COVID-19 Outbreaks

Real-time vaccine hesitancy surveillance is needed to better understand changes in vaccination behaviors. We aim to understand the association between coronavirus disease 2019 (COVID-19) outbreaks and population vaccine hesitancy and to monitor the dynamic changes in vaccination behaviors. We used the autoregressive integrated moving average model to examine the association between daily internet search volume for vaccines and two waves of COVID-19 local outbreaks in Taiwan from 19 March to 25 May, 2021. During the small-scale outbreak, the search volume increased significantly for 7 out of 22 days with an average increase of 17.3% ± 10.7% from the expected search volume. During the large-scale outbreak, the search volume increased significantly for 14 out of 14 days, with an average increase of 58.4% ± 14.7%. There was a high correlation between the search volume and the number of domestic cases (r = 0.71, P < 0.001). Google Trends serves as a timely indicator to monitor the extent of population vaccine willingness.