Evidence map›Paper›PMID 33707546›Full record

ArticleScientific reports2021

Determining the level of social distancing necessary to avoid future COVID-19 epidemic waves: a modelling study for North East London.

Nathan Cheetham, William Waites, Irene Ebyarimpa, Werner Leber, Katie Brennan, Jasmina Panovska-Griffiths

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 24% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
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  3. Review
  4. Reformulating the susceptible-infectious-removed model in terms of the number of detected cases: well-posedness of the observational model.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022
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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

6 authors at 3 institutions in 2 countries.

Nathan Cheetham *Financial Strategy Team, NHS North East London Commissioning Alliance, London, UK.
William WaitesSchool of Informatics, University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-7759-6805
Irene EbyarimpaFinancial Strategy Team, NHS North East London Commissioning Alliance, London, UK.
Werner LeberCentre for Clinical Effectiveness and Health Data Science, Institute of Population Health Sciences, Barts School of Medicine and Dentistry, Queen Mary University of London, London, UK.ORCID 0000-0003-1321-2566
Katie BrennanFinancial Strategy Team, NHS North East London Commissioning Alliance, London, UK.
Jasmina Panovska-Griffiths *Department of Applied Health Care, Institute of Epidemiology & Health Care, University College London, London, UK. j.panovska-griffiths@ucl.ac.uk.ORCID 0000-0002-7720-1121
Griffith University · AUQueen Mary University of London · GBUniversity of Edinburgh · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Determining the level of social distancing, quantified here as the reduction in daily number of social contacts per person, i.e. the daily contact rate, needed to maintain control of the COVID-19 epidemic and not exceed acute bed capacity in case of future epidemic waves, is important for future planning of relaxing of strict social distancing measures. This work uses mathematical modelling to simulate the levels of COVID-19 in North East London (NEL) and inform the level of social distancing necessary to protect the public and the healthcare demand from future COVID-19 waves. We used a Susceptible-Exposed-Infected-Removed (SEIR) model describing the transmission of SARS-CoV-2 in NEL, calibrated to data on hospitalised patients with confirmed COVID-19, hospital discharges and in-hospital deaths in NEL during the first epidemic wave. To account for the uncertainty in both the infectiousness period and the proportion of symptomatic infection, we simulated nine scenarios for different combinations of infectiousness period (1, 3 and 5 days) and proportion of symptomatic infection (70%, 50% and 25% of all infections). Across all scenarios, the calibrated model was used to assess the risk of occurrence and predict the strength and timing of a second COVID-19 wave under varying levels of daily contact rate from July 04, 2020. Specifically, the daily contact rate required to suppress the epidemic and prevent a resurgence of COVID-19 cases, and the daily contact rate required to stay within the acute bed capacity of the NEL system without any additional intervention measures after July 2020, were determined across the nine different scenarios. Our results caution against a full relaxing of the lockdown later in 2020, predicting that a return to pre-COVID-19 levels of social contact from July 04, 2020, would induce a second wave up to eight times the original wave. With different levels of ongoing social distancing, future resurgence can be avoided, or the strength of the resurgence can be mitigated. Keeping the daily contact rate lower than 5 or 6, depending on scenarios, can prevent an increase in the number of COVID-19 cases, could keep the effective reproduction number R

Indexed as

Models, TheoreticalPhysical DistancingCOVID-19Hospital Bed CapacityHumansLondon

Identifiers

PMID33707546
PMCPMC7952900
OpenAlexW3133929331

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.