Evidence map›Paper›PMID 41862854›Full record

ArticleBMC public health2026

Simulating COVID-19 lockdowns' impact on depressive symptoms in the northern Netherlands.

Kristina Thompson, Jiri Kaan, Ji Qi, Astrid Anh Pham, Eva Viviani

Abstract read
In one paragraph

Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Kristina ThompsonHealth & Society, Wageningen University & Research, Hollandseweg 1, Wageningen, 6706 KN, The Netherlands. kristina.thompson@wur.nl.
Jiri KaanHealth & Society, Wageningen University & Research, Hollandseweg 1, Wageningen, 6706 KN, The Netherlands.
Ji QiNetherlands eScience Center, Science Park 402, Amsterdam, 1098 XH, The Netherlands.
Astrid Anh PhamHealth & Society, Wageningen University & Research, Hollandseweg 1, Wageningen, 6706 KN, The Netherlands.
Eva VivianiNetherlands eScience Center, Science Park 402, Amsterdam, 1098 XH, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring the COVID-19 (SARS-CoV-2) pandemic, a major challenge for policymakers was finding the balance between containing outbreaks and supporting mental health. Although lockdowns slowed COVID-19 transmission, it appears that they also increased the prevalence of depressive symptoms. It is not yet clear whether different, hypothetical lockdown scenarios would have differently impacted the prevalence of depressive symptoms.

methodsTo that end, we developed an open-source microsimulation model, COMMA (COvid Mental health Model with Agents). With COMMA, we explored how lock down scenarios, individual characteristics, and behaviors during lockdowns related to the prevalence of depressive symptoms during the COVID-19 period. The characteristics of the population were synthesized from Lifelines, a prospective cohort study set in the northern Netherlands.

resultsCOMMA simulations estimated that the actual lockdown scenario between June 2020 and June 2021 would result in 10.92% (95% CI: 10.68%-11.18%) of the population experiencing depressive symptoms, up from 3.49% (95% CI: 3.49–3.49) at baseline. Had there been a full or partial lockdown for the entirety of this period, 11.44% (95% CI: 11.18%-11.69%), or 10.63% (95% CI: 10.38%-10.87%), of the population, respectively, would have experienced depressive symptoms.

conclusionsLockdown severity was an important predictor of the prevalence of depressive symptoms, with higher rates in full lockdowns than partial lockdowns. However, across all simulations, only a minority of the population ever developed depressive symptoms. These findings suggest that lockdowns, particularly full lockdowns, are not without consequences for mental health.

Indexed as

COVID-19DepressionPandemicsQuarantineAdultComputer SimulationFemaleHumansMaleNetherlandsPrevalenceProspective StudiesCOVID-19Depressive symptomsLockdownsMental healthMicrosimulation

Identifiers

PMID41862854
PMCPMC13126702

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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.