[News article] Early warning: Internet surveillance predicts disease outbreak

Early warning: Internet surveillance predicts disease outbreak.

From the 7 January 2014 news article

The habit of Googling for an online diagnosis before visiting a GP can provide early warning of an infectious disease epidemic.

In a new study published in Lancet Infectious Diseases, internet-based surveillance has been found to detect infectious diseases such Dengue Fever and Influenza up to two weeks earlier than traditional surveillance methods.

Dr 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 recognizing the symptoms and seeking treatment before diagnosis, along with the time taken for health professionals to alert authorities through their health networks,” Dr Hu said.

“In contrast, digital surveillance can provide real-time detection of epidemics.”

Dr Hu said the study found 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 Organization (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.”

Dr 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 revolutionize emerging infectious disease surveillance,” he said.

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Read entire article here

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