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

Author

Listed:
  • Taro Kanatani

    (Shiga University)

  • Kuninori Nakagawa

    (University of Hyogo)

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.

Suggested Citation

  • Taro Kanatani & Kuninori Nakagawa, 2023. "Analysis of reporting lag in daily data of COVID-19 in Japan," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-20, December.
    • Handle: RePEc:spr:lsprsc:v:16:y:2023:i:1:d:10.1007_s12076-023-00334-y
    DOI: 10.1007/s12076-023-00334-y
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    References listed on IDEAS

    as
    1. Zeileis, Achim & Kleiber, Christian & Jackman, Simon, 2008. "Regression Models for Count Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i08).
    2. Chan, Stephen & Chu, Jeffrey & Zhang, Yuanyuan & Nadarajah, Saralees, 2021. "Count regression models for COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Congestion; Reporting delay; Public health; COVID-19;
    All these keywords.

    JEL classification:

    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • R50 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - General

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