Characterizing human collective behaviours of COVID-19 in Hong Kong

TL;DR

This study analyzes online collective behaviors during COVID-19 in Hong Kong, linking internet activity with real-time epidemic data and validating risk perception models through surveys to inform public health strategies.

Contribution

It introduces a framework combining online behavior analysis and survey validation to assess risk perception and collective response during COVID-19 in Hong Kong.

Findings

Strong correlation between Google searches and reproduction numbers

Model captures 80% of risk perception trend

Online behaviors reflect public awareness and concern

Abstract

People are likely to engage in collective behaviour online during extreme events, such as the COVID-19 crisis, to express their awareness, actions and concerns. Hong Kong has implemented stringent public health and social measures (PHSMs) to curb COVID-19 epidemic waves since the first COVID-19 case was confirmed on 22 January 2020. People are likely to engage in collective behaviour online during extreme events, such as the COVID-19 crisis, to express their awareness, actions and concerns. Here, we offer a framework to evaluate interactions among individuals emotions, perception, and online behaviours in Hong Kong during the first two waves (February to June 2020) and found a strong correlation between online behaviours of Google search and the real-time reproduction numbers. To validate the model output of risk perception, we conducted 10 rounds of cross-sectional telephone surveys from February 1 through June 20 in 2020 to quantify risk perception levels over time. Compared with the survey results, the estimates of the risk perception of individuals using our network-based mechanistic model capture 80% of the trend of people risk perception (individuals who worried about being infected) during the studied period. We may need to reinvigorate the public by engaging people as part of the solution to live their lives with reduced risk.