Buses, trains, and the London Underground will be swabbed for active SARS-CoV-2 virus and other human biomarkers to build a computer model that predicts exactly how passengers and staff catch infections in transit. Current public transport risk assessments rely on guesswork. TRACK will replace that with hard data: air samples, surface swabs, passenger movement patterns from CCTV footage, and surveys of who travels when and why. The team will measure how far infectious droplets and aerosols spread inside different vehicles under different ventilation and cleaning regimes. This matters because transport networks are restarting after COVID lockdowns, and no one knows which interventions—mask mandates, one-way systems, enhanced ventilation—actually cut transmission in a crowded tube carriage versus a half-empty bus. If the model works, the Department for Transport and local operators will have a planning tool that simulates infection risk for any vehicle type, occupancy level, or mitigation strategy. Policy teams could test interventions on a computer before rolling them out, reducing both infection rates and the economic cost of blanket restrictions. The same framework could later be adapted for seasonal flu or future pandemics, making public transport safer without shutting it down.
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Public Transport (PT) patronage is currently well below the norm, but as restart progresses the number of people using transport systems will increase. This could increase COVID-19 infection due to increased proximity and interaction with infected persons and contaminated surfaces. TRACK will develop a novel risk model that can simulate infection risk through three transmission mechanisms (droplet, aerosol, surface contact) within different transport vehicles and operating scenarios. Our interdisciplinary team will collect new data concerning buses, metro and trains (Leeds, Newcastle, London). We will collect air and surface samples to measure SARS-Cov-2 prevalence together with other human biomarkers as a proxy measure for pathogens. We will characterise user and staff travel behaviour and demographics through surveys and passive data collection to relate PT use to geographic and population sub-group disease prevalence. Quantifying proximity of people and their surface contacts through analysis of transport operator CCTV data will enable simulation of micro-behaviour in the transport system. Physical and computational models will be used to evaluate dispersion of infectious droplets and aerosols with different environmental infection control strategies. Data sources will be combined to develop probability distributions for SARS-CoV-2 exposure and simulate transmission risk through a Quantitative Microbial Risk Assessment (QMRA) framework. Working closely with Department for Transport (DfT) and transport stakeholders, TRACK will provide microbial and user data, targeted guidance and risk planning tools that will directly enable better assessment of infection risks for passengers and staff using surface PT networks, and help policy teams design effective interventions to mitigate transmission
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