Towards an Integrated Global Transport and Health Assessment Tool (TIGTHAT)
Lead Research Organisation:
University of Cambridge
Department Name: MRC Epidemiology Unit
Abstract
Globally, how people and goods move is important for urban health. Transport causes ill-health through road traffic injuries, noise, and air pollution, but is an opportunity for benefiting health through active travel. Although there are good examples, problems of poor safety, pollution, and environments unconducive to walking and cycling are common in many lower and middle income cities (LMICs). These cities are often changing fast, many are growing rapidly, and motorbike and then car use is increasing. The problem and the opportunity are large.
A number of studies have used computer based models to estimate the health impacts of more active travel in high income Western countries. However, we are aware of only three studies in LMICs (Delhi, Sao Paulo and Kuala Lumpur), all involving the applicants.
The high income studies found more walking and cycling and fewer cars could bring large health benefits. However, our work shows things are more complicated in LMICs. For example, how much people benefit from increasing their physical activity depends how active they are to start with. It also depends on how polluted the air is, because pedestrians and cyclists breath in faster. Road injuries numbers may go up or down as pedestrians and cyclists are at higher risk than drivers, but fewer cars may make the roads safer.
One way to support decision makers is to provide tools that help them to compare the health impacts of their choices. The challenge is to be both practically useful and scientifically accurate. In this project we lay the basis for creating a model that can be readily applied to cities around the world. A key challenge is data comparability and quality. Our international team of health and transport researchers in the UK, India, Brazil, USA, and Peru will assess what data are available and work to develop rules for drawing the best conclusions from it.
We will build a model for two Indian cities (Bengaluru and Visakhapatnam) and do further work with the models we have recently created for Sao Paulo and Delhi. Running the model will not just produce new results but we also use statistical techniques to work out where getting better data is most valuable e.g. do our results change more if we have better information on injuries or on walking.
To estimate health impacts we need scenarios about how travel might change. We will do this in two ways. Firstly asking what would happen if people were as likely to walk, cycle (including electric-assist bikes) a trip of a given distance as people are in more active cities. Secondly, we will look at how more compact cities might affect how people travel.
We will look at the data available in a further four Latin America and sub-Saharan African cities in depth to model them in the future. We will also look across a wide range of settings to see what data is available on how people travel and useful it is for modelling.
We will use a computer programme to get information from Google Street View for different cities and use it to estimate the mix of traffic across the city. We will see if we can use this data to predict how much time people spend travelling by each mode, and using other data about the city how active people are in total.
The project team has worked previously on using a range of data to estimate the number of road traffic victims by mode in different countries. We will now apply this approach to the urban level and work with estimating the kind of data we need for the health impact model. For calculating air pollution risk we will develop a simple method for estimating the contribution of transport to AP using global databases and we will compare this against more detailed analysis in cities for which we have better data.
In summary this project lays the foundation for a scientifically robust webtool that can help policy makers tackle a major determinant of population health.
A number of studies have used computer based models to estimate the health impacts of more active travel in high income Western countries. However, we are aware of only three studies in LMICs (Delhi, Sao Paulo and Kuala Lumpur), all involving the applicants.
The high income studies found more walking and cycling and fewer cars could bring large health benefits. However, our work shows things are more complicated in LMICs. For example, how much people benefit from increasing their physical activity depends how active they are to start with. It also depends on how polluted the air is, because pedestrians and cyclists breath in faster. Road injuries numbers may go up or down as pedestrians and cyclists are at higher risk than drivers, but fewer cars may make the roads safer.
One way to support decision makers is to provide tools that help them to compare the health impacts of their choices. The challenge is to be both practically useful and scientifically accurate. In this project we lay the basis for creating a model that can be readily applied to cities around the world. A key challenge is data comparability and quality. Our international team of health and transport researchers in the UK, India, Brazil, USA, and Peru will assess what data are available and work to develop rules for drawing the best conclusions from it.
We will build a model for two Indian cities (Bengaluru and Visakhapatnam) and do further work with the models we have recently created for Sao Paulo and Delhi. Running the model will not just produce new results but we also use statistical techniques to work out where getting better data is most valuable e.g. do our results change more if we have better information on injuries or on walking.
