Literature DB >> 17362405

A risk-based method for modeling traffic fatalities.

Kavi Bhalla1, Majid Ezzati, Ajay Mahal, Joshua Salomon, Michael Reich.   

Abstract

We describe a risk-based analytical framework for estimating traffic fatalities that combines the probability of a crash and the probability of fatality in the event of a crash. As an illustrative application, we use the methodology to explore the role of vehicle mix and vehicle prevalence on long-run fatality trends for a range of transportation growth scenarios that may be relevant to developing societies. We assume crash rates between different road users are proportional to their roadway use and estimate case fatality ratios (CFRs) for the different vehicle-vehicle and vehicle-pedestrian combinations. We find that in the absence of road safety interventions, the historical trend of initially rising and then falling fatalities observed in industrialized nations occurred only if motorization was through car ownership. In all other cases studied (scenarios dominated by scooter use, bus use, and mixed use), traffic fatalities rose monotonically. Fatalities per vehicle had a falling trend similar to that observed in historical data from industrialized nations. Regional adaptations of the model validated with local data can be used to evaluate the impacts of transportation planning and safety interventions, such as helmets, seat belts, and enforcement of traffic laws, on traffic fatalities.

Mesh:

Year:  2007        PMID: 17362405     DOI: 10.1111/j.1539-6924.2006.00864.x

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  9 in total

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Review 2.  Ride-Hailing and Road Traffic Crashes: A Critical Review.

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3.  Modelling of road traffic fatalities in India.

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Journal:  Accid Anal Prev       Date:  2018-03

4.  Obesity-related health impacts of fuel excise taxation- an evidence review and cost-effectiveness study.

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5.  Economic development and road traffic fatalities in Russia: analysis of federal regions 2004-2011.

Authors:  Huan He; Nino Paichadze; Adnan A Hyder; David Bishai
Journal:  Inj Epidemiol       Date:  2015-08-27

6.  Better transport accessibility, better health: a health economic impact assessment study for Melbourne, Australia.

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7.  Health impact modelling of active travel visions for England and Wales using an Integrated Transport and Health Impact Modelling Tool (ITHIM).

Authors:  James Woodcock; Moshe Givoni; Andrei Scott Morgan
Journal:  PLoS One       Date:  2013-01-09       Impact factor: 3.240

8.  The societal costs and benefits of commuter bicycling: simulating the effects of specific policies using system dynamics modeling.

Authors:  Alexandra Macmillan; Jennie Connor; Karen Witten; Robin Kearns; David Rees; Alistair Woodward
Journal:  Environ Health Perspect       Date:  2014-02-04       Impact factor: 9.031

Review 9.  Land use, transport, and population health: estimating the health benefits of compact cities.

Authors:  Mark Stevenson; Jason Thompson; Thiago Hérick de Sá; Reid Ewing; Dinesh Mohan; Rod McClure; Ian Roberts; Geetam Tiwari; Billie Giles-Corti; Xiaoduan Sun; Mark Wallace; James Woodcock
Journal:  Lancet       Date:  2016-09-23       Impact factor: 79.321

  9 in total

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