Internet-based surveillance can detect infectious diseases such as dengue fever and influenza up to two weeks earlier than traditional methods, scientists say.
People’s habit of Googling for an online diagnosis before visiting a doctor can provide early warning of an infectious disease epidemic, researchers said.
When investigating the occurrence of epidemics, spikes in searches for information about infectious diseases could accurately predict outbreaks of that disease, said senior author of the study Dr Wenbiao Hu from Queensland University of Technology.
Hu, based at QUT’s Institute for Health and Biomedical Innovation, said there was often a lag time of two weeks before traditional surveillance methods could detect an emerging infectious disease.
“This is because traditional surveillance relies on the patient recognising the symptoms and seeking treatment before diagnosis, along with the time taken for health professionals to alert authorities through their health networks,” Hu said.
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“In contrast, digital surveillance can provide real-time detection of epidemics,” he added.
The study found that by using digital surveillance through search engine algorithms such as Google Trends and Google Insights, detecting the 2005-06 avian influenza outbreak “Bird Flu” would have been possible between one and two weeks earlier than official surveillance reports.
“In another example, a digital data collection network was found to be able to detect the SARS outbreak more than two months before the first publications by the World Health Organisation (WHO),” he said.
“Early detection means early warning and that can help reduce or contain an epidemic, as well alert public health authorities to ensure risk management strategies such as the provision of adequate medication are implemented,” he added.
Hu said the study found social media and micoblogs including Twitter and Facebook could also be effective in detecting disease outbreaks.
“There is the potential for digital technology to revolutionise emerging infectious disease surveillance,” he said.
“The next step would be to combine the approaches currently available such as social media, aggregator websites and search engines, along with other factors such as climate and temperature, and develop a real-time infectious disease predictor,” Hu said.
The study was published in Lancet Infectious Diseases.