Evidence map›Paper›PMID 33612922›Full record

ReviewPhysics reports2021

Non-pharmaceutical interventions during the COVID-19 pandemic: A review.

Nicola Perra

Open access · greenAbstract readReview
In one paragraph

Review in Physics reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 241 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
241citing papers in PubMed, 6 pooled it
118.9field-weighted citation impact, top 1% of its field
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

241 citing papers in PubMed, 6 syntheses or guidelines pooled it, 509 citations in OpenAlex.

  1. Pooled it
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  7. Article
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  9. Dissociative symptoms during the SARS-CoV-2 pandemic situation in mental health patients.Borderline personality disorder and emotion dysregulation · 2026
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  12. Partnership Quality and Mental Health Among Older Adults in England Amid the COVID-19 Pandemic.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2026
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  14. Observational
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181 more citing papers are in PubMed but not listed here.

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

1 author at 1 institution in 1 country.

Nicola PerraNetworks and Urban Systems Centre, University of Greenwich, London, UK.
University of Greenwich · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Infectious diseases and human behavior are intertwined. On one side, our movements and interactions are the engines of transmission. On the other, the unfolding of viruses might induce changes to our daily activities. While intuitive, our understanding of such feedback loop is still limited. Before COVID-19 the literature on the subject was mainly theoretical and largely missed validation. The main issue was the lack of empirical data capturing behavioral change induced by diseases. Things have dramatically changed in 2020. Non-pharmaceutical interventions (NPIs) have been the key weapon against the SARS-CoV-2 virus and affected virtually any societal process. Travel bans, events cancellation, social distancing, curfews, and lockdowns have become unfortunately very familiar. The scale of the emergency, the ease of survey as well as crowdsourcing deployment guaranteed by the latest technology, several Data for Good programs developed by tech giants, major mobile phone providers, and other companies have allowed unprecedented access to data describing behavioral changes induced by the pandemic. Here, I review some of the vast literature written on the subject of NPIs during the COVID-19 pandemic. In doing so, I analyze 348 articles written by more than 2518 authors in the first 12 months of the emergency. While the large majority of the sample was obtained by querying PubMed, it includes also a hand-curated list. Considering the focus, and methodology I have classified the sample into seven main categories: epidemic models, surveys, comments/perspectives, papers aiming to quantify the effects of NPIs, reviews, articles using data proxies to measure NPIs, and publicly available datasets describing NPIs. I summarize the methodology, data used, findings of the articles in each category and provide an outlook highlighting future challenges as well as opportunities.

Indexed as

Behavioral changesCOVID-19Non-pharmaceutical interventionsSARS-CoV-2

Identifiers

PMID33612922
PMCPMC7881715
OpenAlexW3116362583

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.