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J Med Internet Res ; 22(9): e22181, 2020 09 21.
Article in English | MEDLINE | ID: covidwho-789099

ABSTRACT

BACKGROUND: Real-time global mental health surveillance is urgently needed for tracking the long-term impact of the COVID-19 pandemic. OBJECTIVE: This study aimed to use Google Trends data to investigate the impact of the pandemic on global mental health by analyzing three keywords indicative of mental distress: "insomnia," "depression," and "suicide." METHODS: We examined increases in search queries for 19 countries. Significant increases were defined as the actual daily search value (from March 20 to April 19, 2020) being higher than the 95% CIs of the forecast from the 3-month baseline via ARIMA (autoregressive integrated moving average) modeling. We examined the correlation between increases in COVID-19-related deaths and the number of days with significant increases in search volumes for insomnia, depression, and suicide across multiple nations. RESULTS: The countries with the greatest increases in searches for insomnia were Iran, Spain, the United States, and Italy; these countries exhibited a significant increase in insomnia searches on more than 10 of the 31 days observed. The number of COVID-19-related deaths was positively correlated to the number of days with an increase in searches for insomnia in the 19 countries (ρ=0.64, P=.003). By contrast, there was no significant correlation between the number of deaths and increases in searches for depression (ρ=-0.12, P=.63) or suicide (ρ=-0.07, P=.79). CONCLUSIONS: Our analysis suggests that insomnia could be a part of routine mental health screening during the COVID-19 pandemic.


Subject(s)
Coronavirus Infections/epidemiology , Global Health/statistics & numerical data , Internationality , Internet/statistics & numerical data , Mental Health/statistics & numerical data , Pandemics , Pneumonia, Viral/epidemiology , Search Engine/statistics & numerical data , Sleep Initiation and Maintenance Disorders/epidemiology , Betacoronavirus , COVID-19 , Depression/epidemiology , Humans , Longitudinal Studies , SARS-CoV-2 , Suicide/statistics & numerical data
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