To estimate health impacts we need scenarios about how travel might change. We will do this in two ways. Firstly asking what would happen if people were as likely to walk, cycle (including electric-assist bikes) a trip of a given distance as people are in more active cities. Secondly, we will look at how more compact cities might affect how people travel.
We will look at the data available in a further four Latin America and sub-Saharan African cities in depth to model them in the future. We will also look across a wide range of settings to see what data is available on how people travel and useful it is for modelling.
We will use a computer programme to get information from Google Street View for different cities and use it to estimate the mix of traffic across the city. We will see if we can use this data to predict how much time people spend travelling by each mode, and using other data about the city how active people are in total.
The project team has worked previously on using a range of data to estimate the number of road traffic victims by mode in different countries. We will now apply this approach to the urban level and work with estimating the kind of data we need for the health impact model. For calculating air pollution risk we will develop a simple method for estimating the contribution of transport to AP using global databases and we will compare this against more detailed analysis in cities for which we have better data.
In summary this project lays the foundation for a scientifically robust webtool that can help policy makers tackle a major determinant of population health.
Technical Summary
Urban land transport has positive (physical activity) and negative (road traffic injuries, noise and air pollutants) side effects. Studies in high income cities found substantial population health benefits from mode shift to active travel, with physical activity (PA) dominating. However, our work in Brazil, India, and Malaysia identifies a more varied picture, with a larger burden and trickier trade-offs.
In this project we lay the basis for a globally applicable stochastic synthesis engine with a user friendly interface, to support evidence based decision making on transport and health. A key challenge is data comparability and quality. Our international, multidisciplinary team will assess what data is available and develop approaches for mapping (calibrating) available to desired data, while representing propagated uncertainty.
We will undertake integrated health impact simulation modelling for 3 Indian cities and Sao Paulo, Brazil, using sensitivity analysis to inform future empirical work. We will test counterfactual scenarios assuming changes to mode choice and land use. We will evaluate travel behaviour data for future modelling studies in further Latin American, India, and sub-Saharan settings.
We will query the Google Street View (GSV) API to estimate ratio(s) of traffic modes in several cities. We will build an ecological model to predict travel time mode split and self-report PA from GSV data, and explore mapping to objective PA. The applicants have previously combined and imputed data to estimate RTIs by mode at the national level. We will now do this at the urban level. For AP we will develop a simple method for estimating the transport's contribution to AP using global databases and compare this to detailed analysis in several cities.
This project lays the foundation for an analytic modelling framework to estimate multiple outcomes of interest under counterfactual scenarios with respect to a major determinant of population health.
In this project we lay the basis for a globally applicable stochastic synthesis engine with a user friendly interface, to support evidence based decision making on transport and health. A key challenge is data comparability and quality. Our international, multidisciplinary team will assess what data is available and develop approaches for mapping (calibrating) available to desired data, while representing propagated uncertainty.
We will undertake integrated health impact simulation modelling for 3 Indian cities and Sao Paulo, Brazil, using sensitivity analysis to inform future empirical work. We will test counterfactual scenarios assuming changes to mode choice and land use. We will evaluate travel behaviour data for future modelling studies in further Latin American, India, and sub-Saharan settings.
We will query the Google Street View (GSV) API to estimate ratio(s) of traffic modes in several cities. We will build an ecological model to predict travel time mode split and self-report PA from GSV data, and explore mapping to objective PA. The applicants have previously combined and imputed data to estimate RTIs by mode at the national level. We will now do this at the urban level. For AP we will develop a simple method for estimating the transport's contribution to AP using global databases and compare this to detailed analysis in several cities.
This project lays the foundation for an analytic modelling framework to estimate multiple outcomes of interest under counterfactual scenarios with respect to a major determinant of population health.
Planned Impact
This project will develop methods and tools to improve health and well-being in urban environments in Low and Middle Income Countries (LMICs). The methods we will develop in this project will allow to predict how changes in urban transport would change the air pollution, injuries and physical activity, and how these changes would improve health and well-being, and link to greenhouse gas emission targets.
