COVID-19 concerns in cyberspace predict human reduced dispersal in the real world: Meta-regression analysis of time series relationships across American states and 115 countries/territories

作者：

Highlights：

• This study investigates how COVID-19 concerns in cyberspace predict human reduced dispersal in the real world throughout the pandemic.

• COVID-19 concerns in cyberspace positively and significantly predict reduced dispersal in the real world, and this prediction is stronger in historically high-risk areas of infectious-disease contagion.

• Actual coronavirus threat weakly predicts reduced dispersal, and historical risk of infectious-disease contagion is not a significant moderator.

• Online query data can be used to predict human behavioral changes in response to large-scale catastrophic events in the real world and are indispensable for COVID-19 surveillance.

摘要

•This study investigates how COVID-19 concerns in cyberspace predict human reduced dispersal in the real world throughout the pandemic.•COVID-19 concerns in cyberspace positively and significantly predict reduced dispersal in the real world, and this prediction is stronger in historically high-risk areas of infectious-disease contagion.•Actual coronavirus threat weakly predicts reduced dispersal, and historical risk of infectious-disease contagion is not a significant moderator.•Online query data can be used to predict human behavioral changes in response to large-scale catastrophic events in the real world and are indispensable for COVID-19 surveillance.

论文关键词：COVID-19,Google trends,Parasite-stress theory of sociality,Behavioral immune system theory,Time series data,Reduced dispersal

论文评审过程：Received 25 June 2021, Revised 14 September 2021, Accepted 13 October 2021, Available online 14 October 2021, Version of Record 18 November 2021.

论文官网地址：https://doi.org/10.1016/j.chb.2021.107059