Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic — TEI-tagged view

Damian Santomauro, Ana Maria Mantilla Herrera, Jamileh Shadid, Peng Zheng, Charlie Ashbaugh, David M. Pigott, Cristiana Abbafati, Christopher Adolph, Joanne O Amlag, Aleksandr Y. Aravkin, Bree Bang-Jensen, Gregory J Bertolacci, Sabina Bloom, Rachel Castellano, Emma Castro, Suman Chakrabarti, Jhilik Chattopadhyay, Rebecca M Cogen, James K. Collins, Xiaochen Dai, William James Dangel, Carolyn Dapper, Amanda Deen, Megan Erickson, Samuel B Ewald, Abraham D. Flaxman, Joseph Frostad, Nancy Fullman, J Giles, Ababi Zergaw Giref, Gaorui Guo, Jiawei He, Monika Helak, Erin Hulland, Bulat Idrisov, Akiaja Lindstrom, Emily Linebarger, Paulo A. Lotufo, Rafael Lozano, Beatrice Magistro, Déborah Carvalho Malta, Johan Månsson, Fatima Marinho, Ali H. Mokdad, Lorenzo Monasta, Paulami Naik, Shuhei Nomura, James Kevin O'Halloran, Samuel M Ostroff, Maja Pasovic, Louise Penberthy, Robert C. Reiner, Grace Reinke, Antônio Luiz Pinho Ribeiro, Aleksei Sholokhov, Reed J D Sorensen, Elena A. Varavikova, Anh Vo, Rebecca Walcott, Stefanie Watson, Charles Shey Wiysonge, Bethany Zigler, Simon I Hay, Theo Vos, Christopher Murray, Harvey Whiteford, Alize J Ferrari · 2021 · health-psychology · doi:10.1016/s0140-6736(21)02143-7 · TEI xml · tagged edition · index · concepts · authors
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This record’s own method is meta-analysis, and the tags below follow from that. A review’s findings, quantities and statistics are things stated IN this paper, and some of them report results obtained elsewhere. No tag on this page names a different author. Measured across every review in this corpus, 81% of a review’s tags carry no citation at all — most of them are the review speaking. The corpus does not adjudicate the rest: read an unmarked tag as a claim this paper makes, not necessarily one it made first.
Other fields define these differently the same word, defined another way in another discipline
meta-analysis 4 fields · risk factors 2 fields
Tags on this paper every tag the record carries, whether or not the words occur in the text below — a number is how many papers in the corpus carry that tag; a tag with no number is unique to this paper
major depressive disorder4 anxiety disorders2 prevalence6 pre-pandemic baseline human mobility daily SARS-CoV-2 infection rate daily excess mortality rate COVID-19 pandemic3 risk factors4 proxies3 DisMod-MR 2.12 DALYs4 YLDs4 market research quota sampling population shocks screening measures meta-analysis20
Method, as described: systematic review restricted to surveys with a pre-pandemic baseline, then Bayesian meta-regression (MR-BRT) of the prevalence change against COVID-19 impact indicators, applied to DisMod-MR 2.1 pre-pandemic estimates for every GBD location

Our tag layer for this paper

Cross-disciplinary analysis
content-tags & facets: phenomenon · claim-type · cross-domain-transfer · mechanism · claim-relation · replication-status · limitation — grounded in the full text
phenomenona population shock raising the prevalence of common mental disorders - the same pattern seen after the 2008 and 2009 financial crises, now measured globally— “Our study is not the first to show how population shocks (ie, unexpected or unpredictable events that disrupt the environmental, health, economic, or social circumstances within a population) can increase the prevalence of depressive and anxiety disorders. In their review of mental health outcomes after the economic crisis in 2009, Frasquilho…
claim-typeexistence— “We estimated an additional 53·2 million (44·8 to 62·9) cases of major depressive disorder globally (an increase of 27·6% [25·1 to 30·3]) due to the COVID-19 pandemic, such that the total prevalence was 3152·9 cases (2722·5 to 3654·5) per 100 000 population.”
