Dynamo-HIA-a dynamic modeling tool for generic health impact assessments

Stefan K. Lhachimi, Wilma J. Nusselder, Henriette A. Smit, Pieter van Baal, Paolo Baili, Kathleen Bennett, Esteve Fernández, Margarete C. Kulik, Tim Lobstein, Joceline Pomerleau, Johan P. Mackenbach, Hendriek C. Boshuizen

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Currently, no standard tool is publicly available that allows researchers or policy-makers to quantify the impact of policies using epidemiological evidence within the causal framework of Health Impact Assessment (HIA). A standard tool should comply with three technical criteria (real-life population, dynamic projection, explicit risk-factor states) and three usability criteria (modest data requirements, rich model output, generally accessible) to be useful in the applied setting of HIA. With DYNAMO-HIA (Dynamic Modeling for Health Impact Assessment), we introduce such a generic software tool specifically designed to facilitate quantification in the assessment of the health impacts of policies. Methods and Results: DYNAMO-HIA quantifies the impact of user-specified risk-factor changes on multiple diseases and in turn on overall population health, comparing one reference scenario with one or more intervention scenarios. The Markov-based modeling approach allows for explicit risk-factor states and simulation of a real-life population. A built-in parameter estimation module ensures that only standard population-level epidemiological evidence is required, i.e. data on incidence, prevalence, relative risks, and mortality. DYNAMO-HIA provides a rich output of summary measures - e.g. life expectancy and disease-free life expectancy - and detailed data - e.g. prevalences and mortality/survival rates - by age, sex, and risk-factor status over time. DYNAMO-HIA is controlled via a graphical user interface and is publicly available from the internet, ensuring general accessibility. We illustrate the use of DYNAMO-HIA with two example applications: a policy causing an overall increase in alcohol consumption and quantifying the disease-burden of smoking. Conclusion: By combining modest data needs with general accessibility and user friendliness within the causal framework of HIA, DYNAMO-HIA is a potential standard tool for health impact assessment based on epidemiologic evidence.

Original languageEnglish
Article numbere33317
JournalPLoS One
Volume7
Issue number5
DOIs
Publication statusPublished - May 10 2012

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

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