Analysing the link between public transport use and airborne transmission: mobility and contagion in the London underground

Abstract Background The transmission of infectious diseases is dependent on the amount and nature of contacts between infectious and healthy individuals. Confined and crowded environments that people visit in their day-to-day life (such as town squares, business districts, transport hubs, etc) can a...

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Main Authors: Lara Goscé, Anders Johansson
Format: Article
Language:English
Published: BMC 2018-12-01
Series:Environmental Health
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12940-018-0427-5
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spelling doaj-eb07a9119cf948de9d0580623b3e852b2020-11-25T01:18:33ZengBMCEnvironmental Health1476-069X2018-12-0117111110.1186/s12940-018-0427-5Analysing the link between public transport use and airborne transmission: mobility and contagion in the London undergroundLara Goscé0Anders Johansson1University College LondonUniversity of BristolAbstract Background The transmission of infectious diseases is dependent on the amount and nature of contacts between infectious and healthy individuals. Confined and crowded environments that people visit in their day-to-day life (such as town squares, business districts, transport hubs, etc) can act as hot-spots for spreading disease. In this study we explore the link between the use of public transport and the spread of airborne infections in urban environments. Methods We study a large number of journeys on the London Underground, which is known to be particularly crowded at certain times. We use publically available Oyster card data (the electronic ticket used for public transport in Greater London), to infer passengers’ routes on the underground network. In order to estimate the spread of a generic airborne disease in each station, we use and extend an analytical microscopic model that was initially designed to study people moving in a corridor. Results Comparing our results with influenza-like illnesses (ILI) data collected by Public Health England (PHE) in London boroughs, shows a correlation between the use of public transport and the spread of ILI. Specifically, we show that passengers departing from boroughs with higher ILI rates have higher number of contacts when travelling on the underground. Moreover, by comparing our results with other demographic key factors, we are able to discuss the role that the Underground plays in the spread of airborne infections in the English capital. Conclusions Our study suggests a link between public transport use and infectious diseases transmission and encourages further research into that area. Results could be used to inform the development of non-pharmacological interventions that can act on preventing instead of curing infections and are, potentially, more cost-effective.http://link.springer.com/article/10.1186/s12940-018-0427-5Public transportCrowd modellingUndergroundInfluenza
collection DOAJ
language English
format Article
sources DOAJ
author Lara Goscé
Anders Johansson
spellingShingle Lara Goscé
Anders Johansson
Analysing the link between public transport use and airborne transmission: mobility and contagion in the London underground
Environmental Health
Public transport
Crowd modelling
Underground
Influenza
author_facet Lara Goscé
Anders Johansson
author_sort Lara Goscé
title Analysing the link between public transport use and airborne transmission: mobility and contagion in the London underground
title_short Analysing the link between public transport use and airborne transmission: mobility and contagion in the London underground
title_full Analysing the link between public transport use and airborne transmission: mobility and contagion in the London underground
title_fullStr Analysing the link between public transport use and airborne transmission: mobility and contagion in the London underground
title_full_unstemmed Analysing the link between public transport use and airborne transmission: mobility and contagion in the London underground
title_sort analysing the link between public transport use and airborne transmission: mobility and contagion in the london underground
publisher BMC
series Environmental Health
issn 1476-069X
publishDate 2018-12-01
description Abstract Background The transmission of infectious diseases is dependent on the amount and nature of contacts between infectious and healthy individuals. Confined and crowded environments that people visit in their day-to-day life (such as town squares, business districts, transport hubs, etc) can act as hot-spots for spreading disease. In this study we explore the link between the use of public transport and the spread of airborne infections in urban environments. Methods We study a large number of journeys on the London Underground, which is known to be particularly crowded at certain times. We use publically available Oyster card data (the electronic ticket used for public transport in Greater London), to infer passengers’ routes on the underground network. In order to estimate the spread of a generic airborne disease in each station, we use and extend an analytical microscopic model that was initially designed to study people moving in a corridor. Results Comparing our results with influenza-like illnesses (ILI) data collected by Public Health England (PHE) in London boroughs, shows a correlation between the use of public transport and the spread of ILI. Specifically, we show that passengers departing from boroughs with higher ILI rates have higher number of contacts when travelling on the underground. Moreover, by comparing our results with other demographic key factors, we are able to discuss the role that the Underground plays in the spread of airborne infections in the English capital. Conclusions Our study suggests a link between public transport use and infectious diseases transmission and encourages further research into that area. Results could be used to inform the development of non-pharmacological interventions that can act on preventing instead of curing infections and are, potentially, more cost-effective.
topic Public transport
Crowd modelling
Underground
Influenza
url http://link.springer.com/article/10.1186/s12940-018-0427-5
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