method — evidence— “First, we conducted a systematic literature review to assemble data from surveys measuring the effect of COVID-19 on the prevalence of depressive and anxiety disorders. Second, we used these data in a meta-analysis to (1) estimate the change in prevalence of major depressive disorder and anxiety disorders before versus during the COVID-19…
object of study — evidence— “In this study, we aimed to quantify the impact of the COVID-19 pandemic on the prevalence and burden of major depressive disorder and anxiety disorders globally in 2020.”
research question — evidence— “In this study, we aimed to quantify the impact of the COVID-19 pandemic on the prevalence and burden of major depressive disorder and anxiety disorders globally in 2020.”
contribution — evidence— “This study is the first to quantify the prevalence and burden of depressive and anxiety disorders by age, sex, and location globally.”
mechanismunequal exposure to consequences why women were affected more: carer and household load from school closures, lower salaries and less secure employment, and a measured rise in domestic violence during lockdowns - social channels rather than biological ones— “Additional carer and household responsibilities due to school closures or family members becoming unwell are more likely to fall on women. Women are more likely to be financially disadvantaged during the pandemic due to lower salaries, less savings, and less secure employment than their male counterparts. 17, 18, 19 They are also more likely…mechanisms[0]
mechanismdisrupted development why the young were affected more: 1.6 billion learners out of school in over 190 countries, no physical spaces for peer interaction, and a higher chance of unemployment during and after an economic crisis— “UNESCO declared COVID-19 to be the most severe disruption to global education in history, estimating 1·6 billion learners in over 190 countries to be fully or partially out of school in 2020. With school closures and wider social restrictions in place, young people have been unable to come together in physical spaces, affecting their ability…mechanisms[1]
mechanismpopulation shock the general category the paper places COVID-19 in - an unexpected event disrupting a population's environmental, health, economic or social circumstances, with the 2008-09 financial crises as its worked precedents— “Our study is not the first to show how population shocks (ie, unexpected or unpredictable events that disrupt the environmental, health, economic, or social circumstances within a population) can increase the prevalence of depressive and anxiety disorders. In their review of mental health outcomes after the economic crisis in 2009, Frasquilho…mechanisms[2]
mechanismcare interrupted at the moment of need distancing and travel restriction made medication and in-person care harder to get, services were interrupted or redirected, and people avoided seeking care for fear of infection - demand up and supply down together— “Perhaps more importantly, no reduction in the global prevalence or burden was detected for either disorder since 1990, despite compelling evidence of interventions that reduce their impact.”mechanisms[3]
critiques the body of single-location snapshot surveys of depression and anxiety during COVID-19, and the qualitative syntheses and pooled estimates built on them— “Most of the identified work consisted of surveys done for a specific location, at a snapshot in time, and indicated an increase in prevalence of depressive and anxiety disorders during the COVID-19 pandemic. We also found several systematic reviews and meta-analyses to summarise these studies; however, these studies were either qualitative…claim_relations[0]
distinguishes-from surveys of prevalence during the pandemic that lack a comparable pre-pandemic baseline - which is the design of both wang2020 and lai2020 in this corpus— “Eligible studies reported prevalence of depressive or anxiety disorders during the COVID-19 pandemic and had a pre-pandemic baseline. We used timelines for these periods as defined by each study. Prevalence surveys conducted during the pandemic could not be included without comparable pre-pandemic data”claim_relations[1]
qualifies Pirkis and colleagues' 21-country time-series finding no significant increase in suicide rates between April and July 2020— “In their time-series analysis of the impact of COVID-19 on suicide rates across 21 high-income and middle-income countries, Pirkis and colleagues 30 found no significant increases in suicide rates between April and July, 2020. This finding raises the question of whether or not the increased prevalence of major depressive disorder and anxiety…claim_relations[2]
builds-on Frasquilho and colleagues' review of mental health outcomes after the 2009 economic crisis, and the Greek and Hong Kong prevalence series that followed the 2008-09 crashes— “Our study is not the first to show how population shocks (ie, unexpected or unpredictable events that disrupt the environmental, health, economic, or social circumstances within a population) can increase the prevalence of depressive and anxiety disorders. In their review of mental health outcomes after the economic crisis in 2009, Frasquilho…claim_relations[3]
