Universidade Presbiteriana Mackenzie, PPGEEC, São Paulo, SP, Brazil; Universidade de São Paulo, Escola Politécnica, São Paulo, SP, Brazil; Universidade Presbiteriana Mackenzie, Escola de Engenharia, Rua da Consolação, n.896, São Paulo 01302-907, SP, Brazil.
Universidade Presbiteriana Mackenzie, PPGEEC, São Paulo, SP, Brazil.
Comput Methods Programs Biomed. 2020 Nov;196:105707. doi: 10.1016/j.cmpb.2020.105707. Epub 2020 Aug 18.
One of the main goals of epidemiological studies is to build models capable of forecasting the prevalence of a contagious disease, in order to propose public health policies for combating its propagation. Here, the aim is to evaluate the influence of immune individuals in the processes of contagion and recovery from varicella. This influence is usually neglected.
An epidemic model based on probabilistic cellular automaton is introduced. By using a genetic algorithm, the values of three parameters of this model are determined from data of prevalence of varicella in Belgium and Italy, in a pre-vaccination period.
This methodology can predict the varicella prevalence (with average relative error of 2%-4%) in these two European countries. Belgium data can be explained by ignoring the role of immune individuals in the infection propagation; however, Italy data can be explained by considering contagion exclusively mediated by immune individuals.
The role of immune individuals should be accurately delineated in investigations on the dynamics of disease propagation. In addition, the proposed methodology can be adapted for evaluating, for instance, the role of asymptomatic carriers in the novel coronavirus spread.
流行病学研究的主要目标之一是建立能够预测传染病流行率的模型，以便提出防治传染病传播的公共卫生政策。在这里，我们旨在评估免疫个体在水痘感染和康复过程中的影响。这种影响通常被忽视。
引入了一种基于概率元胞自动机的传染病模型。通过使用遗传算法，从比利时和意大利在疫苗接种前的水痘流行数据中确定了该模型的三个参数的值。
该方法可以预测这两个欧洲国家的水痘流行率（平均相对误差为 2%-4%）。可以忽略免疫个体在感染传播中的作用来解释比利时的数据；然而，考虑到仅由免疫个体介导的感染，意大利的数据可以得到解释。
在疾病传播动力学的研究中，应准确描述免疫个体的作用。此外，所提出的方法可以适应于评估无症状携带者在新型冠状病毒传播中的作用等。
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