Evidence map›Paper›PMID 40108327›Full record

ArticleScientific reports2025

Accelerated global burden of depressive disorders during the COVID-19 pandemic from 2019 to 2021.

Jinlei Zhou, Yuan Zhang, Shuangshuang He, Sen Xu, Qice Sun, Tingxiao Zhao, Yaqin Dai

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. The hippocampus as a central hub in ketamine's antidepressant action: from molecules to circuit rewiring.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Review
  5. Frontiers in microbiology · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
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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

7 authors.

Jinlei Zhou *Center for Plastic & Reconstructive Surgery, Department of Orthopedics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), shangtang Road 158#, Hangzhou, Zhejiang, China.
Yuan Zhang *Department of Rheumatology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Shuangshuang He *Jiashan County Maternal and Child Health Hospital, Zhejiang, Jiaxing, China.
Sen XuZhejiang Chinese Medical University, Hangzhou, China.
Qice SunDepartment of Rheumatology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
Tingxiao ZhaoCenter for Plastic & Reconstructive Surgery, Department of Orthopedics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), shangtang Road 158#, Hangzhou, Zhejiang, China. spinezhaotingxiao@163.com.
Yaqin DaiCenter for Plastic & Reconstructive Surgery, Department of Orthopedics, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), shangtang Road 158#, Hangzhou, Zhejiang, China. dyqjzwk@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A thorough and current analysis of the burden and evolving trends in depressive disorders during the COVID-19 pandemic from 2019 to 2021 remains unavailable. Employing the Global Burden of Disease (GBD) 2021 database, we evaluated the burden of depressive disorders at the global, regional, and national levels, stratifying the analysis by age, gender, and socio-demographic index (SDI). To examine trends in depressive disorders during the epidemic, we calculated the estimated annual percentage change (EAPC) in age-standardized incidence rates (ASIR), age-standardized prevalence rates (ASPR), and age-standardized DALYs rates (ASDR) across all levels from 2019 to 2021. Furthermore, we performed a frontier analysis of depressive disorders across various countries, incorporating risk factor analyses at multiple levels. In 2021, the global incidence of depressive disorders stood at 357.43 million, while the prevalence was recorded at 332.41 million, accompanied by 56.33 million disability-adjusted life years (DALYs). Throughout the COVID-19 pandemic, there was a notable upward trend in ASIR (EAPC = 8.33 [-0.46 to 17.9]), ASPR (EAPC = 6.02 [0.28 to 12.09]), and ASDR (EAPC = 7.13 [-0.18 to 14.97]) for depressive disorders on a global scale. The burden of depressive disorders is most pronounced among females and individuals aged 60 to 64 within their respective subgroups. From 1990 to 2021, the burden of depressive disorders consistently remained highest in the low SDI region; however, it experienced the most significant increase in the high SDI region during the COVID-19 pandemic from 2019 to 2021. In 2021, the burden of depressive disorders was highest in central sub-Saharan Africa, Greenland, and Uganda, while the Andean region of Latin America, along with Bulgaria and Belarus, experienced the most significant increase in depressive disorders during the COVID-19 pandemic. Globally, bullying victimization, intimate partner violence, and childhood sexual abuse contributed to 6.47%, 4.91%, and 2.65% of the ASDR for depressive disorders, respectively. The global burden of depressive disorders has markedly increased during the COVID-19 pandemic, gradually shifting from low to high SDI regions, particularly in North America and Europe.

Indexed as

COVID-19Depressive DisorderAdolescentAdultAgedCost of IllnessDisability-Adjusted Life YearsFemaleGlobal Burden of DiseaseGlobal HealthHumansIncidenceMaleMiddle AgedPandemicsPrevalenceCOVID-19 pandemicDepressive disordersEstimated annual percentage changesGlobal burden of diseaseSocio-demographic index

Identifiers

PMID40108327
PMCPMC11923300

What OpenQuestion holds

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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.