extends GBD 2019's estimates of depressive and anxiety disorder burden, which this study adjusts rather than replaces— “Because no epidemiological data from the year 2020 informed the DisMod-MR 2.1 model for major depressive disorder and anxiety disorders, the prevalence produced for 2020 by age and sex and for each of the 204 countries and territories represented the prevalence of each disorder without the impact of the COVID-19 pandemic.”claim_relations[4]
predicts future mental health surveys responding to COVID-19 or another population shock, which the authors ask to align their sampling and instruments with pre-pandemic baselines— “Researchers planning surveys during the pandemic should strive to align their sample representation and measures of mental health with existing pre-pandemic baseline estimates to ensure appropriate comparable data from before and during the pandemic.”claim_relations[5]
senseCOVID-19 impact indicator - THE PAPER PRE-EMPTS ITS OWN MISREADING AND SAYS SO OUTRIGHT: human mobility and infection rate `should not be interpreted as risk factors`. They are PROXIES for the pandemic, which is the risk factor. A reader who takes the coefficient on human mobility as an effect of mobility has read the model backwards, and the authors put the warning in the discussion rather than leaving it to be inferred— “The two COVID-19 impact indicators used in our model should not be interpreted as risk factors for major depressive disorder and anxiety disorders. The risk factor of interest was the COVID-19 pandemic, with these two indicators acting as proxies for the effect of COVID-19 in the population.”senses[0]
senseprevalence, in this paper - A MODELLED QUANTITY, NOT A MEASURED ONE, and for most of the 204 locations there is no survey behind it. DisMod-MR estimates prevalence for locations missing raw data by cascading priors down a five-level geographical hierarchy, so a country's figure can be entirely inherited from its region— “It also estimates prevalence for locations that are missing raw epidemiological data. GBD 2020 does this by estimating prevalence across a cascade down five levels of a geographical hierarchy: global, super-region, region, country or territory, and subnational locations. The prevalence from locations higher in the hierarchy act as priors for…senses[1]
sensecase, as counted here - A PROBABLE CASE ON A SCREENING SCALE, not a diagnosis. Only three diagnostic surveys existed to check against. The authors assume the predictive validity of screening thresholds did not change during the pandemic, and then give the counter-example themselves: a high anxiety-scale score in 2020 might be a natural reaction to a real threat rather than a disorder. SAME THRESHOLD PROBLEM AS lai2020, one level up— “We assumed the predictive validity between probable versus diagnosed cases using these screening measures did not change during the COVID-19 pandemic compared with before the pandemic, and therefore the change in the prevalence of probable cases would be equivalent to the change in the prevalence of diagnosed cases”senses[2]
sensepre-pandemic baseline - THE ELIGIBILITY CRITERION, AND THE ONE THAT DID THE WORK. A prevalence survey run during the pandemic was not admissible without comparable data from before it, however large or well conducted. 5,683 sources became 48. Both COVID-19 mental health papers in this corpus - wang2020 and lai2020 - are cross-sectional with no pre-pandemic measurement and would fail it— “Eligible studies reported prevalence of depressive or anxiety disorders during the COVID-19 pandemic and had a pre-pandemic baseline. We used timelines for these periods as defined by each study. Prevalence surveys conducted during the pandemic could not be included without comparable pre-pandemic data”senses[3]
sensenot associated, said of daily excess mortality - A COLLINEARITY RESULT, NOT A NULL EFFECT. Excess mortality correlates at r=0.8 with both surviving indicators, so it drops out of the model after they are controlled for. The paper says the reason. Reading it as `deaths did not affect mental health` is the opposite of what the analysis supports— “After controlling for human mobility and daily SARS-CoV-2 infection rate, daily excess mortality rate was not associated with the change in prevalence for either major depressive disorder or anxiety disorders. This was likely due to high collinearity between the daily excess mortality rate…senses[4]
controlan eligibility rule requiring a comparable PRE-PANDEMIC BASELINE, applied before any modelling: 5,683 sources found, 1,674 past title and abstract, 48 admitted — held — rules out a during-pandemic prevalence being read as a CHANGE in prevalence. Without a baseline a survey measures a level, and the level was already high - this paper's own introduction notes no reduction since 1990
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[0]
controlGBD case definitions tied to DSM-IV-TR and ICD-10 rather than to whatever each survey called a case — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
— rules out the pooled estimate being an average over incompatible definitions of depression and anxiety
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[1]
controlmarket-research quota sampling admitted but carried as a bias covariate rather than pooled with random samples — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
— rules out a non-probabilistic sampling frame inflating the estimate silently - AND THE COVARIATE EARNED ITS PLACE: cross-sectional quota studies significantly over-estimated the increase, which the model could then correct for
