Analysis of reporting lag in daily data of COVID-19 in Japan

Taro Kanatani and Kuninori Nakagawa ()
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Taro Kanatani: Shiga University
Kuninori Nakagawa: University of Hyogo

Letters in Spatial and Resource Sciences, 2023, vol. 16, issue 1, No 12, 20 pages

Abstract: Abstract 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.

Keywords: Congestion; Reporting delay; Public health; COVID-19 (search for similar items in EconPapers)
JEL-codes: H75 I18 R50 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s12076-023-00334-y

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