The influenza pandemic preparedness planning tool InfluSim.
The influenza pandemic preparedness planning tool InfluSim.
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DOI：
10.1186/1471-2334-7-17
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发表时间：
2007-03-13
影响因子：
3.7
通讯作者：
Brockmann SO
中科院分区：
文献类型：
--
作者：
Eichner M;Schwehm M;Duerr HP;Brockmann SO
规划针对大流行性流感的公共卫生对策依赖于预测模型，通过这些模型可以评估不同干预策略的影响。迄今为止，研究的重点是对某些地方或特定条件下的情况作出预测，而不是设计一种可供公共卫生行政部门应用的公开的规划工具。在这里，我们提供了这样一个工具，它可以通过明确制定的结构重现，并设计为精确，现实主义和普遍性的竞争要求的最佳组合。influusim是一个基于1000多个微分方程系统的确定性隔间模型，它通过与大流行防备规划相关的临床和人口参数扩展了经典SEIR模型。它允许生成流感病例、门诊就诊、应用抗病毒治疗剂量、住院、死亡和因病损失的工作日的时间进程和累积数字，所有这些都可能与经济方面有关。该软件是用Java编写的，独立于平台运行，可以在普通台式计算机上运行。influusim是一个在线软件http://www.influsim.info，它有效地帮助公共卫生规划人员设计针对大流行性流感的最佳干预措施。它可以像复杂的计算机模拟一样再现大流行性流感的感染动态，同时提供再现性、更高的计算性能和更好的可操作性。
Planning public health responses against pandemic influenza relies on predictive models by which the impact of different intervention strategies can be evaluated. Research has to date rather focused on producing predictions for certain localities or under specific conditions, than on designing a publicly available planning tool which can be applied by public health administrations. Here, we provide such a tool which is reproducible by an explicitly formulated structure and designed to operate with an optimal combination of the competing requirements of precision, realism and generality. InfluSim is a deterministic compartment model based on a system of over 1,000 differential equations which extend the classic SEIR model by clinical and demographic parameters relevant for pandemic preparedness planning. It allows for producing time courses and cumulative numbers of influenza cases, outpatient visits, applied antiviral treatment doses, hospitalizations, deaths and work days lost due to sickness, all of which may be associated with economic aspects. The software is programmed in Java, operates platform independent and can be executed on regular desktop computers. InfluSim is an online available software http://www.influsim.info which efficiently assists public health planners in designing optimal interventions against pandemic influenza. It can reproduce the infection dynamics of pandemic influenza like complex computer simulations while offering at the same time reproducibility, higher computational performance and better operability.