日本新冠疫情每日数据报告延迟分析。
Analysis of reporting lag in daily data of COVID-19 in Japan.
作者信息
Kanatani Taro, Nakagawa Kuninori
机构信息
Department of Finance, Shiga University, Hikone, Shiga 522-8522 Japan.
School of Economics and Management, University of Hyogo, Kobe, Hyogo 651-2197 Japan.
出版信息
Lett Spat Resour Sci. 2023;16(1):12. doi: 10.1007/s12076-023-00334-y. Epub 2023 Mar 23.
The daily announcement of positive COVID-19 cases had a major socioeconomic impact. In Japan, it is well known that the characteristic of this number as time series data is the weekly periodicity. We assume that this periodicity is generated by changes in the timing of reporting on the weekend. We analyze a lag structure that shows how congestion that occurs over the weekend affects the number of new confirmed cases at the beginning of the following week. We refer to this reporting delay as the weekend effect. Our study aims to describe the geographical heterogeneity found in the time series of reported positive cases. We use data on the number of new positives reported by the prefectures. Our results suggest that delays generally occur in prefectures with a population of more than 2 million, including Japan's three largest metropolitan areas, Tokyo, Osaka, and Nagoya. The number of new positives was higher in the more populated prefectures. This will explain the weekend effect.
每日公布的新冠病毒阳性病例对社会经济产生了重大影响。在日本，众所周知，作为时间序列数据，这一数字的特征是具有每周周期性。我们假设这种周期性是由周末报告时间的变化所产生的。我们分析了一种滞后结构，该结构显示了周末出现的拥堵如何影响下周初新确诊病例的数量。我们将这种报告延迟称为周末效应。我们的研究旨在描述报告的阳性病例时间序列中发现的地理异质性。我们使用了各都道府县报告的新增阳性病例数量的数据。我们的结果表明，包括日本三大都市圈东京、大阪和名古屋在内，人口超过200万的都道府县普遍出现延迟。人口较多的都道府县新增阳性病例数更高。这将解释周末效应。
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