Evidence map›Paper›PMID 35791373›Full record

ArticleThe Lancet regional health. Europe2022

Intrinsic generation time of the SARS-CoV-2 Omicron variant: An observational study of household transmission.

Mattia Manica, Alfredo De Bellis, Giorgio Guzzetta, Pamela Mancuso, Massimo Vicentini, Francesco Venturelli, Alessandro Zerbini, Eufemia Bisaccia, Maria Litvinova, Francesco Menegale and 13 more

Abstract read
In one paragraph

Article in The Lancet regional health. Europe, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 3 pooled it
–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

41 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Pooled it
  4. Why Andes hantavirus is not the next SARS-CoV-2: contrasting viral shedding, transmissibility and genomic patterns.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026
    Article
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  7. China's post-zero-COVID Omicron wave: A Bayesian analysis.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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

23 authors.

Mattia ManicaCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Alfredo De BellisCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Giorgio GuzzettaCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Pamela MancusoEpidemiology Unit, Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Reggio Emilia, Italy.
Massimo VicentiniEpidemiology Unit, Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Reggio Emilia, Italy.
Francesco VenturelliPublic Health Department, Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Reggio Emilia, Italy.
Alessandro ZerbiniUnit of Clinical Immunology, Allergy and Advanced Biotechnologies, Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Italy.
Eufemia BisacciaPublic Health Department, Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Reggio Emilia, Italy.
Maria LitvinovaLaboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
Francesco MenegaleCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Carla Molina GranéCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Piero PolettiCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Valentina MarzianoCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Agnese ZardiniCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Valeria d'AndreaCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Filippo TrentiniCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Antonino BellaDipartimento di Malattie Infettive, Istituto Superiore di Sanità, Rome, Italy.
Flavia RiccardoDipartimento di Malattie Infettive, Istituto Superiore di Sanità, Rome, Italy.
Patrizio PezzottiDipartimento di Malattie Infettive, Istituto Superiore di Sanità, Rome, Italy.
Marco AjelliLaboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA.
Paolo Giorgi RossiEpidemiology Unit, Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Reggio Emilia, Italy.
Stefano MerlerCenter for Health Emergencies, Fondazione Bruno Kessler, Trento, Italy.
Reggio Emilia COVID-19 Working Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Starting from the final months of 2021, the SARS-CoV-2 Omicron variant expanded globally, swiftly replacing Delta, the variant that was dominant at the time. Many uncertainties remain about the epidemiology of Omicron; here, we aim to estimate its generation time. Methods: We used a Bayesian approach to analyze 23,122 SARS-CoV-2 infected individuals clustered in 8903 households as determined from contact tracing operations in Reggio Emilia, Italy, throughout January 2022. We estimated the distribution of the intrinsic generation time (the time between the infection dates of an infector and its secondary cases in a fully susceptible population), realized household generation time, realized serial interval (time between symptom onset of an infector and its secondary cases), and contribution of pre-symptomatic transmission. Findings: We estimated a mean intrinsic generation time of 6.84 days (95% credible intervals, CrI, 5.72-8.60), and a mean realized household generation time of 3.59 days (95%CrI: 3.55-3.60). The household serial interval was 2.38 days (95%CrI 2.30-2.47) with about 51% (95%CrI 45-56%) of infections caused by symptomatic individuals being generated before symptom onset. Interpretation: These results indicate that the intrinsic generation time of the SARS-CoV-2 Omicron variant might not have shortened as compared to previous estimates on ancestral lineages, Alpha and Delta, in the same geographic setting. Like for previous lineages, pre-symptomatic transmission appears to play a key role for Omicron transmission. Estimates in this study may be useful to design quarantine, isolation and contact tracing protocols and to support surveillance (e.g., for the accurate computation of reproduction numbers). Funding: The study was partially funded by EU grant 874850 MOOD.

Indexed as

Bayesian inferenceContact tracingCOVID-19Generation timeOmicronSARS-CoV-2

Identifiers

PMID35791373
PMCPMC9246701

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.