The way people and goods move around is a public health issue. Impacts are at their starkest in LMICs with rapidly increasing urbanisation and motorisation. The burden of road traffic injuries (RTIs) is predicted to rise globally from the 9th to 7th leading cause of death. In India there are an estimated 200,000RTI deaths per year, while Africa has the highest per capita burden. Urban outdoor air pollution (AP) also poses a large burden, greatest in Asia. At the same time LMICs face a growing burden of chronic disease associated with lack of physical activity (PA). For example around 30% of the adult population are inactive in Brazil.
In longer term our plan is to develop a tool that can be applied in all larger urban areas in LMICs, as well as other cities in the world. A web interface will be provided so that stakeholders (e.g. public health professional, transport professionals, other interested parties) can assess the evidence on likely health consequences of transport interventions and scenarios, and in this way promote policies that improve health. We aim that in five years we will have Version 1 of an open source, freely available health impact model developed and disseminated for India, Brazil and Peru, with other Latin American and Caribbean countries, and then Africa and East Asia to follow.
In the short term this project will bring evidenced understanding of the availability and usefulness of data for modelling the health impacts of transport. This will be strongly advanced in India, advanced in Latin America, and started in Africa. We will have appraised and tested the suitability of multiple data types for inclusion in a health impact model. We will have started data mapping of Google Street View to travel time mode share and total physical activity. We will be able to inform science and surveillance about where enhanced travel, PA, RTI, and AP data collection would most reduce decision uncertainty. We will have worked with a range of potential model users. This project will also increase our project partners' capacity in LMICs to develop and conduct health impact assessment studies. On a larger scale, availability of the model code through an open-source portal will enable scientific reproducibility.
The challenge for the study is to disseminate knowledge from these methods to potential users around the world. For details on how we aim to do this, see Pathways to Impact, and for academic dissemination Communications Plan.
ODA justification
This research will bring long-term benefits to LMICs by providing public health, transport, and planners the means to assess health risks and benefits of transport choices. The vast majority of heath impact fo transport modelling studies are for high income settings. Few tools integrate risks due to PA, RTI and AP. The World Health Organization (WHO) Health Economic Assessment Tool (HEAT) is mainly used in Europeans setting with good data, and, focusing on walking and cycling, does not provide integrated assessment of motorised modes. On the other side, travel demand models, where available, contain little or no data on active travel.
In the short-term, our project will benefit the cities in India, Brazil and Peru. We will develop and test the methods in these cities and disseminate the preliminary results to local stakeholders through our local collaborators. We will also disseminate best practice through our partners. However, the main impact will be achieved after the project when we have developed and disseminated our impact assessment model.
The way people and goods move around is a public health issue. Impacts are at their starkest in LMICs with rapidly increasing urbanisation and motorisation. The burden of road traffic injuries (RTIs) is predicted to rise globally from the 9th to 7th leading cause of death. In India there are an estimated 200,000RTI deaths per year, while Africa has the highest per capita burden. Urban outdoor air pollution (AP) also poses a large burden, greatest in Asia. At the same time LMICs face a growing burden of chronic disease associated with lack of physical activity (PA). For example around 30% of the adult population are inactive in Brazil.
In longer term our plan is to develop a tool that can be applied in all larger urban areas in LMICs, as well as other cities in the world. A web interface will be provided so that stakeholders (e.g. public health professional, transport professionals, other interested parties) can assess the evidence on likely health consequences of transport interventions and scenarios, and in this way promote policies that improve health. We aim that in five years we will have Version 1 of an open source, freely available health impact model developed and disseminated for India, Brazil and Peru, with other Latin American and Caribbean countries, and then Africa and East Asia to follow.
In the short term this project will bring evidenced understanding of the availability and usefulness of data for modelling the health impacts of transport. This will be strongly advanced in India, advanced in Latin America, and started in Africa. We will have appraised and tested the suitability of multiple data types for inclusion in a health impact model. We will have started data mapping of Google Street View to travel time mode share and total physical activity. We will be able to inform science and surveillance about where enhanced travel, PA, RTI, and AP data collection would most reduce decision uncertainty. We will have worked with a range of potential model users. This project will also increase our project partners' capacity in LMICs to develop and conduct health impact assessment studies. On a larger scale, availability of the model code through an open-source portal will enable scientific reproducibility.