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[2]
controla separate bias covariate for instruments measuring depression and anxiety symptoms together, such as the K-6 — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
— rules out a combined-symptom instrument being counted as evidence about either disorder alone - and again it was measured, not assumed: those instruments overestimated the anxiety increase but not the depression increase
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[3]
controlleave-one-country-out cross-validation of the final model — partial
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
— rules out the estimates for locations with no data being untested - PARTIAL, and the authors report what it found against them: estimates stayed within their uncertainty bounds but the RANKINGS between locations moved with data availability
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[4]
controlbackward elimination on the Akaike information criterion, with each unique sample given a random intercept and random effects on the impact indicators — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
— rules out covariates surviving in the model on the analyst's preference rather than on fit
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controls[5]
controlPRISMA reporting, a protocol registered with PROSPERO before the review, and GATHER compliance with all analysis code published — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
— rules out the search and the inclusion rule being decided after the data were seen - the protocol is registered and the code is inspectable
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controls[6]
controlno language restriction on the literature search — partial
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
— rules out an English-only search compounding the geographical gap the authors already report - though it did not close it: no qualifying study came from a low- or middle-income country
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controls[7]
controlconfirming that no 2020 epidemiological data entered the DisMod-MR model, so its 2020 output is a genuine counterfactual — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
— rules out the pandemic's effect being partly inside the baseline it is measured against - the pre-pandemic prevalence for 2020 is uncontaminated by 2020
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controls[8]
controla statement that the funders had no role in design, collection, analysis or interpretation — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
— rules out a funder's interest shaping a global prevalence estimate that policy is set from
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[9]
notethe body of single-location snapshot surveys of depression and anxiety during COVID-19, and the qualitative syntheses and pooled estimates built on them — the criticism is not of any one survey but of what the set of them cannot do: no study had synthesised a global prevalence and burden for 2020, and the pooled estimates on offer did not adjust for the baseline problem
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
claim_relations[0]
notesurveys of prevalence during the pandemic that lack a comparable pre-pandemic baseline - which is the design of both wang2020 and lai2020 in this corpus — THE PAPER DOES NOT NAME THOSE TWO. What it states is the criterion, and the criterion excludes their design - both are cross-sectional with no pre-pandemic measurement, and lai2020 says so itself. The relation is to the DESIGN CLASS, not to the papers
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
claim_relations[1]
notePirkis and colleagues' 21-country time-series finding no significant increase in suicide rates between April and July 2020 — and the qualification runs BOTH ways - the authors say they have insufficient data to conclude anything, and offer that the window may have been too early rather than claiming the finding is wrong
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
claim_relations[2]
notefuture mental health surveys responding to COVID-19 or another population shock, which the authors ask to align their sampling and instruments with pre-pandemic baselines — an unusual relation to record and worth having: the paper is addressing studies that do not exist yet, and the data standard is offered as its second contribution
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
claim_relations[5]
effect directionCOVID-19 pandemic —causes→ major depressive disorder — increases
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
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concept_edges[0]
noteCOVID-19 pandemic —causes→ major depressive disorder — the paper is explicit that the PANDEMIC is the risk factor and the indicators are proxies for it, so this edge and not an indicator edge is the one it licenses
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concept_edges[0]
weightCOVID-19 pandemic —causes→ major depressive disorder — 0.9
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concept_edges[0]
auditCOVID-19 pandemic —causes→ anxiety disorders — Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but endpoint by anaphora: 'We also estimated' continues the previous sentence's estimate 'due to the COVID-19 pandemic'.
