Department of Health Information Technology, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Nutrition and Metabolic Disease Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Work. 2021;70(2):377-385. doi: 10.3233/WOR-210463.
In recent years the relationship between ambient air temperature and the prevalence of viral infection has been under investigation.
The study was aimed at providing the statistical and machine learning-based analysis to investigate the influence of climatic factors on frequency of COVID-19 confirmed cases in Iran.
The data of confirmed cases of COVID-19 and some climatic factors related to 31 provinces of Iran between 04/03/2020 and 05/05/2020 was gathered from official resources. In order to investigate the important climatic factors on the frequency of confirmed cases of COVID-19 in all studied cities, a model based on an artificial neural network (ANN) was developed.
The proposed ANN model showed accuracy rates of 87.25%and 86.4%in the training and testing stage, respectively, for classification of COVID-19 confirmed cases. The results showed that in the city of Ahvaz, despite the increase in temperature, the coefficient of determination R2 has been increasing.
This study clearly showed that, with increasing outdoor temperature, the use of air conditioning systems to set a comfort zone temperature is unavoidable. Thus, the number of positive cases of COVID-19 increases. Also, this study shows the role of closed-air cycle condition in the indoor environment of tropical cities.
近年来，环境空气温度与病毒感染流行之间的关系一直受到研究。
本研究旨在提供基于统计和机器学习的分析，以调查气候因素对伊朗 COVID-19 确诊病例频率的影响。
从官方资源中收集了 2020 年 3 月 4 日至 5 月 5 日期间伊朗 31 个省份的 COVID-19 确诊病例和一些与气候有关的因素的数据。为了研究所有研究城市中 COVID-19 确诊病例频率的重要气候因素，开发了一种基于人工神经网络（ANN）的模型。
所提出的 ANN 模型在训练和测试阶段的分类准确率分别为 87.25%和 86.4%。结果表明，在阿瓦兹市，尽管温度升高，但决定系数 R2 一直在增加。
本研究清楚地表明，随着室外温度的升高，为了设置舒适区温度，使用空调系统是不可避免的。因此，COVID-19 的阳性病例数增加。此外，本研究还显示了热带城市室内环境中封闭空气循环条件的作用。