The challenge for the study is to disseminate knowledge from these methods to potential users around the world. For details on how we aim to do this, see Pathways to Impact, and for academic dissemination Communications Plan.
ODA justification
This research will bring long-term benefits to LMICs by providing public health, transport, and planners the means to assess health risks and benefits of transport choices. The vast majority of heath impact fo transport modelling studies are for high income settings. Few tools integrate risks due to PA, RTI and AP. The World Health Organization (WHO) Health Economic Assessment Tool (HEAT) is mainly used in Europeans setting with good data, and, focusing on walking and cycling, does not provide integrated assessment of motorised modes. On the other side, travel demand models, where available, contain little or no data on active travel.
In the short-term, our project will benefit the cities in India, Brazil and Peru. We will develop and test the methods in these cities and disseminate the preliminary results to local stakeholders through our local collaborators. We will also disseminate best practice through our partners. However, the main impact will be achieved after the project when we have developed and disseminated our impact assessment model.
Organisations
Publications
Aldred R
(2019)
Contextualising Safety in Numbers: a longitudinal investigation into change in cycling safety in Britain, 1991-2001 and 2001-2011.
in Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
Aldred R
(2021)
How does mode of travel affect risks posed to other road users? An analysis of English road fatality data, incorporating gender and road type.
in Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention
Aldridge R
(2018)
Global Patterns of Mortality in International Migrants: A Systematic Review and Meta-Analysis
in SSRN Electronic Journal
Aldridge RW
(2018)
Global patterns of mortality in international migrants: a systematic review and meta-analysis.
in Lancet (London, England)
Banerjee A
(2020)
Multimorbidity: Not Just for the West
in Global Heart
Title | Additional file 1: of Physical activity and sedentary behavior patterns and sociodemographic correlates in 116,982 adults from six South American countries: the South American physical activity and sedentary behavior network (SAPASEN) |
Description | Figure S1. Harmonized meta-analysis of the association between leisure-time physical activity (=150 min/week) and sex/educational status. A) Odds ratio of sex refers to women compared with men. B) Odds ratio of educational status refers to college or more vs. lower than secondary school. Odds ratio results are adjusted by age group and sitting time and calculated using sampling weights. (TIFF 431 kb) |
Type Of Art | Film/Video/Animation |
Year Produced | 2019 |
URL | https://springernature.figshare.com/articles/Additional_file_1_of_Physical_activity_and_sedentary_be... |
Title | Additional file 1: of Physical activity and sedentary behavior patterns and sociodemographic correlates in 116,982 adults from six South American countries: the South American physical activity and sedentary behavior network (SAPASEN) |
Description | Figure S1. Harmonized meta-analysis of the association between leisure-time physical activity (=150 min/week) and sex/educational status. A) Odds ratio of sex refers to women compared with men. B) Odds ratio of educational status refers to college or more vs. lower than secondary school. Odds ratio results are adjusted by age group and sitting time and calculated using sampling weights. (TIFF 431 kb) |
Type Of Art | Film/Video/Animation |
Year Produced | 2019 |
URL | https://springernature.figshare.com/articles/Additional_file_1_of_Physical_activity_and_sedentary_be... |
Title | Additional file 2: of Physical activity and sedentary behavior patterns and sociodemographic correlates in 116,982 adults from six South American countries: the South American physical activity and sedentary behavior network (SAPASEN) |
Description | Figure S2. Harmonized meta-analysis of the association between transport physical activity (=10 min/week) and sex/educational status. A) Odds ratio of sex refers to women compared with men. B) Odds ratio of educational status refers to college or more vs. lower than secondary school. Odds ratio results are adjusted by age group and sitting time and calculated using sampling weights. (TIFF 407 kb) |
Type Of Art | Film/Video/Animation |
Year Produced | 2019 |
URL | https://springernature.figshare.com/articles/Additional_file_2_of_Physical_activity_and_sedentary_be... |
Title | Additional file 2: of Physical activity and sedentary behavior patterns and sociodemographic correlates in 116,982 adults from six South American countries: the South American physical activity and sedentary behavior network (SAPASEN) |
