DYNAMO-HIA–A Dynamic Modeling Tool for Generic Health Impact Assessments

BackgroundCurrently, 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 ResultsDYNAMO-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. ConclusionBy 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.

背景 当前尚无公开可用的标准工具，可供研究者或政策制定者在健康影响评估（Health Impact Assessment, HIA）的因果框架内，借助流行病学证据量化政策的影响。一款合格的标准工具需满足三项技术准则（真实人群、动态预测、明确的风险因素状态）与三项可用性准则（数据需求适中、模型输出丰富、普遍可及），方可在健康影响评估的实际应用场景中发挥效用。我们推出的DYNAMO-HIA（Dynamic Modeling for Health Impact Assessment，健康影响评估动态建模工具）正是这样一款通用软件工具，专为助力政策健康影响的量化评估而开发。

方法与结果 DYNAMO-HIA可量化用户指定的风险因素变化对多种疾病，进而对整体人群健康的影响，通过对比一个参考场景与一个或多个干预场景实现分析。该工具采用基于马尔可夫（Markov）的建模方法，可实现明确的风险因素状态建模与真实人群模拟。内置的参数估计模块确保仅需标准的人群水平流行病学证据，即发病率、患病率、相对风险与死亡率相关数据。DYNAMO-HIA可提供丰富的汇总指标输出——例如预期寿命与无病预期寿命——以及按年龄、性别、风险因素状态分类的详细数据（如患病率、死亡率/生存率），并覆盖时间维度。该工具通过图形用户界面进行操控，且可从互联网公开获取，保障了普遍可及性。我们通过两个示例应用演示DYNAMO-HIA的使用方法：一是导致整体酒精消费量上升的政策场景，二是量化吸烟相关疾病负担的场景。

结论 通过在健康影响评估的因果框架内兼顾适中的数据需求、普遍可及性与用户友好性，DYNAMO-HIA有望成为基于流行病学证据开展健康影响评估的标准工具。