PandemicsApp-based citizen science experiment to help predict future pandemics

Published 9 October 2017

There are flu outbreaks every year, but in the last 100 years, there have been four pandemics of a particularly deadly flu, including the Spanish Influenza outbreak which hit in 1918, killing up to 100 million people worldwide. Nearly a century later, a catastrophic flu pandemic still tops the U.K. government’s Risk Register of threats to the United Kingdom. A new app gives U.K. residents the chance to get involved in an ambitious science experiment that could save lives.

The most likely and immediate threat to our species is a global pandemic of highly infectious flu. Such a pandemic could be so serious that it currently tops the U.K. government’s Risk Register.

Scientists from the University of Cambridge and London School of Hygiene and Tropical Medicine are attempting to collect a gold standard data set that can be used to predict how the next pandemic flu would spread through this country - and what can be done to stop it. They need your help.

U.K. residents can take part in the BBC Pandemic experiment simply by downloading the Pandemic app onto your smartphone via App Store or Google Play from today.

The app and results will be featured in a documentary on BBC Four in 2018, to be presented by Dr Hannah Fry and Dr. Javid Abdelmoneim.

Data gathered via the app could be key in preparing for the next pandemic outbreak. In order to better understand how an infectious disease like flu can spread, researchers need data about how we travel and interact.

Cambridge says that two experiments will be conducted through the app: the National Outbreak, which has been open to anyone in the United Kingdom from 27th September 2017; and the Haslemere Outbreak, a closed local study that is only open to people in the town of Haslemere, Surrey, and runs for seventy-two hours starting on Thursday, 19 October 2017.

In the National Outbreak, the app has been tracking users’ approximate movement at regular intervals over a twenty-four hour period – with data anonymized, so the app does not know exactly where or who the user is. The app also asks some questions about users’ journeys and the people they spent time with during those twenty-four hours.

All data collected are grouped to ensure anonymity, and a research team from the University of Cambridge and the London School of Hygiene and Tropical Medicine will use it to predict how a flu pandemic might spread across the country – and determine what can be done to stop it.

Professor Julia Gog, who specializes in the mathematics of infectious diseases, and her colleagues from Cambridge’s Department of Applied Mathematics and Theoretical Physics have helped design the experiment and will be processing the data, running statistical analyses, and building and running the pandemic models.

“This will give us a chance to explore a range of different scenarios,” said Professor Gog. “This could the best data set we’ve ever had on the movement of people in the United Kingdom, and could help support future research projects to control infectious diseases – for a researchers like us, this is incredibly exciting.”

There are flu outbreaks every year, but in the last 100 years, there have been four pandemics of a particularly deadly flu, including the Spanish Influenza outbreak which hit in 1918, killing up to 100 million people worldwide. Nearly a century later, a catastrophic flu pandemic still tops the U.K. government’s Risk Register of threats to the United Kingdom. Key to the government’s response plan are mathematical models which simulate how a highly contagious disease may spread. These models help to decide how best to direct NHS resources, like vaccines and protective clothing. But the models are only as good as the data that goes into them.

Cambridge notes that the more people of all ages that take part in BBC Pandemic, the better that data will be.

By identifying the human networks and behaviors that spread a deadly flu, the app will help to make these models more accurate and, in turn, help to stem the next pandemic.

More information is available at the BBC website