Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya 466-8555, Japan.
Department of Mathematics, Faculty of Science, Suez Canal University, Ismailia 41522, Egypt.
Int J Environ Res Public Health. 2020 Jul 24;17(15):5354. doi: 10.3390/ijerph17155354.
This study analyzed the spread and decay durations of the COVID-19 pandemic in different prefectures of Japan. During the pandemic, affordable healthcare was widely available in Japan and the medical system did not suffer a collapse, making accurate comparisons between prefectures possible. For the 16 prefectures included in this study that had daily maximum confirmed cases exceeding ten, the number of daily confirmed cases follow bell-shape or log-normal distribution in most prefectures. A good correlation was observed between the spread and decay durations. However, some exceptions were observed in areas where travelers returned from foreign countries, which were defined as the origins of infection clusters. Excluding these prefectures, the population density was shown to be a major factor, affecting the spread and decay patterns, with = 0.39 ( < 0.05) and 0.42 ( < 0.05), respectively, approximately corresponding to social distancing. The maximum absolute humidity was found to affect the decay duration normalized by the population density ( > 0.36, < 0.05). Our findings indicate that the estimated pandemic spread duration, based on the multivariate analysis of maximum absolute humidity, ambient temperature, and population density (adjusted = 0.53, -value < 0.05), could prove useful for intervention planning during potential future pandemics, including a second COVID-19 outbreak.
本研究分析了日本不同都道府县 COVID-19 疫情的传播和衰退持续时间。在疫情期间,日本提供了负担得起的医疗保健服务,医疗体系并未崩溃,这使得对各都道府县进行准确比较成为可能。在本研究包括的 16 个每日最大确诊病例超过 10 例的都道府县中,大多数都道府县的每日确诊病例数呈钟形或对数正态分布。传播和衰退持续时间之间观察到了良好的相关性。然而,在一些有旅行者从国外返回的地区,即感染群的起源地,观察到了一些例外情况。排除这些都道府县后,人口密度被证明是一个主要因素,影响了传播和衰退模式,分别为 = 0.39(<0.05)和 0.42(<0.05),大致相当于社交距离。发现最大绝对湿度会影响人口密度归一化的衰退持续时间(>0.36,<0.05)。我们的研究结果表明,基于最大绝对湿度、环境温度和人口密度的多元分析(调整 = 0.53,p 值<0.05)来估计大流行传播持续时间,可能对未来潜在大流行(包括第二次 COVID-19 爆发)期间的干预计划有用。