Description | Figure S2. Harmonized meta-analysis of the association between transport physical activity (=10 min/week) and sex/educational status. A) Odds ratio of sex refers to women compared with men. B) Odds ratio of educational status refers to college or more vs. lower than secondary school. Odds ratio results are adjusted by age group and sitting time and calculated using sampling weights. (TIFF 407 kb) |
Type Of Art | Film/Video/Animation |
Year Produced | 2019 |
URL | https://springernature.figshare.com/articles/Additional_file_2_of_Physical_activity_and_sedentary_be... |
Title | Additional file 3: of Physical activity and sedentary behavior patterns and sociodemographic correlates in 116,982 adults from six South American countries: the South American physical activity and sedentary behavior network (SAPASEN) |
Description | Figure S3. Harmonized meta-analysis of the association between occupational physical activity (=10 min/week) and sex/educational status. A) Odds ratio of sex refers to women compared with men. B) Odds ratio of educational status refers to college or more vs. lower than secondary school. Odds ratio results are adjusted by age group and sitting time and calculated using sampling weights. (TIFF 380 kb) |
Type Of Art | Film/Video/Animation |
Year Produced | 2019 |
URL | https://springernature.figshare.com/articles/Additional_file_3_of_Physical_activity_and_sedentary_be... |
Title | Additional file 3: of Physical activity and sedentary behavior patterns and sociodemographic correlates in 116,982 adults from six South American countries: the South American physical activity and sedentary behavior network (SAPASEN) |
Description | Figure S3. Harmonized meta-analysis of the association between occupational physical activity (=10 min/week) and sex/educational status. A) Odds ratio of sex refers to women compared with men. B) Odds ratio of educational status refers to college or more vs. lower than secondary school. Odds ratio results are adjusted by age group and sitting time and calculated using sampling weights. (TIFF 380 kb) |
Type Of Art | Film/Video/Animation |
Year Produced | 2019 |
URL | https://springernature.figshare.com/articles/Additional_file_3_of_Physical_activity_and_sedentary_be... |
Description | Transport has important implications for population health. Modelling studies have shown potentially large benefits from increasing walking and cycling and reducing car use, but most of these studies have been conducted in high income countries. In lower and middle income countries the context is different and more varied, and the data are often less readily available. The aim of the project was to lay the foundations for a globally relevant model. We have done by creating an improved health impact model of transport and are currently finalising results for eleven cities in Latin America, Africa, and India. This goes beyond the number of cities and continents anticipated originally. The approach is now being scaled up through the ERC funded GLASST project. In Accra we undertook more detailed case study work (supported additionally by the WHO) with policy makers and produced a separate paper and report. We have also successfully tested new methods for estimating travel patterns and traffic volume using image data, working with both Google Street View and satellite data. In the case of satellite data we have also shown associations with traffic injury burden We have created 'who hit whom' clusters using road traffic injury data from multiple countries. These show the greater complexity of the problem in many lower and middle income cities. We have developed a new method for modeling traffic's contribution to particulate matter in urban areas. Based on the data gaps we identified we have secured funding for new data collection in Africa. In Accra travel survey data, and in Kisumu and Yaoundé travel survey and injury data. We are still finalising results from the integrated model but our initial results demonstrate the greater complexity and variability in lower and middle income countries, and that finding from high income settings cannot be readily applied. In particular the high injury risk means addressing pedestrian and cyclist safety in an immediate priority. We have both demonstrated the feasibility of doing modelling studies in multiple lower and middle income settings with intensive research work, and the started to demonstrate the potential of using alternate data sources. |
Exploitation Route | The code base for the ITHIM R (Tigthat models) is available at https://github.com/ITHIM/ITHIM-R We will be making anonymised data and detailed results tables available for reuse over the next year. Our identification of data gaps has informed new data collection efforts and we expect this to continue as we publish more results. |