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concept_edges[1]
effect directionCOVID-19 pandemic —causes→ anxiety disorders — increases
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concept_edges[1]
weightCOVID-19 pandemic —causes→ anxiety disorders — 0.9
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concept_edges[1]
noterisk factors —distinct-from→ proxies — the distinction the paper draws about its own model, in its own discussion, before anyone could get it wrong
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concept_edges[4]
weightrisk factors —distinct-from→ proxies — 0.95
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concept_edges[4]
auditprevalence —operationalised-as→ DisMod-MR 2.1 — Audit 2026-09-28: DOUBTFUL - read against its span and kept, but prevalence is estimated by DisMod-MR 2.1; operationalised-as is loose.
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concept_edges[5]
noteprevalence —operationalised-as→ DisMod-MR 2.1 — and for locations with no raw data the operationalisation is the whole of it - the figure is a cascaded prior, not a measurement
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concept_edges[5]
weightprevalence —operationalised-as→ DisMod-MR 2.1 — 0.85
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concept_edges[5]
noteYLDs —part-of→ DALYs — AUDIT REVERSED THIS. Years lived with disability are a COMPONENT of disability-adjusted life-years, not the container. I had written it backwards and then written a note explaining why backwards was acceptable. For these two disorders the component is the whole - DALYs are composed entirely of YLDs, because neither is counted as an underlying cause of death - and that is what makes the containment total here rather than partial
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concept_edges[6]
auditmarket research quota sampling —causes→ prevalence — Audit 2026-09-28: RESTORED AND DOUBTFUL - the full span was re-read; kept, but the full span says studies using market research quota sampling 'significantly over-estimated the increase in disorder prevalence' - the relation is stated, but 'causes prevalence' drops that it is an OVER-ESTIMATE of the increase; the withdrawal said the span only listed the sampling as a data source. The earlier withdrawal is kept in the record.
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concept_edges[7]
effect directionmarket research quota sampling —causes→ prevalence — increases
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concept_edges[7]
notemarket research quota sampling —causes→ prevalence — a bias with a measured direction, and the qualifier is load-bearing: cross-sectional quota studies overestimated, longitudinal ones did not
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concept_edges[7]
weightmarket research quota sampling —causes→ prevalence — 0.85
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concept_edges[7]
auditpopulation shocks —causes→ major depressive disorder — Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but the span says these disorders are historically more SENSITIVE to population shocks; causes is loose.
