Evidence map›Paper›PMID 35595824›Full record

ArticleScientific reports2022

Transmission dynamics of SARS-CoV-2 in a strictly-Orthodox Jewish community in the UK.

William Waites, Carl A B Pearson, Katherine M Gaskell, Thomas House, Lorenzo Pellis, Marina Johnson, Victoria Gould, Adam Hunt, Neil R H Stone, Ben Kasstan and 7 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 53% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
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

17 authors at 5 institutions in 2 countries.

William WaitesCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK. william.waites@strath.ac.uk.
Carl A B PearsonCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
Katherine M GaskellDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
Thomas HouseSchool of Mathematics, University of Manchester, Manchester, UK.
Lorenzo PellisSchool of Mathematics, University of Manchester, Manchester, UK.
Marina JohnsonGreat Ormond Street Institute of Child Health Biomedical Research Centre, University College London, London, UK.
Victoria GouldDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
Adam HuntGreat Ormond Street Institute of Child Health Biomedical Research Centre, University College London, London, UK.
Neil R H StoneDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
Ben KasstanCentre for Health, Law and Society, University of Bristol Law School, Bristol, UK.
Tracey ChantlerDepartment of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
Sham LalDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
Chrissy H RobertsDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
David GoldblattGreat Ormond Street Institute of Child Health Biomedical Research Centre, University College London, London, UK.
CMMID COVID-19 Working Group
Michael MarksDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
Rosalind M EggoCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK.
London School of Hygiene & Tropical Medicine · GBUniversity of London · GBUniversity College London · GBUniversity of Manchester · GBHebrew University of Jerusalem · IL

Funding

Department of Health MR/V027956/1Medical Research Council MR/R015600/1Medical Research Council MR/S003975/1Medical Research Council MR/V027956/1Medical Research Council MR/V038613/1Wellcome Trust 208812/Z/17/Z
6 · The paper itself

Abstract

Some social settings such as households and workplaces, have been identified as high risk for SARS-CoV-2 transmission. Identifying and quantifying the importance of these settings is critical for designing interventions. A tightly-knit religious community in the UK experienced a very large COVID-19 epidemic in 2020, reaching 64.3% seroprevalence within 10 months, and we surveyed this community both for serological status and individual-level attendance at particular settings. Using these data, and a network model of people and places represented as a stochastic graph rewriting system, we estimated the relative contribution of transmission in households, schools and religious institutions to the epidemic, and the relative risk of infection in each of these settings. All congregate settings were important for transmission, with some such as primary schools and places of worship having a higher share of transmission than others. We found that the model needed a higher general-community transmission rate for women (3.3-fold), and lower susceptibility to infection in children to recreate the observed serological data. The precise share of transmission in each place was related to assumptions about the internal structure of those places. Identification of key settings of transmission can allow public health interventions to be targeted at these locations.

Indexed as

COVID-19SARS-CoV-2ChildFemaleHumansJewsSeroepidemiologic StudiesUnited Kingdom

Identifiers

PMID35595824
PMCPMC9121858
OpenAlexW4281262084

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.