Impact of COVID-19 on public social life and mental health : a statistical study of google trends data from the USA

Bibliographische Detailangaben
Veröffentlicht in:	Journal of applied statistics. - 1991. - 51(2024), 3 vom: 29., Seite 581-605
1. Verfasser:	Roy, Archi (VerfasserIn)
Weitere Verfasser:	Deb, Soudeep, Chakarwarti, Divya
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2024
Zugriff auf das übergeordnete Werk:	Journal of applied statistics
Schlagworte:	Journal Article ARMA-GARCH models changepoint detection coronavirus pandemic google search volume infodemiology

Beschreibung
Zusammenfassung:	© 2023 Informa UK Limited, trading as Taylor & Francis Group. The COVID-19 pandemic has caused a significant disruption in the social lives and mental health of people across the world. This study aims to asses the effect of using internet search volume data. We categorize the widely searched keywords on the internet in several categories, which are relevant in analyzing the public mental health status. Corresponding to each category of keywords, we conduct an appropriate statistical analysis to identify significant changes in the search pattern during the course of the pandemic. Binary segmentation method of changepoint detection, along with the combination of ARMA-GARCH models are utilized in this analysis. It helps us detect how people's behavior changed in phases and whether the severity of the pandemic brought forth those shifts in behaviors. Interestingly, we find that rather than the severity of the outbreak, the long duration of the pandemic has affected the public health status more. The phases, however, align well with the so-called COVID-19 waves and are consistent for different aspects of social and mental health. We further observe that the results are typically similar for different states as well
Beschreibung:	Date Revised 20.02.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE
ISSN:	0266-4763
DOI:	10.1080/02664763.2022.2164562