Model Transition Sensitivity Analysis

描述：该项目将开发用于评估模型假设对有关传染病的分析、监测和控制决策的影响的软件。大多数分析只考虑对模型参数值变化的敏感性，而忽略了模型形式的假设(例如，确定性与随机性、ODE与离散个体)如何影响结果和伴随的决策。这项研究将：(1)进行需求分析，以指定要纳入软件的模拟引擎和功能。(2)开发并测试一个软件原型，以评估所提出方法的可行性。(3)根据样机的测试结果构建、测试和实现一个完整的软件包。(4)应用软件和方法演示了该方法及其在疾病监测和控制中的独特效益。该项目的可行性在实现前两个目标的第一阶段研究中得到了论证。该SBIR二期项目将实现目标三和目标四。该项目的技术和科学创新将彻底改变我们制定有关传染病分析、控制和监测的合理决策的能力。

DESCRIPTION: This project will develop software for assessing the impacts of model assumptions on decisions regarding the analysis, surveillance, and control of infectious diseases. Most analyses consider sensitivity only to changes in a model's parameter values, and ignore how assumptions of model form (e.g. deterministic vs. stochastic, ODE vs. discrete individual) impact results and concomitant decisions. This research will: (1) Conduct a requirements analysis to specify the simulation engines and functionality to incorporate in the software. (2) Develop and test a software prototype to evaluate feasibility of the proposed approaches. (3) Build, test and implement a complete software package based on results of the prototype. (4) Apply the software and methods to demonstrate the approach and its unique benefits for disease surveillance and control. Feasibility of this project was demonstrated in the phase I research that accomplished the first two aims. This phase II SBIR project will accomplish Aims three and four. The technologic and scientific innovations from this project will revolutionize our ability to formulate sound decisions regarding the analysis, control and surveillance of infectious diseases.