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concept_edges[8]
effect directionpopulation shocks —causes→ major depressive disorder — increases
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concept_edges[8]
weightpopulation shocks —causes→ major depressive disorder — 0.85
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concept_edges[8]
outcomecontrol — held
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Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[0]
outcomecontrol — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[1]
outcomecontrol — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[2]
outcomecontrol — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[3]
outcomecontrol — partial
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[4]
outcomecontrol — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[5]
outcomecontrol — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[6]
outcomecontrol — partial
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[7]
outcomecontrol — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[8]
outcomecontrol — held
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
controls[9]
no type for thisdaily excess mortality rate → daily SARS-CoV-2 infection rate — COLLINEAR AT r=0.8, WHICH IS WHY ONE OF THEM IS NOT IN THE MODEL. Excess mortality showed no independent association with the prevalence change once the other two indicators were controlled for, and the paper attributes that to collinearity rather than to absence of effect. None of the eight types says 'correlates with', and none of them can say 'dropped from the model because it duplicates another variable' - which is the actual relation and the reason the coefficient is missing
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
unhoused_relations[0]
no type for thispre-pandemic baseline → prevalence — A CRITERION THAT DECIDES WHAT COUNTS AS EVIDENCE. Requiring a comparable pre-pandemic measurement took 5,683 sources to 48 - it is the single most consequential step in the analysis and it is not a relation between two concepts in any of the eight senses. 'part-of' is false, 'causes' is false, and 'operationalised-as' inverts it: the baseline is not how prevalence is measured, it is what makes a measurement admissible
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unhoused_relations[1]
limitationthe two indicators are unlikely to have captured the full impact of the pandemic, and infection rates are not consistently measured or reported everywhere
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limitations[0]
limitationmobile-phone mobility tracking is inaccurate where phone use is low, and people who cannot reduce their mobility because of their job may have their mobility drop overestimated - a bias with a direction, stated
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limitations[1]
limitationVERY FEW QUALIFYING SURVEYS FROM LOW- AND MIDDLE-INCOME COUNTRIES, and large increases were nonetheless estimated for Latin America and the Caribbean, north Africa and the Middle East, and south Asia - super-regions from which NO study met the inclusion criteria at all
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limitations[2]
limitationso the paper asks readers not to extrapolate rankings between countries, and its own leave-one-country-out cross-validation showed the rankings move with data availability
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limitations[3]
limitationmost surveys used symptom scales estimating PROBABLE cases; the assumption that screening thresholds kept their predictive validity through the pandemic could bias the estimates, and a high anxiety score in 2020 might be a natural reaction to a real threat
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limitations[4]
limitationonly three diagnostic surveys existed to test that assumption against; two showed increases and the third used very small samples and changed from face-to-face to telephone administration at the pandemic's onset
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limitations[5]
limitationthe severity distribution had to be assumed unchanged - existing cases may have worsened and new cases may be milder, and the burden estimate cannot tell
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limitations[6]
limitationstudies were excluded for convenience sampling, non-standard case definitions, and instruments with no comparable pre-pandemic estimate
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limitations[7]
limitationother disorders may also have been affected - eating disorders are named - and were not estimated because the data have not been assessed
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limitations[8]
limitationwhether the increased prevalence came with increased suicide is left open: a 21-country time-series found no significant rise, and the authors say they have insufficient data to conclude either way
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limitations[9]
limitationDALYs here are entirely years lived with disability - despite potential excess deaths, neither disorder is counted as an underlying cause of death, which is an ICD convention and not a finding about lethality
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limitations[10]
limitationthe geographical spread of the evidence: 22 studies from western Europe, 14 from high-income North America, 5 Australasia, 5 high-income Asia Pacific, 2 east Asia, 1 central Europe
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limitations[11]
Content tags
content-observations: finding · quantity · variable · definition · key-term — grounded in the full text
findingan additional 53.2 million cases of major depressive disorder globally in 2020, an increase of 27.6%
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content_tags.findings[0]
findingan additional 76.2 million cases of anxiety disorders, an increase of 25.6%
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content_tags.findings[1]
finding49.4 million DALYs from major depressive disorder and 44.5 million from anxiety disorders in 2020
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content_tags.findings[2]
findingfemales were affected more than males and younger age groups more than older ones
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content_tags.findings[3]
findingthe locations hit hardest by the pandemic had the greatest increases
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content_tags.findings[4]
finding48 of 5,683 identified sources met the inclusion criteria - 46 for depression, 27 for anxiety
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content_tags.findings[5]
findingAND THE INCREASE WAS ESTIMATED FOR SUPER-REGIONS WITH NO QUALIFYING SURVEY AT ALL - Latin America and the Caribbean, north Africa and the Middle East, south Asia
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content_tags.findings[6]
findingno reduction in global prevalence or burden of either disorder had been detected since 1990, before the pandemic began
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content_tags.findings[7]
variablechange in prevalence
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content_tags.variables[0]
variablebias covariates
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content_tags.variables[1]
definitioneligible studies
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content_tags.definitions[0]
definitionCOVID-19 impact indicator
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content_tags.definitions[1]
definitionpopulation shocks
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content_tags.definitions[2]
definitioncase definitions
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content_tags.definitions[3]
Concepts
terms this paper carries, each with the sentence it was cut from — the layer that joins one paper to another. Terms with no quote yet are on CONCEPTS.html.
