Dataset Information

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

ABSTRACT:

Background

Achieving health benefits while reducing greenhouse gas emissions from transport offers a potential policy win-win; the magnitude of potential benefits, however, is likely to vary. This study uses an Integrated Transport and Health Impact Modelling tool (ITHIM) to evaluate the health and environmental impacts of high walking and cycling transport scenarios for English and Welsh urban areas outside London.

Methods

Three scenarios with increased walking and cycling and lower car use were generated based upon the Visions 2030 Walking and Cycling project. Changes to carbon dioxide emissions were estimated by environmental modelling. Health impact assessment modelling was used to estimate changes in Disability Adjusted Life Years (DALYs) resulting from changes in exposure to air pollution, road traffic injury risk, and physical activity. We compare the findings of the model with results generated using the World Health Organization's Health Economic Assessment of Transport (HEAT) tools.

Results

This study found considerable reductions in disease burden under all three scenarios, with the largest health benefits attributed to reductions in ischemic heart disease. The pathways that produced the largest benefits were, in order, physical activity, road traffic injuries, and air pollution. The choice of dose response relationship for physical activity had a large impact on the size of the benefits. Modelling the impact on all-cause mortality rather than through individual diseases suggested larger benefits. Using the best available evidence we found fewer road traffic injuries for all scenarios compared with baseline but alternative assumptions suggested potential increases.

Conclusions

Methods to estimate the health impacts from transport related physical activity and injury risk are in their infancy; this study has demonstrated an integration of transport and health impact modelling approaches. The findings add to the case for a move from car transport to walking and cycling, and have implications for empirical and modelling research.

SUBMITTER: Woodcock J

PROVIDER: S-EPMC3541403 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

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

Woodcock James J Givoni Moshe M Morgan Andrei Scott AS

PloS one 20130109 1

<h4>Background</h4>Achieving health benefits while reducing greenhouse gas emissions from transport offers a potential policy win-win; the magnitude of potential benefits, however, is likely to vary. This study uses an Integrated Transport and Health Impact Modelling tool (ITHIM) to evaluate the health and environmental impacts of high walking and cycling transport scenarios for English and Welsh urban areas outside London.<h4>Methods</h4>Three scenarios with increased walking and cycling and lo ...[more]

PMID: 23326315

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Project description:BACKGROUND:In October 2017, the United Kingdom Joint Committee on Vaccination and Immunisation (JCVI) recommended removal of one primary dose of the 13-valent pneumococcal conjugate vaccine (PCV13) from the existing 2+1 schedule (2, 4, 12 months). We conducted a mathematical modelling study to investigate the potential impact of a 1+1 (3, 12 month) schedule on invasive pneumococcal disease (IPD) and pneumococcal community-acquired pneumonia (CAP). Our results and those from a 1+1 immunogenicity study formed the key evidence reviewed by JCVI. METHODS AND FINDINGS:We developed age-structured, dynamic, deterministic models of pneumococcal transmission in England and Wales to describe the impact on IPD of 7-valent PCV (PCV7; introduced in 2006) and PCV13 (introduced in 2010). Key transmission and vaccine parameters were estimated by fitting to carriage data from 2001/2002 and post-PCV IPD data to 2015, using vaccine coverage, mixing patterns between ages, and population data. We considered various models to investigate potential reasons for the rapid increase in non-PCV13 (non-vaccine serotype [NVT]) IPD cases since 2014. After searching a large parameter space, 500 parameter sets were identified with a likelihood statistically close to the maximum and these used to predict future cases (median, prediction range from 500 parameter sets). Our findings indicated that the emergence of individual NVTs with higher virulence resulting from ongoing replacement was likely responsible; the NVT increase was predicted to plateau from 2020. Long-term simulation results suggest that changing to a 1+1 schedule would have little overall impact, as the small increase in vaccine-type IPD would be offset by a reduction in NVT IPD. Our results were robust to changes in vaccine assumptions in a sensitivity analysis. Under the base case scenario, a change to a 1+1 schedule in 2018 was predicted to produce 31 (6, 76) additional IPD cases over five years and 83 (-10, 242) additional pneumococcal-CAP cases, with together 8 (-2, 24) additional deaths, none in children under 15 years. Long-term continuation with the 2+1 schedule, or changing to a 1+1, was predicted to sustain current reductions in IPD cases in under-64-year-olds, but cases in 65+-year-olds would continue to increase because of the effects of an aging population. Limitations of our model include difficulty in fitting to past trends in NVT IPD in some age groups and inherent uncertainty about future NVT behaviour, sparse data for defining the mixing matrix in 65+-year-olds, and the methodological challenge of defining uncertainty on predictions. CONCLUSIONS:Our findings suggest that, with the current mature status of the PCV programme in England and Wales, removing one primary dose in the first year of life would have little impact on IPD or pneumococcal CAP cases or associated deaths at any age. A reduction in the number of priming doses would improve programmatic efficiency and facilitate the introduction of new vaccines by reducing the number of coadministered vaccines given at 2 and 4 months of age in the current UK schedule. Our findings should not be applied to other settings with different pneumococcal epidemiology or with immature programmes and poor herd immunity.

Project description:BackgroundReliable estimation of future trends in life expectancy and the burden of disability is crucial for ageing societies. Previous forecasts have not considered the potential impact of trends in disease incidence. The present prediction model combines population trends in cardiovascular disease, dementia, disability, and mortality to forecast trends in life expectancy and the burden of disability in England and Wales up to 2025.MethodsWe developed and validated the IMPACT-Better Ageing Model-a probabilistic model that tracks the population aged 35-100 years through ten health states characterised by the presence or absence of cardiovascular disease, dementia, disability (difficulty with one or more activities of daily living) or death up to 2025, by use of evidence-based age-specific, sex-specific, and year-specific transition probabilities. As shown in the English Longitudinal Study of Ageing, we projected continuing declines in dementia incidence (2·7% per annum), cardiovascular incidence, and mortality. The model estimates disability prevalence and disabled and disability-free life expectancy by year.FindingsBetween 2015 and 2025, the number of people aged 65 years and older will increase by 19·4% (95% uncertainty interval [UI] 17·7-20·9), from 10·4 million (10·37-10·41 million) to 12·4 million (12·23-12·57 million). The number living with disability will increase by 25·0% (95% UI 21·3-28·2), from 2·25 million (2·24-2·27 million) to 2·81 million (2·72-2·89 million). The age-standardised prevalence of disability among this population will remain constant, at 21·7% (95% UI 21·5-21·8) in 2015 and 21·6% (21·3-21·8) in 2025. Total life expectancy at age 65 years will increase by 1·7 years (95% UI 0·1-3·6), from 20·1 years (19·9-20·3) to 21·8 years (20·2-23·6). Disability-free life expectancy at age 65 years will increase by 1·0 years (95% UI 0·1-1·9), from 15·4 years (15·3-15·5) to 16·4 years (15·5-17·3). However, life expectancy with disability will increase more in relative terms, with an increase of roughly 15% from 2015 (4·7 years, 95% UI 4·6-4·8) to 2025 (5·4 years, 4·7-6·4).InterpretationThe number of older people with care needs will expand by 25% by 2025, mainly reflecting population ageing rather than an increase in prevalence of disability. Lifespans will increase further in the next decade, but a quarter of life expectancy at age 65 years will involve disability.FundingBritish Heart Foundation.

Dataset Information

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

Background

Methods

Results

Conclusions

Publications

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

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