Evidence map›Paper›PMID 41330013›Full record

ArticleEpidemics2025

The impact of household physical distancing and its timing on the transmission of SARS-CoV-2: Insights from a household transmission evaluation study.

Pietro Coletti, Niel Hens, Christel Faes, Huong Q McLean, Edward A Belongia, Melissa Rolfes, Alexandra Mellis, Carrie Reed, Jessica Biddle, Ahra Kim and 3 more

Abstract read
In one paragraph

Article in Epidemics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Pietro ColettiInstitute of Health and Society, Université catholique de Louvain, Brussels, Belgium; Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium. Electronic address: pietro.coletti@uclouvain.be.
Niel HensData Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium; Centre for Health Economic Research and Modelling Infectious Diseases, Vaxinfectio, University of Antwerp, Antwerp, Belgium.
Christel FaesData Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.
Huong Q McLeanMarshfield Clinic Research Institute, Marshfield, WI, USA.
Edward A BelongiaMarshfield Clinic Research Institute, Marshfield, WI, USA.
Melissa RolfesInfluenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia.
Alexandra MellisInfluenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia.
Carrie ReedInfluenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia.
Jessica BiddleInfluenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia.
Ahra KimVanderbilt University Medical Center, Nashville, TN, USA.
Yuwei ZhuVanderbilt University Medical Center, Nashville, TN, USA.
H Keipp TalbotVanderbilt University Medical Center, Nashville, TN, USA.
Carlos G GrijalvaVanderbilt University Medical Center, Nashville, TN, USA.

Funding

Mentoring in transmission of influenza and strategies for preventionK24AI148459 · NIAID · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GRIJALVA, CARLOS G · 2020 to 2024
$893k
NIAID NIH HHS K24 AI148459
6 · The paper itself

Abstract

backgroundStudies on SARS-CoV-2 household transmission often assume random mixing, overlooking detailed contact patterns and the timing of physical distancing.

methodsTo address this, we examined interactions within 280 households, including 280 index cases and 544 members, enrolled from April 2020 to April 2021 in Nashville, Tennessee, and central Wisconsin. Eligible households were enrolled within 7 days of index case symptom onset if at least one member was initially asymptomatic. Participants were monitored for 14 days, with symptoms and respiratory specimens collected daily, and contact data retrospectively assessed at three time points: the day before index case symptom onset, the day before enrollment, and 14 days post-enrollment. We fitted Exponential Random Graph Models to the contact pattern to identify drivers of household contact. We used the fitted household models to inform a two-level mixing model to account for community infection risk, and we calibrated it to the infection data. We then used the calibrated model to study different implementation of physical distancing.

resultsContact patterns showed a significant reduction in physical interactions after infection awareness, particularly avoidance of index cases, with a 77% reduction in contact density (95% CI [65%-84%], p<0.001). Simulations from the two-level mixing model indicated that initiating contact reductions at symptom onset could lower secondary infections by over 25% in households of 4-5 members.

conclusionsThese results demonstrate how behavior changes following infection awareness reduce transmission. Implementing physical distancing earlier, at symptom onset, could further limit secondary infections and enhance household transmission control.

Indexed as

COVID-19Family CharacteristicsPhysical DistancingAdolescentAdultAgedChildContact TracingFemaleHumansMaleMiddle AgedRetrospective StudiesSARS-CoV-2TennesseeTime FactorsCOVID-19Exponential random graph modelsHousehold transmissionPhysical distancingSocial contactTwo-level mixing models

Identifiers

PMID41330013
PMCPMC13023158

What OpenQuestion holds

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LicenceCC BY-NC
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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.