Evidence map›Paper›PMID 39717862›Full record

ArticleIJID regions2025

The relationship between long COVID, labor productivity, and socioeconomic losses in Japan: A cohort study.

Shunichiro Konishi, Katsunori Masaki, Kyoko Shimamoto, Yoko Ibuka, Rei Goto, Ho Namkoong, Shotaro Chubachi, Hideki Terai, Takanori Asakura, Jun Miyata and 16 more

Abstract read
In one paragraph

Article in IJID regions, 2025. 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

26 authors.

Shunichiro KonishiDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Katsunori MasakiDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Kyoko ShimamotoKeio Global Research Institute, Tokyo, Japan.
Yoko IbukaKeio University Faculty of Economics, Tokyo, Japan.
Rei GotoKeio University Graduate School of Business Administration, Tokyo, Japan.
Ho NamkoongDepartment of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan.
Shotaro ChubachiDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Hideki TeraiDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Takanori AsakuraDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Jun MiyataDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Shuhei AzekawaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Kensuke NakagawaraDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Hiromu TanakaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Atsuho MoritaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.
Norihiro HaradaDepartment of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan.
Hitoshi SasanoDepartment of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan.
Ai NakamuraDepartment of Respiratory Medicine, Juntendo University Faculty of Medicine and Graduate School of Medicine, Tokyo, Japan.
Yu KusakaOme Municipal General Hospital, Ome, Japan.
Takehiko OhbaOme Municipal General Hospital, Ome, Japan.
Yasushi NakanoDepartment of Pulmonary Medicine, Kawasaki Municipal Ida Hospital, Kanagawa, Japan.
Kazumi NishioDepartment of Pulmonary Medicine, Kawasaki Municipal Ida Hospital, Kanagawa, Japan.
Yukiko NakajimaDepartment of Infectious Disease, Kawasaki Municipal Ida Hospital, Kanagawa, Japan.
Shoji SuzukiDepartment of Pulmonary Medicine, Saitama City Hospital, Saitama, Japan.
Shuichi YoshidaDepartment of Pulmonary Medicine, Saitama City Hospital, Saitama, Japan.
Hiroki TatenoDepartment of Pulmonary Medicine, Saitama City Hospital, Saitama, Japan.
Koichi FukunagaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Shinjuku-ku, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: We examined shifts in labor productivity and their economic ramifications among adult patients with long COVID in Japan. Methods: A total of 396 patients were categorized into three groups based on symptom progression: non-long COVID, long COVID recovered, and long COVID persistent. Patient-reported outcomes were assessed at three time intervals: 3, 6, and 12 months after COVID-19 diagnosis. Labor productivity was gauged through presenteeism and absenteeism, measured using the World Health Organization Health and Work Performance Questionnaire. Results: Long COVID was observed in 52.7% of patients, and 29.3% of all the patients continued to experience long COVID symptoms 1 year after diagnosis. At all three time points (3, 6, and 12 months after diagnosis), the long COVID persistent group showed a statistically significant difference in absolute presenteeism compared with the non-long COVID and long COVID recovered groups ( Conclusion: The study's results revealed a notable decline in labor productivity over time, underscoring the importance of early detection and intervention to mitigate the socio-economic repercussions of long COVID, in addition to its health implications.

Indexed as

AbsenteeismEconomic impactLabor productivityLong COVIDPresenteeism

Identifiers

PMID39717862
PMCPMC11664411

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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.