Evidence map›Paper›PMID 34053253›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2021

Using a household-structured branching process to analyse contact tracing in the SARS-CoV-2 pandemic.

Martyn Fyles, Elizabeth Fearon, Christopher Overton, University of Manchester COVID-19 Modelling Group, Tom Wingfield, Graham F Medley, Ian Hall, Lorenzo Pellis, Thomas House

Open access · hybridAbstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 pooled it
3.2field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 3 syntheses or guidelines pooled it, 42 citations in OpenAlex.

  1. Pooled it
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  9. Parameter estimation for contact tracing in graph-based models.Journal of the Royal Society, Interface · 2023
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  14. Visualization for epidemiological modelling: challenges, solutions, reflections and recommendations.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022
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  17. Modelling that shaped the early COVID-19 pandemic response in the UK.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
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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

9 authors at 4 institutions in 2 countries.

Martyn FylesDepartment of Mathematics, University of Manchester, Manchester M13 9PY, UK.
Elizabeth FearonCentre for the Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.
Christopher OvertonDepartment of Mathematics, University of Manchester, Manchester M13 9PY, UK.
University of Manchester COVID-19 Modelling Group
Tom WingfieldDepartment of Clinical Sciences and International Public Health, Liverpool School of Tropical Medicine, Liverpool L3 5QA, UK.
Graham F MedleyCentre for the Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.
Ian HallDepartment of Mathematics, University of Manchester, Manchester M13 9PY, UK.
Lorenzo PellisDepartment of Mathematics, University of Manchester, Manchester M13 9PY, UK.
Thomas HouseDepartment of Mathematics, University of Manchester, Manchester M13 9PY, UK.
Turing Institute · GBUniversity of London · GBUniversity of Liverpool · GBUniversity of Manchester · GB

Funding

Medical Research Council MR/S020462/1Medical Research Council MR/V004832/1Medical Research Council MR/V028618/1Medical Research Council MR/V038613/1Wellcome Trust 202562/Z/16/ZWellcome Trust 209075/Z/17/ZWellcome Trust MR/V004832/1
6 · The paper itself

Abstract

We explore strategies of contact tracing, case isolation and quarantine of exposed contacts to control the SARS-CoV-2 epidemic using a branching process model with household structure. This structure reflects higher transmission risks among household members than among non-household members. We explore strategic implementation choices that make use of household structure, and investigate strategies including two-step tracing, backwards tracing, smartphone tracing and tracing upon symptom report rather than test results. The primary model outcome is the effect of contact tracing, in combination with different levels of physical distancing, on the growth rate of the epidemic. Furthermore, we investigate epidemic extinction times to indicate the time period over which interventions must be sustained. We consider effects of non-uptake of isolation/quarantine, non-adherence, and declining recall of contacts over time. Our results find that, compared to self-isolation of cases without contact tracing, a contact tracing strategy designed to take advantage of household structure allows for some relaxation of physical distancing measures but cannot completely control the epidemic absent of other measures. Even assuming no imported cases and sustainment of moderate physical distancing, testing and tracing efforts, the time to bring the epidemic to extinction could be in the order of months to years. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'.

Indexed as

Models, TheoreticalPandemicsContact TracingCOVID-19Family CharacteristicsHumansQuarantineSARS-CoV-2contact tracingCOVID-19epidemicepidemiologyinfectious diseaseSARS-CoV-2

Identifiers

PMID34053253
PMCPMC8165594
OpenAlexW3126707232

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.