Evidence map›Paper›PMID 36417252›Full record

ArticleEpidemiologia (Basel, Switzerland)2022

Balancing Public & Economic Health in Japan during the COVID-19 Pandemic: A Descriptive Analysis.

Gainha Kim, Justine M Natuplag, Sui Jin Lin, Jinyi Feng, Nicolas Ray

Abstract read
In one paragraph

Article in Epidemiologia (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Gainha KimGraduate Institute of International and Development Studies (IHEID), Chemin Eugène-Rigot 2, CH-1202 Geneva, Switzerland.ORCID 0000-0002-0131-0444
Justine M NatuplagInstitute of Global Health, University of Geneva, 9 Chemin des Mines, CH-1202 Geneva, Switzerland.
Sui Jin LinGeneva School of Social Sciences, University of Geneva, Uni Mail, Boulevard du Pont-d'Arve 40, CH-1205 Geneva, Switzerland.ORCID 0000-0002-7495-6051
Jinyi FengGeneva School of Social Sciences, University of Geneva, Uni Mail, Boulevard du Pont-d'Arve 40, CH-1205 Geneva, Switzerland.
Nicolas RayInstitute of Global Health, University of Geneva, 9 Chemin des Mines, CH-1202 Geneva, Switzerland.ORCID 0000-0002-4696-5313

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite loose restrictions and a low mortality rate due to COVID-19, Japan faced the challenge of stabilizing its economy during the pandemic. Here, we analyzed how the Japanese government attempted to maintain a balance between the health of the population and the health of the economy. We used a mix of quantitative data, information from policy documents, and news agency publications. Features of the Japanese government's handling of the pandemic include the lack of constitutional authority to enforce a lockdown, the laxer restrictions compared with other countries in which citizens were advised only to exercise self-restraint and avoid close social contact, and the existence of expert panels that had only an advisory role. Our findings address the slow initial response of the government, which feared that the 2020 Tokyo Olympics would be canceled, and the increased testing when the Olympics were postponed, as well as the expansion of vaccination efforts after the Olympics. In addition, there was a targeted campaign to promote national travel to increase economic revenue in the tourism sector, but this led to an increase in COVID-19 cases.

Indexed as

2020 Tokyo OlympicsDiamond Princess CruiseGo to Travel CampaignJapan COVID-19 policiesJapanese politicsShinzo Abe

Identifiers

PMID36417252
PMCPMC9620936

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.