Internet-based surveillance could help predict infectious diseases outbreak

Researchers have claimed that internet-based surveillance can help detect infectious diseases like Dengue Fever and Influenza up to two weeks earlier than traditional surveillance methods.

Senior author of the paper titled Internet-based surveillance systems for monitoring emerging infectious diseases, QUT Senior Research Fellow Dr Wenbiao Hu said that when investigating the occurrence of epidemics, spikes in searches for information about infectious diseases could accurately predict outbreaks of that disease.

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.

He said that 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 that in contrast, digital surveillance can provide real-time detection of epidemics.

He 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.

The new study has been published in journal Lancet Infectious Diseases.