Evidence map›Paper›PMID 33954262›Full record

ArticleWellcome open research2020

Second waves, social distancing, and the spread of COVID-19 across the USA.

Karl J Friston, Thomas Parr, Peter Zeidman, Adeel Razi, Guillaume Flandin, Jean Daunizeau, Oliver J Hulme, Alexander J Billig, Vladimir Litvak, Catherine J Price and 2 more

Abstract read
In one paragraph

Article in Wellcome open research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Five Fristonian Formulae.Entropy (Basel, Switzerland) · 2025
    Article
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  4. From pixels to planning: scale-free active inference.Frontiers in network physiology · 2025
    Article
  5. Article
  6. Linking fast and slow: The case for generative models.Network neuroscience (Cambridge, Mass.) · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Clinical-epidemiologic variation in patients treated in the first and second wave of COVID-19 in Lambayeque, Peru: A cluster analysis.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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

12 authors.

Karl J FristonThe Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.ORCID https://orcid.org/0000-0001-7984-8909
Thomas ParrThe Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.ORCID https://orcid.org/0000-0001-5108-5743
Peter ZeidmanThe Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.
Adeel RaziThe Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.ORCID https://orcid.org/0000-0002-0779-9439
Guillaume FlandinThe Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.
Jean DaunizeauInstitut du Cerveau et de la Moelle épinière, INSERM UMRS 1127, Paris, France.
Oliver J HulmeDanish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.
Alexander J BilligEar Institute, University College London, London, UK.ORCID https://orcid.org/0000-0002-4531-8616
Vladimir LitvakThe Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.
Catherine J PriceThe Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.
Rosalyn J MoranCentre for Neuroimaging Science, Department of Neuroimaging, IoPPN, King's College London, London, UK.ORCID https://orcid.org/0000-0002-2736-2621
Christian LambertThe Wellcome Centre for Human Neuroimaging, University College London, London, WC1N 3BG, UK.ORCID https://orcid.org/0000-0001-8281-4611

Funding

Medical Research Council MR/M023672/1Medical Research Council MR/R006504/1Wellcome Trust 205103/Z/16/Z
6 · The paper itself

Abstract

We recently described a dynamic causal model of a COVID-19 outbreak within a single region. Here, we combine several instantiations of this (epidemic) model to create a (pandemic) model of viral spread among regions. Our focus is on a second wave of new cases that may result from loss of immunity-and the exchange of people between regions-and how mortality rates can be ameliorated under different strategic responses. In particular, we consider hard or soft social distancing strategies predicated on national (Federal) or regional (State) estimates of the prevalence of infection in the population. The modelling is demonstrated using timeseries of new cases and deaths from the United States to estimate the parameters of a factorial (compartmental) epidemiological model of each State and, crucially, coupling between States. Using Bayesian model reduction, we identify the effective connectivity between States that best explains the initial phases of the outbreak in the United States. Using the ensuing posterior parameter estimates, we then evaluate the likely outcomes of different policies in terms of mortality, working days lost due to lockdown and demands upon critical care. The provisional results of this modelling suggest that social distancing and loss of immunity are the two key factors that underwrite a return to endemic equilibrium.

Indexed as

Bayesiancompartmental modelscoronavirusdynamic causal modellingepidemiologyvariational

Identifiers

PMID33954262
PMCPMC8063524

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.