conceptmajor depressive disorder
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concepts[0]
conceptanxiety disorders
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concepts[1]
conceptprevalence
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concepts[2]
conceptpre-pandemic baseline
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concepts[3]
concepthuman mobility
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concepts[4]
conceptdaily SARS-CoV-2 infection rate
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concepts[5]
conceptdaily excess mortality rate
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concepts[6]
conceptCOVID-19 pandemic
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concepts[7]
conceptrisk factors
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concepts[8]
conceptproxies
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concepts[9]
conceptDisMod-MR 2.1
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
concepts[10]
conceptDALYs
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concepts[11]
conceptYLDs
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concepts[12]
conceptmarket research quota sampling
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concepts[13]
conceptpopulation shocks
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concepts[14]
conceptscreening measures
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concepts[15]
Statistics — cross-field join keys
field-invariant statistical terms, used in their statistical sense (gated on a number / symbol / test). A p-value or a standard deviation means the SAME thing in physics, biology, psychology and sociology — so these are the strongest cross-field join keys. Grounded verbatim.
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content_tags.statistics[0]
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content_tags.statistics[1]
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.statistics[2]
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.statistics[3]
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.statistics[4]
Quotation withheld — this paper is not ours to reproduce, and the page has already quoted as much of it as the rights layer allows. The tag, its field and its confidence stand; the sentence is at the publisher.
content_tags.statistics[5]
Second readings
a facet read a second time, independently, from its own sentence — and whether the two readings agree
claim typeexistence — a second reading reaching the same value; recorded: existence
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alternatives.claim_type
methodsystematic-review-and-meta-regression — a second reading DIFFERING from the recorded value; recorded: meta-analysis
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alternatives.method
phenomenonthe global prevalence and burden of major depressive and anxiety disorders in 2020 attributable to the COVID-19 pandemic — a second reading DIFFERING from the recorded value; recorded: a population shock raising the prevalence of common mental disorders - the same pattern seen after the 2008 and 2009 fin
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alternatives.phenomenon

When we have changed our mind. Some entries in the table begin with a word in capitals and the reason for it. EVIDENCE CORRECTED — the finding still stands, but we had quoted the wrong sentence from the paper, and the quotation has been replaced with the right one. RETRACTED — the entry itself was wrong; it stays on the page, marked, with the reason, rather than being deleted. WITHDRAWN AND REPLACED — the entry was wrong, and a corrected version of it appears in the entries below. Each mark carries its own reason, in brackets, because the reasons differ from one entry to the next. An entry we have WITHDRAWN is removed from this page and kept in the record, with its reason. A line reading Audit and a date is a later re-reading of the entry against its whole sentence: DOUBTFUL means it was kept, and the reason says what is loose about it. Quotation marks inside the tagger's sentence. Where a tag is the tagger's own sentence, a phrase in quotation marks inside it is borrowed from the paper — the tagger's wording around it is not. The paper's own sentence is the evidence quote for that row; on this page it is withheld with the article, and the article is at its publisher. Nothing inside quotation marks anywhere on this page is ours: if it is quoted, it is the paper's. Whose words a concept carries. A concept entry records a term the paper itself uses, so the term, the sense given for it, and its evidence are the paper's own words, quoted where the paper fixes them. This is the opposite of a sense entry in the tag table, which is the tagger's sentence about how the paper uses a term. Where a concept entry could not be grounded in the paper's words, the entry says so on its own row.

Tag layer © the Meta-Tagging Project, CC BY 4.0. The paper text is © its authors/publisher and is linked, not reproduced. Excerpts shown are short quotations for identification and verification. · back to index · concepts · authors · עברית
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