DYNAMO-HIA–A Dynamic Modeling Tool for Generic Health Impact AssessmentsReport as inadecuate




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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.



Author: Stefan K. Lhachimi , Wilma J. Nusselder, Henriette A. Smit, Pieter van Baal, Paolo Baili, Kathleen Bennett, Esteve Fernández, Ma

Source: http://plos.srce.hr/



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