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Modelling the spreading rate of controlled communicable epidemics through an entropy-based thermodynamic model

机译:通过基于熵的热力学模型对可控制传染病的传播速度进行建模

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摘要

A model based on a thermodynamic approach is proposed for predicting the dynamics of communicable epidemics assumed to be governed by controlling efforts of multiple scales so that an entropy is associated with the system. All the epidemic details are factored into a single and time-dependent coefficient, the functional form of this coefficient is found through four constraints, including notably the existence of an inflexion point and a maximum. The model is solved to give a log-normal distribution for the spread rate, for which a Shannon entropy can be defined. The only parameter, that characterizes the width of the distribution function, is uniquely determined through maximizing the rate of entropy production. This entropy-based thermodynamic (EBT) model predicts the number of hospitalized cases with a reasonable accuracy for SARS in the year 2003. This EBT model can be of use for potential epidemics such as avian influenza and H7N9 in China.
机译:提出了一种基于热力学方法的模型,用于预测假定通过控制多个尺度的努力来控制的传染病的动力学,从而使熵与系统相关联。所有流行病的详细信息都被分解为一个与时间相关的系数,该系数的功能形式是通过四个约束条件找到的,特别是存在拐点和最大值。对该模型进行求解以给出扩展速率的对数正态分布,为此可以定义香农熵。表征分布函数宽度的唯一参数是通过最大化熵产生速率来唯一确定的。该基于熵的热力学(EBT)模型预测2003年SARS的住院病例数具有合理的准确性。该EBT模型可用于潜在的流行病,如中国的禽流感和H7N9。

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