Snowball et al 2018a - Revision history

Scipediacontent at 20:04, 1 February 2021

2021-02-01T20:04:46Z

Scipediacontent: Scipediacontent moved page Draft Content 707757206 to Snowball et al 2018a

2021-01-21T13:55:43Z

Scipediacontent moved page Draft Content 707757206 to Snowball et al 2018a

Scipediacontent: Created page with " == Abstract == Resumen de la comunicaciÃ³n [EN] The work presented here demonstrates the potential of new generation data arising from innovative policies (based on persua..."

2021-01-21T13:55:40Z

Created page with " == Abstract == Resumen de la comunicaciÃ³n [EN] The work presented here demonstrates the potential of new generation data arising from innovative policies (based on persua..."

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== Abstract ==

Resumen de la comunicaciÃ³n [EN] The work presented here demonstrates the potential of new generation data arising from innovative policies (based on persuasive technologies) in the transport sector. Improved understanding of the spatial distribution of health impacts arising from the introduction of new travel initiatives will support more targeted and efficient policy development across both the transport and health sectors. Typical health impacts include those arising from changes in levels of personal activity with alternative mode choices. With a sectoral approach to policy development, positive impacts for one sector (i.e. improved transport services) may be negated by dis-benefits in another (e.g. low levels of active travel choice and increased obesity related disease burden). The horizontal notion of equity (Thomopoulos, Grant-Muller and Tight, 2009) is applied using a range of transport-related health outcomes including cancer, heart disease and depression. The research methodology interfaces new generation âTrack and Traceâ information on individuals location and mode choices (detected as mobile phone app-based sensor data) with a new integrated transport and health model (IHITM), finally calculating an equity indicator based on distributional impacts. Grant-Muller, S.; Hodgson, F.; Harrison, G.; Malleson, N.; Redfern, T.; Snowball, R. (2018). Transport-Health Equity Outcomes from mobile phone location data â a case study. En 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018). Editorial Universitat PolitÃ¨cnica de ValÃ¨ncia. 256-256. https://doi.org/10.4995/CARMA2018.2018.8349 OCS 256 256

== Original document ==

The different versions of the original document can be found in:

* [http://hdl.handle.net/10251/111922 http://hdl.handle.net/10251/111922]

* [http://ocs.editorial.upv.es/index.php/CARMA/CARMA2018/paper/download/8349/4305 http://ocs.editorial.upv.es/index.php/CARMA/CARMA2018/paper/download/8349/4305]

* [http://ocs.editorial.upv.es/index.php/CARMA/CARMA2018/paper/viewFile/8349/4305 http://ocs.editorial.upv.es/index.php/CARMA/CARMA2018/paper/viewFile/8349/4305],
: [http://dx.doi.org/10.4995/carma2018.2018.8349 http://dx.doi.org/10.4995/carma2018.2018.8349]

* [https://riunet.upv.es/handle/10251/111922 https://riunet.upv.es/handle/10251/111922],
: [http://ocs.editorial.upv.es/index.php/CARMA/CARMA2018/paper/viewFile/8349/4305 http://ocs.editorial.upv.es/index.php/CARMA/CARMA2018/paper/viewFile/8349/4305],
: [https://academic.microsoft.com/#/detail/2884283483 https://academic.microsoft.com/#/detail/2884283483]

← Older revision		Revision as of 20:04, 1 February 2021
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	== Abstract ==		== Abstract ==

−	Resumen de la ~~comunicaciÃ³n~~ [EN] The work presented here demonstrates the potential of new generation data arising from innovative policies (based on persuasive technologies) in the transport sector. Improved understanding of the spatial distribution of health impacts arising from the introduction of new travel initiatives will support more targeted and efficient policy development across both the transport and health sectors. Typical health impacts include those arising from changes in levels of personal activity with alternative mode choices. With a sectoral approach to policy development, positive impacts for one sector (i.e. improved transport services) may be negated by dis-benefits in another (e.g. low levels of active travel choice and increased obesity related disease burden). The horizontal notion of equity (Thomopoulos, Grant-Muller and Tight, 2009) is applied using a range of transport-related health outcomes including cancer, heart disease and depression. The research methodology interfaces new generation ~~âTrack~~ and ~~Traceâ~~ information on individuals location and mode choices (detected as mobile phone app-based sensor data) with a new integrated transport and health model (IHITM), finally calculating an equity indicator based on distributional impacts. Grant-Muller, S.; Hodgson, F.; Harrison, G.; Malleson, N.; Redfern, T.; Snowball, R. (2018). Transport-Health Equity Outcomes from mobile phone location data ~~â~~ a case study. En 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018). Editorial Universitat ~~PolitÃ¨cnica~~ de ~~ValÃ¨ncia~~. 256-256. https://doi.org/10.4995/CARMA2018.2018.8349 OCS 256 256	+	Resumen de la comunicación [EN] The work presented here demonstrates the potential of new generation data arising from innovative policies (based on persuasive technologies) in the transport sector. Improved understanding of the spatial distribution of health impacts arising from the introduction of new travel initiatives will support more targeted and efficient policy development across both the transport and health sectors. Typical health impacts include those arising from changes in levels of personal activity with alternative mode choices. With a sectoral approach to policy development, positive impacts for one sector (i.e. improved transport services) may be negated by dis-benefits in another (e.g. low levels of active travel choice and increased obesity related disease burden). The horizontal notion of equity (Thomopoulos, Grant-Muller and Tight, 2009) is applied using a range of transport-related health outcomes including cancer, heart disease and depression. The research methodology interfaces new generation ‘Track and Trace’ information on individuals location and mode choices (detected as mobile phone app-based sensor data) with a new integrated transport and health model (IHITM), finally calculating an equity indicator based on distributional impacts. Grant-Muller, S.; Hodgson, F.; Harrison, G.; Malleson, N.; Redfern, T.; Snowball, R. (2018). Transport-Health Equity Outcomes from mobile phone location data – a case study. En 2nd International Conference on Advanced Reserach Methods and Analytics (CARMA 2018). Editorial Universitat Politècnica de València. 256-256. https://doi.org/10.4995/CARMA2018.2018.8349 OCS 256 256

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