Three people walking along wearing masks

The UoP C-19 Mobility Tracking Project is looking to understand how people move around and where there is a high-risk of catching the disease.

  • 17 November 2020
  • 2 min read

Staff and students are required to help researchers identify Portsmouth’s Covid-19 hotspots.

The UoP C-19 Mobility Tracking Project is looking to understand how people move around the city and the University to look for places where there is a high-risk of catching the disease and to improve our understanding of how it spreads.

Volunteers will install the FollowMee app, which provides their anonymous location data to the project (this can be switched on and off as you wish) and answer short anonymous surveys about their perceptions of risk and their disease status.

We are looking for volunteers who are willing to provide anonymous location data to the project, and to answer questions about their risk perceptions and behavioural motivations.

Dr James Burridge, Reader in Probability and Statistical Physics

The project team, Dr James Burridge, Dr Michal Gnacik and Dr Rob Inkpen who are based in the School of Mathematics and Physics, will use this data to build models of high-risk areas and map how the disease is spreading. They will also incorporate data collected from the University’s own Covid-19 testing programme.

This will help provide early warnings of disease hotspots, understand the effect of lockdowns on behaviour and disease transmission, and guide people away from high-risk zones. The information will be displayed on the University website along with maps of high-risk zones.

Dr James Burridge, Reader in Probability and Statistical Physics in the School of Mathematics and Physics, said: “We are looking for volunteers who are willing to provide anonymous location data to the project, and to answer questions about their risk perceptions and behavioural motivations. As well as assisting the University and city with risk management, volunteers will be contributing to our understanding of human behaviour and movement.

“By combining movement data with knowledge about individual risk perceptions and motivations, we can understand how movement and motivation are related. We can then incorporate human behaviour into disease modelling.”

Sign up to take part in the project.

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