Sectors | Construction Healthcare Transport |
URL | https://github.com/ITHIM/ITHIM-R |
Description | We developed a bespoke version of the model for the WHO in a project in Accra, Ghana and worked with the local government and other organisations. We are not yet fully sure of the impact on policies of this engagement Findings from this study were used in developing a bespoke model for the C40 Cities coalition. This model is being used by them for estimating health impacts of walking and cycling schemes in many of their consitutent cities. |
First Year Of Impact | 2019 |
Sector | Transport |
Impact Types | Policy & public services |
Description | Global & local health impact assessment of transport |
Amount | € 1,661,804 (EUR) |
Organisation | European Research Council (ERC) |
Sector | Public |
Country | Belgium |
Start | 01/2019 |
End | 12/2023 |
Title | ITHIM |
Description | ITHIM refers to a range of related models and tools developed at CEDAR to perform integrated assessment of the health effects of transport scenarios and policies at the urban and national level. The health effects of transport policies are modelled through the changes in physical activity, road traffic injury risk, and exposure to fine particulate matter (PM2.5) air pollution. Some versions of ITHIM also predict changes in CO2 emissions. ITHIM is being used in research and by health and transport professionals to estimate the health impacts of scenarios, compare the impact of travel patterns in different places, and model the impact of interventions. ITHIM works either as a stand-alone model, or it can be linked with other models (e.g. transport, health, economic). |
Type Of Material | Computer model/algorithm |
Year Produced | 2012 |
Provided To Others? | Yes |
Impact | Fed into transport plans in London, California and Portland. ITHIM has is being used in research projects in Brazil, India, and Malaysia. It has been sent to research & practitioner groups in Ireland, Taiwan, Singapore, Canada, and multiple groups in the US. It has been used to generate results for reports (for British Cycling and CTC) that have attracted media and parliamentary attention. |
URL | http://www.cedar.iph.cam.ac.uk/research/modelling/ithim/ |
Title | ITHIM R |
Description | The Integrated Transport and Health Impact Modelling (ITHIM) tool has been considerably upgraded and implemented into R. https://shiny.mrc-epid.cam.ac.uk/ithim/ |
Type Of Material | Computer model/algorithm |
Year Produced | 2018 |
Provided To Others? | Yes |
Impact | A version of the model was developed with inputs from local and WHO stakeholders in Accra, Ghana. Impacts and outputs have also been realised from spin off versions of the model (and earlier versions) including citation under objective 6 of the California "Health in All Policies Task Force 2014-2018 Active Transportation Action Report" with recent papers here https://ajph.aphapublications.org/doi/full/10.2105/AJPH.2018.304879 https://www.nzma.org.nz/journal/read-the-journal/all-issues/2010-2019/2018/vol-131-no-1472-23-march-2018/7529 https://www.sciencedirect.com/science/article/pii/S1361920918309052 https://www.mdpi.com/1660-4601/15/5/962 |
URL | https://shiny.mrc-epid.cam.ac.uk/ithim/ |
Title | Population, density, GDP, and census travel to work attributes of Indian cities |
Description | The spreadsheet consists of multiple attributes of case study cities. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://data.mendeley.com/datasets/w6h8fmm9g5/1 |
Title | Population, density, GDP, and census travel to work attributes of Indian cities |
Description | The spreadsheet consists of multiple attributes of case study cities. |
Type Of Material | Database/Collection of data |
Year Produced | 2020 |
Provided To Others? | Yes |
URL | https://data.mendeley.com/datasets/w6h8fmm9g5 |
Description | 4th Safer City Streets Network Meeting (LG) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Dr Leandro Garcia presented at the 4th Safer City Streets Network Meeting held on 20 November 2018 in London. |
Year(s) Of Engagement Activity | 2018 |
Description | 7th International Society for Physical Activity and Health Congress (ISPAH) (MT) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Dr Marko Tainio both chaired a session and presented at the 7th International Society for Physical Activity and Health Congress (ISPAH), held in London on 15 October 2018. |
Year(s) Of Engagement Activity | 2018 |
Description | 7th International Society for Physical Activity and Health Congress (LG) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Dr Leandro Garcia presented at the 7th International Society for Physical Activity and Health Congress held in London on 15 October 2018. |
