JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
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Estimating the costs of air pollution to the National Health Service and social care: An assessment and forecast up to 2035.

PLoS Medicine 2018 July
BACKGROUND: Air pollution damages health by promoting the onset of some non-communicable diseases (NCDs), putting additional strain on the National Health Service (NHS) and social care. This study quantifies the total health and related NHS and social care cost burden due to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in England.

METHOD AND FINDINGS: Air pollutant concentration surfaces from land use regression models and cost data from hospital admissions data and a literature review were fed into a microsimulation model, that was run from 2015 to 2035. Different scenarios were modelled: (1) baseline 'no change' scenario; (2) individuals' pollutant exposure is reduced to natural (non-anthropogenic) levels to compute the disease cases attributable to PM2.5 and NO2; (3) PM2.5 and NO2 concentrations reduced by 1 μg/m3; and (4) NO2 annual European Union limit values reached (40 μg/m3). For the 18 years after baseline, the total cumulative cost to the NHS and social care is estimated at £5.37 billion for PM2.5 and NO2 combined, rising to £18.57 billion when costs for diseases for which there is less robust evidence are included. These costs are due to the cumulative incidence of air-pollution-related NCDs, such as 348,878 coronary heart disease cases estimated to be attributable to PM2.5 and 573,363 diabetes cases estimated to be attributable to NO2 by 2035. Findings from modelling studies are limited by the conceptual model, assumptions, and the availability and quality of input data.

CONCLUSIONS: Approximately 2.5 million cases of NCDs attributable to air pollution are predicted by 2035 if PM2.5 and NO2 stay at current levels, making air pollution an important public health priority. In future work, the modelling framework should be updated to include multi-pollutant exposure-response functions, as well as to disaggregate results by socioeconomic status.

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