CSIRO has developed a new tool that harnesses AI and Twitter for early detection of disease outbreaks.

Thunderstorm asthma is occurs when environmental conditions caused by a local thunderstorm trigger a respiratory response.

A sudden outbreak in Melbourne on 21 November 2016 inundated emergency services and hospitals resulting in over 8000 hospital admissions by 6pm that day.

But CSIRO says its new tool may be able to see the next big asthma event coming.

Using anonymised and publicly available Twitter data, the tool has analysed more than 3 million tweets containing keywords related to asthma such as “breath” and “coughing”.

The technique combines two fields of artificial intelligence — natural language processing and statistical time series modelling — and a four-step process to ensure the tweets containing the keywords were indeed reports of health conditions and to remove duplicates where an individual might tweet more than once about their condition.

Natural language processing, or NLP, is the ability of a computer program to process human language. The tool uses NLP based on word embeddings, to distinguish between symptoms and unrelated mentions of the keywords.

Professor Raina MacIntyre, Head of Biosecurity Research Program, Kirby Institute, UNSW Sydney said that this work is a remarkable contribution to public health research.

“In future, this system can be used to provide health authorities and the community early warning of a serious and sudden health event,” Professor MacIntyre said.

“Early detection could significantly improve our capability to mitigate the impact of epidemics.”

The tool can be used to detect other outbreaks such as Influenza, Ebola and the Zika virus. It draws on Data61’s Emergency Situation Awareness system, which analyses Twitter messages posted during disasters and crises to support disaster response efforts.

A new paper describes the technology in more detail.