Internet disease surveillance may be better than traditional methods
Researchers at Queensland University of Technology in Australia found that spikes in searches for information about infectious diseases could help to accurately predict disease outbreaks. Wenbiao Hu, the senior author of the study, said there was a lag time of two weeks before traditional methods of surveillance were able to detect the emerging 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," Hu said. "In contrast, digital surveillance can provide real-time detection of epidemics."
Hu said the study used search engine algorithms like Google Insights and Google Trends to retroactively track the 2005-06 avian influenza outbreak. Hu said that using such algorithms would have tracked the outbreak between one and two weeks earlier than official surveillance reports.
"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," Hu said.
Hu said the next step would be to combine the currently available approaches to develop a real-time infectious disease predictor. He said it was also important for future research to apply internet-based surveillance on a global scale.
"The international nature of emerging infectious diseases combined with the globalization of travel and trade, have increased the interconnectedness of all countries and means detecting, monitoring and controlling these diseases is a global concern," Hu said.