The BEST-COST R package, ‘healthiar’, is now publicly available on GitHub for researchers to use in their own work assessing health impact assessments and environmental stressors.
The healthiar R package is a calculation tool for quantifying and monetising the burden of disease attributable to different environmental exposures (including air and noise pollution), by using different calculation pathways and input data. It combines three dimensions – health, monetisation, and social aspects – to present a fuller understanding of the socioeconomic costs resulting from pollution. It comes not only with the code, but also with function descriptions and vignette to guide users on how to use it.
As a flexible programming resource, healthiar can be used to build a more solid basis for evidence-based policy making. It works with different data formats and provides multiple calculation pathways to allow different users to transform data on health and exposure into attributable health impacts, including on morbidity and mortality rates, as well as cost estimates. By being able to quantify the health impacts from air and noise pollution, researchers can provide strong, evidence-based input for policymaking. It also helps users measure the social inequalities exacerbated by environmental stressors, such as by looking at levels of social deprivation and other vulnerable factors including age and gender.
BEST-COST will continue to work with healthiar by applying it to our case study countries to test the code performance, as part of our work to improve research methods exploring how environmental stressors impact our health. A Python version of healthiar will become available in 2026.
Access to the R package, as well as information on citation, is available here.
To view the presentation on how to use healthiar, please click here. The slides and workshop recording are also available online here, which will be kept up to date.
If you would like to book a demonstration of healthiar, please contact alberto.castrofernandez@swisstph.ch and axel.luyten@swisstph.ch.
