The global health crisis caused by the COVID-19 pandemic has resulted in overwhelming pressure on healthcare institutions, making resource planning a significant challenge due to unpredictable waves of infection.
However, scientists from University College London (UCL) have found that online search activity can help predict the peaks of COVID-19 a few weeks in advance, as people tend to search for symptoms online.
During the early stages of the pandemic, information on the disease was widely available, but public interest decreased over time, despite ongoing waves of infection. The UCL researchers developed a model based on internet search activity related to COVID-19 symptoms, which served as an early warning indicator for an impending pandemic wave.
The researchers tested the model in various countries, including the UK, USA, Italy, Australia, and South Africa, and found consistent results. The model successfully predicted the approaching peak 17 days in advance, which is expected to be useful in the ongoing fight against COVID-19 and future pandemics.
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