Online searches of humans can be used as a tool to help epidemiologists spot early coronavirus outbreaks, researchers have said.
Using signal-related searches through Google could allow experts to predict a peak in cases an average of 17 days in advance, a group from University College London (UCL) said.
Internet survey activity analysis has already been used to detect and understand seasonal flu.
Using data on Covid-19 web searches in a similar way to more established methods could improve public health analysis methods.
“Building on previous research which has demonstrated the usefulness of online diagnostic activity in shaping infectious diseases such as influenza, this study provides a new set of tools that can used to monitor Covid-19, ”said lead author Dr Vasileios Lampos.
“We have shown that our approach works across different countries despite cultural, socio-economic and climate differences.
“Our analysis was also among the first to find a link between Covid-19 frequency and investigations into symptoms of odor loss and skin rash.
“We are delighted that public health organizations such as PHE (Public Health England) have also recognized the usefulness of these new and non-traditional approaches to epidemiology.”
Scientists have found that their model provides useful insights, such as early warnings, and demonstrates the effect of physical speed measures.
Professor Michael Edelstein, of the University of Bar-Ilan, Israel, who co-authored the research, said: 19 to detect them early so that they can act early.
“Using innovative methods for disease detection such as analyzing internet survey activity to add to established methods is the best way to break out early.”
Details of the model were published in the journal Nature Digital Medicine.