Evidence map›Paper›PMID 34718594›Full record

SynthesisInternational journal of epidemiology2022

Reduced mortality during the COVID-19 outbreak in Japan, 2020: a two-stage interrupted time-series design.

Daisuke Onozuka, Yuta Tanoue, Shuhei Nomura, Takayuki Kawashima, Daisuke Yoneoka, Akifumi Eguchi, Chris Fook Sheng Ng, Kentaro Matsuura, Shoi Shi, Koji Makiyama and 15 more

Abstract readMeta-Analysis
In one paragraph

Synthesis in International journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
–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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Inferring the true number of SARS-CoV-2 infections in Japan.Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy · 2022
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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

25 authors.

Daisuke OnozukaDepartment of Medical Informatics and Clinical Epidemiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.ORCID 0000-0001-9596-9188
Yuta TanoueInstitute for Business and Finance, Waseda University, Tokyo, Japan.
Shuhei NomuraDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.
Takayuki KawashimaDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.
Daisuke YoneokaDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.ORCID 0000-0002-3525-5092
Akifumi EguchiDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.
Chris Fook Sheng NgSchool of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan.ORCID 0000-0003-1025-0807
Kentaro MatsuuraDepartment of Management Science, Graduate School of Engineering, Tokyo University of Science, Tokyo, Japan.
Shoi ShiDepartment of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Koji MakiyamaHOXO-M Inc., Tokyo, Japan.
Shinya UryuCenter for Environmental Biology and Ecosystem Studies, National Institute for Environmental Studies (NIES), Tokyo, Japan.
Yumi KawamuraRIKEN Center for Sustainable Resource Science, Saitama, Japan.
Shinichi TakayanagiHOXO-M Inc., Tokyo, Japan.
Stuart GilmourGraduate School of Public Health, St. Luke's International University, Tokyo, Japan.ORCID 0000-0002-6556-0995
Takehiko I HayashiCenter for Health and Environmental Risk Research, National Institute for Environmental Studies, Ibaraki, Japan.
Hiroaki MiyataDepartment of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.
Francesco SeraDepartment of Statistics, Computer Science and Applications 'G. Parenti', University of Florence, Florence, Italy.ORCID 0000-0002-8890-6848
Tomimasa SunagawaInfectious Disease Surveillance Center, the National Institute of Infectious Diseases, Tokyo, Japan.
Takuri TakahashiInfectious Disease Surveillance Center, the National Institute of Infectious Diseases, Tokyo, Japan.
Yuuki TsuchihashiInfectious Disease Surveillance Center, the National Institute of Infectious Diseases, Tokyo, Japan.
Yusuke KobayashiInfectious Disease Surveillance Center, the National Institute of Infectious Diseases, Tokyo, Japan.
Yuzo ArimaInfectious Disease Surveillance Center, the National Institute of Infectious Diseases, Tokyo, Japan.
Kazuhiko KanouInfectious Disease Surveillance Center, the National Institute of Infectious Diseases, Tokyo, Japan.
Motoi SuzukiInfectious Disease Surveillance Center, the National Institute of Infectious Diseases, Tokyo, Japan.
Masahiro HashizumeDepartment of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Funding

Japan Society for the Promotion of ScienceJapan Society for the Promotion of Science (JSPS) KAKENHI JP18K11666KAKENHI JP18K11666Ministry of Health, Labour and Welfare JPMH20HA2007
6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19) continues to be a major global health burden. This study aims to estimate the all-cause excess mortality occurring in the COVID-19 outbreak in Japan, 2020, by sex and age group.

methodsDaily time series of mortality for the period January 2015-December 2020 in all 47 prefectures of Japan were obtained from the Ministry of Health, Labour and Welfare, Japan. A two-stage interrupted time-series design was used to calculate excess mortality. In the first stage, we estimated excess mortality by prefecture using quasi-Poisson regression models in combination with distributed lag non-linear models, adjusting for seasonal and long-term variations, weather conditions and influenza activity. In the second stage, we used a random-effects multivariate meta-analysis to synthesize prefecture-specific estimates at the nationwide level.

resultsIn 2020, we estimated an all-cause excess mortality of -20 982 deaths [95% empirical confidence intervals (eCI): -38 367 to -5472] in Japan, which corresponded to a percentage excess of -1.7% (95% eCI: -3.1 to -0.5) relative to the expected value. Reduced deaths were observed for both sexes and in all age groups except those aged <60 and 70-79 years.

conclusionsAll-cause mortality during the COVID-19 outbreak in Japan in 2020 was decreased compared with a historical baseline. Further evaluation of cause-specific excess mortality is warranted.

Indexed as

COVID-19Disease OutbreaksFemaleHumansInterrupted Time Series AnalysisJapanMaleMortalitySARS-CoV-2All-cause deathCOVID-19excess mortalityJapantwo-stage interrupted time-series design

Identifiers

PMID34718594
PMCPMC8856001

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.