Evidence map›Paper›PMID 35990314›Full record

ArticleJournal of the Japanese and international economies2022

Quantifying the impact of the Tokyo Olympics on COVID-19 cases using synthetic control methods.

Taro Esaka, Takao Fujii

Abstract read
In one paragraph

Article in Journal of the Japanese and international economies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Taro EsakaKobe City University of Foreign Studies, 9-1, Gakuenhigashi-machi, Nishi-ku, Kobe, Hyogo 651-2187, Japan.
Takao FujiiKobe City University of Foreign Studies, 9-1, Gakuenhigashi-machi, Nishi-ku, Kobe, Hyogo 651-2187, Japan and Research Fellow at the Graduate School of Economics, Kobe University, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper uses a synthetic control method (SCM) and a Ridge Augmented SCM to estimate the impact of holding the Tokyo Olympic games on the number of newly confirmed COVID-19 cases in Tokyo (Japan). Our analysis with these methods enables us to estimate the causal impact of the Tokyo Olympics on COVID-19 cases by constructing counterfactual COVID-19 cases for Tokyo (Japan) as the optimal weighted average of COVID-19 cases of OECD countries that are not affected by holding the Olympics through a data-driven approach. Based on reliable estimates obtained from different analytical settings, we find that, compared to the counterfactuals, holding the Tokyo Olympics significantly increased the daily average number of COVID-19 cases by 105 to 132 cases in Tokyo (47 to 65 cases in Japan as a whole) per million people. This result suggests that holding the Olympics likely led to the spread of COVID-19 infection in Tokyo (Japan).

Indexed as

Causal inferenceCounterfactualCOVID-19Public healthSynthetic control methodTokyo Olympics

Identifiers

PMID35990314
PMCPMC9376984

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.