Abstract
The Omicron variant has become the dominant COVID-19 variant worldwide due to its rapid and cryptic spread; therefore, successful early warning is of great importance to be able to control epidemics in their early phase, before developing into large outbreaks. COVID-19-related Baidu search index, which reflects human behavior to a certain degree, was used to retrospectively detect the warning signs for Omicron variant outbreaks in China in 2022. The characteristics and effects of warning signs were analyzed in detail. We detected the presence of early warning signs (both high and low thresholds) and found that these occurred 4–7 days earlier than traditional epidemiological surveillance and >20 days earlier than the implementation of the local "lockdown" policy. Compared with the "high threshold" warning, the early warning effect of the "low threshold" is also vital because it indicates a complacency about epidemic prevention and control. Ho wever, there is obvious heterogeneity in the optimal threshold for detecting early warning signs and their distribution in different cities. Multi-source and multi-point early warning systems should be established via combining internet-based big data in the future to conduct effective and early real-time warning. This would create precious time for the early control of COVID-19 outbreaks.
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