Year(s) Of Engagement Activity | 2018 |
Description | All party Parliamentary Cycling Committee (JW) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Dr James Woodcock was on the panel at the All party Parliamentary Cycling Committee held in the Houses of Parliament on 26 February 2018. |
Year(s) Of Engagement Activity | 2018 |
URL | https://allpartycycling.org/2019/03/01/meeting-with-public-health-england/ |
Description | Comments in The Lancet Planetary Health feature (RG) |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Dr Rahul Goel was interviewed for a feature article in The Lancet Planetary Health, and his comments were subsequently published. The article was shared by 3 news outlets and 31 tweeters. |
Year(s) Of Engagement Activity | 2019 |
URL | https://doi.org/10.1016/S2542-5196(19)30247-5 |
Description | Conversation - Active transport is a gender equality issue |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Conversation article by Rahul Goel and Oyinlola Oyebode "From walking to cycling, how we get around a city is a gender equality issue - new research" for Transportation article "Gender differences in active travel in major cities across the world" on which James Woodcock was senior author and Louise Foley and Lambed Tatah co-authors Conversation article republished in at least 5 online news outlets, including the World Economic Forum news blog https://www.weforum.org/agenda/2022/02/cycling-city-gender-equality-research-transport/. News report in cycling industry news https://cyclingindustry.news/moving-around-a-city-is-a-gender-equality-issue-shows-global-study/ |
Year(s) Of Engagement Activity | 2022 |
URL | https://theconversation.com/from-walking-to-cycling-how-we-get-around-a-city-is-a-gender-equality-is... |
Description | Expert consultation on risk communication and intervention to reduce exposure and to minimize the health effects of air pollution (MT) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Audience: Academics and policy makers, including World Health Organization. Session online where Dr Marko Tainio gave his discussant: Review the evidence on the benefit of physical activity [definition of PA, cycling to work, leisure or work with heavy exercise] versus the harms of air pollution, also in relation to population specific characteristics and discuss practical advice |
Year(s) Of Engagement Activity | 2019 |
Description | High-level Roundtable on Cities and sustainable infrastructure in South Asia (JW) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Dr James Woodcock was invited to speak at the High-level Roundtable on Cities and sustainable infrastructure in South Asia meeting, held in Delhi, India. |
Year(s) Of Engagement Activity | 2018 |
Description | International Society of Exposure Science (ISES)-International Society for Environmental Epidemiology (ISEE) Joint Annual Meeting (MT) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Dr Marko Tainio chaired and spoke at the International Society of Exposure Science (ISES)-International Society for Environmental Epidemiology (ISEE) Joint Annual Meeting, held in Ottawa, Canada, on 26 August 2018. |
Year(s) Of Engagement Activity | 2018 |
Description | International Symposium on Safety of Vulnerable Road Users, 2019 Changsha, China (RG) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Dr Rahul Goel presented 'Effective police enforcement: what works' at the International Symposium on Safety of Vulnerable Road Users 2019 held in Changsha, China. |
Year(s) Of Engagement Activity | 2019 |
Description | MIT Technology Review 'Goodbye, census-hello, Street View' (RG, JW) |
Form Of Engagement Activity | A magazine, newsletter or online publication |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | News article on MIT Technology Review 'Goodbye, census-hello, Street View' https://www.technologyreview.com/s/610293/goodbye-census-hello-street-view/ on Google Street View paper. |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.technologyreview.com/s/610293/goodbye-census-hello-street-view/ |
Description | Modelling World Predicting mode share with Google Street View (JW) |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Dr James Woodcock presented a talk on Predicting mode share with Google Street View at the Modelling World conference held in Birmingham in June 2018. |
Year(s) Of Engagement Activity | 2018 |
URL | http://landor.co.uk/modellingworld/2018/home.php |
Description | Press Release - Google Street View travel patterns (RG, JW) |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Media (as a channel to the public) |
