Building an effective and highly usable epidemiology model presents two main challenges: finding the appropriate, realistic enough model that takes into account complex biological, social and environmental parameters and efficiently estimating the parameter values with which the model can accurately match the available outbreak data, provide useful projections. The reproduction number of the novel coronavirus (SARS-CoV-2) has been found to vary over time, potentially being influenced by a multitude of factors such as varying control strategies, changes in public awareness and reaction or, as a recent study suggests, sensitivity to temperature or humidity changes. To take into consideration these constantly evolving factors, the paper introduces a time dynamic, humidity-dependent SEIR-type extended epidemiological model with range-defined parameters. Using primarily the historical data of the outbreak from Northern and Southern Italy and with the help of stochastic global optimization algorithms, we are able to determine a model parameter estimation that provides a high-quality fit to the data. The time-dependent contact rate showed a quick drop to a value slightly below 2. Applying the model for the COVID-19 outbreak in the northern region of Italy, we obtained parameters that suggest a slower shrinkage of the contact rate to a value slightly above 4. These findings indicate that model fitting and validation, even on a limited amount of available data, can provide useful insights and projections, uncover aspects that upon improvement might help mitigate the disease spreading.

中文翻译：

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COVID-19 爆发的湿度相关隔室模型的参数估计

建立有效且高度可用的流行病学模型面临两个主要挑战：找到适当的、足够现实的模型，考虑复杂的生物、社会和环境参数，并有效估计模型可以准确匹配可用疫情数据的参数值，提供有用的预测。人们发现，新型冠状病毒（SARS-CoV-2）的繁殖数量会随着时间的推移而变化，可能受到多种因素的影响，例如不同的控制策略、公众意识和反应的变化，或者正如最近的一项研究表明的那样，对温度或湿度变化的敏感性。为了考虑到这些不断变化的因素，本文引入了一种具有范围定义参数的时间动态、湿度相关的 SEIR 型扩展流行病学模型。主要使用意大利北部和南部爆发的历史数据，并在随机全局优化算法的帮助下，我们能够确定模型参数估计，为数据提供高质量的拟合。与时间相关的接触率显示出快速下降至略低于 2 的值。应用意大利北部地区 COVID-19 爆发的模型，我们获得的参数表明接触率缓慢收缩至略高于 2 的值4. 这些发现表明，即使在有限数量的可用数据上，模型拟合和验证也可以提供有用的见解和预测，揭示改进后可能有助于减轻疾病传播的方面。