Crowd Sourced Data for Road Traffic Injury Surveillance

About this project

This projects seeks to provide a novel crowdsourced data tool for road traffic injury surveillance to improve emergency medical systems.

Project background

Good trauma system planning needs good Road Traffic Collision data, to run hospitals, ambulance travel time cuts, and to reduce high risk roads. WHO Injury Surveillance and Trauma Care guidelines show the need for good data, particularly when resources are limited. Such data is sparse in developing countries, but the boom in digital technology in developing world cities provides a potential alternative data source to help capacity building, emergency medicine and risk reduction, in line with FIA/UN Decade goals.

Project aims and objectives

This project will seek to:

  1. Collect and aggregate novel digital data sources relating to Road Traffic Collisions eg online media, news, mobile navigation, vehicle telematics;
  2. Assess the ability of these sources to identify geolocation, timing and severity of Road Traffic Collisions;
  3. Compare the accuracy of these sources as Road Traffic Collision surveillance to well-established high quality data from London’s transport, ambulance, health services; and
  4. Establish if these sources can be a surrogate for developing world cities to overcome inadequate infrastructure and improve

Project timescales

The project commenced in January 2018 and will complete in June 2020.

Project partners

This project is being delivered by Imperial College London / Imperial College Healthcare Trust and is being funded by the RAC Foundation and the FIA via their Road Safety Grants Programme.

For more information

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Updated: 08 Oct 2018