Evidence map›Paper›PMID 37290944›Full record

ArticleBMJ open2023

Trends and symptoms of SARS-CoV-2 infection: a longitudinal study on an Alpine population representative sample.

Giulia Barbieri, Massimo Pizzato, Martin Gögele, Daniele Giardiello, Christian X Weichenberger, Luisa Foco, Daniele Bottigliengo, Cinzia Bertelli, Laura Barin, Rebecca Lundin and 3 more

Abstract read
In one paragraph

Article in BMJ open, 2023. 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
–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

1 citing paper in PubMed.

  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

13 authors.

Giulia BarbieriInstitute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy giulia.barbieri@eurac.edu cristian.pattaro@eurac.edu.ORCID 0000-0002-3531-0725
Massimo PizzatoDepartment of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy.ORCID 0000-0002-9491-1483
Martin GögeleInstitute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy.ORCID 0000-0003-4785-4348
Daniele GiardielloInstitute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy.ORCID 0000-0002-9005-9430
Christian X WeichenbergerInstitute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy.ORCID 0000-0002-2176-0274
Luisa FocoInstitute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy.ORCID 0000-0002-6694-3322
Daniele BottigliengoInstitute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy.ORCID 0000-0002-8802-3834
Cinzia BertelliDepartment of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy.ORCID 0000-0002-9443-1957
Laura BarinInstitute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy.ORCID 0000-0001-8139-4686
Rebecca LundinInstitute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy.ORCID 0000-0002-8380-4834
Peter P Pramstaller *Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy.ORCID 0000-0002-9831-8302
Cristian Pattaro *Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy giulia.barbieri@eurac.edu cristian.pattaro@eurac.edu.ORCID 0000-0002-4119-0109
Roberto Melotti *Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano, Italy.ORCID 0000-0003-4115-317X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe continuous monitoring of SARS-CoV-2 infection waves and the emergence of novel pathogens pose a challenge for effective public health surveillance strategies based on diagnostics. Longitudinal population representative studies on incident events and symptoms of SARS-CoV-2 infection are scarce. We aimed at describing the evolution of the COVID-19 pandemic during 2020 and 2021 through regular monitoring of self-reported symptoms in an Alpine community sample.

designTo this purpose, we designed a longitudinal population representative study, the Cooperative Health Research in South Tyrol COVID-19 study. PARTICIPANTS AND OUTCOME MEASURES: A sample of 845 participants was retrospectively investigated for active and past infections with swab and blood tests, by August 2020, allowing adjusted cumulative incidence estimation. Of them, 700 participants without previous infection or vaccination were followed up monthly until July 2021 for first-time infection and symptom self-reporting: COVID-19 anamnesis, social contacts, lifestyle and sociodemographic data were assessed remotely through digital questionnaires. Temporal symptom trajectories and infection rates were modelled through longitudinal clustering and dynamic correlation analysis. Negative binomial regression and random forest analysis assessed the relative importance of symptoms.

resultsAt baseline, the cumulative incidence of SARS-CoV-2 infection was 1.10% (95% CI 0.51%, 2.10%). Symptom trajectories mimicked both self-reported and confirmed cases of incident infections. Cluster analysis identified two groups of high-frequency and low-frequency symptoms. Symptoms like fever and loss of smell fell in the low-frequency cluster. Symptoms most discriminative of test positivity (loss of smell, fatigue and joint-muscle aches) confirmed prior evidence.

conclusionsRegular symptom tracking from population representative samples is an effective screening tool auxiliary to laboratory diagnostics for novel pathogens at critical times, as manifested in this study of COVID-19 patterns. Integrated surveillance systems might benefit from more direct involvement of citizens' active symptom tracking.

Indexed as

AnosmiaCOVID-19HumansLongitudinal StudiesPandemicsRetrospective StudiesSARS-CoV-2COVID-19epidemiologyhealth policySARS-CoV-2

Identifiers

PMID37290944
PMCPMC10254957

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.