Results and Impact | Article in Futurism https://futurism.com/gsv-google-street-view-public-health/ Indian Express http://indianexpress.com/article/technology/social/google-street-view-can-map-travel-patterns-in-cities-study-5163589/ and six other online news outlets. Authors were subsequently invited on 7 May 2018 to attend a Google Street View summit on 30/31 May 2018 to participate in dscussions on how to use view imagery to index ground-level observations that enable socioeconomic insights. |
Year(s) Of Engagement Activity | 2018 |
URL | https://eurekalert.org/pub_releases/2018-05/uoc-ugs050118.php |
Description | ReVisioning Transport and Health (JW) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Dr James Woodcock organised a workshop and hackathon on new and emerging big image data to understand transport and health. The workshop was very well attended and provided ample networking opportunities. |
Year(s) Of Engagement Activity | 2019 |
URL | https://sites.google.com/view/transportcam2019/ |
Description | Travel to work in India: Future concerns (JW) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Dr James Woodcock provided information for the "Travel to work in India: Current patterns and Future Concerns" report from the Transportation research and Injury Prevention Programme (TRIPP) at the Indian Institute of Technology Delhi. Urban structure is very closely linked to the mobility patterns of city residents. An understanding of city mobility patterns has a major impact on residents well being both directly and indirectly. Access to employment, education and health and recreation facilities have to be enabled by safe, green and inclusive transport systems. Reliable data on mobility patterns is a pre requisite to understanding many complex issues that are faced by cities today. Census 2011 has for the first time in India included two questions on travel: We have summarized the responses to this questions in a brief report. A round table discussion on "Travel to work in India: Future concerns" was organized on 15th May, 2018 at IIT Delhi. The participants discussed the following themes: I Travel and city Structure with reference to Pedestrians, and bicyclists. Broadly focusing on the following questions: What lessons do we have from census travel patterns? Are we designing cities for pedestrians and bicyclists? II City Structure, planning and regulatory measures with reference to trips by para transit systems, bus and metro systems. Broadly focusing on the following questions: What lessons do we have from census travel patterns? Are we planning cities and governance structures for public transport systems? List of participants is enclosed. |
Year(s) Of Engagement Activity | 2018 |
URL | http://tripp.iitd.ernet.in/assets/publication/WorkTravelReport.pdf |
Description | Unit research news - Seven is the magic number |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Unit and CEDAR News blog post "Seven is the magic number: new global study identifies a threshold for gender equality in cycling" for paper "Cycling behaviour in 17 countries across 6 continents: levels of cycling, who cycles, for what purpose, and how far? " https://www.tandfonline.com/doi/full/10.1080/01441647.2021.1915898. Shared on Unit and CEDAR social media channels. Reported in El Pais https://elpais.com/clima-y-medio-ambiente/2021-06-21/por-que-las-mujeres-pedalean-mucho-menos-que-los-hombres.html and Planetizen https://www.planetizen.com/news/2021/05/113365-study-when-women-ride-bikes-everyone-rides-more. Later cited by SciBlogs https://sciblogs.co.nz/public-health-expert/2021/11/24/more-than-147km-the-transformative-potential-of-the-wellington-bike-network-plan/. CEDAR blog post received 125 unique views, Unit blog post received 87 unique views. Tweeted by >350 twitter users. CEDAR tweets were retweeted 20+ times. |
Year(s) Of Engagement Activity | 2021 |
URL | https://www.mrc-epid.cam.ac.uk/blog/2021/05/10/global-study-identifies-threshold-for-gender-equality... |
Description | University of Chicago research news article - Transforming Street View Into a Worldwide Transportation Census (JW) |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Media (as a channel to the public) |
Results and Impact | News article discussed collaboration with CEDAR Public Health Modelling group |
Year(s) Of Engagement Activity | 2019 |
URL | https://rcc.uchicago.edu/about-rcc/news-features/transforming-street-view-worldwide-transportation-c... |
Description | Urban Health Initiative workshop in Accra, Ghana (JW) |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Dr James Woodcock was invited to present the model at the workshop for stakeholders on urban health models in Accra, Ghana, on 26 June 2018. |
Year(s) Of Engagement Activity | 2018 |