Evidence map›Paper›PMID 36888684›Full record

ReviewPLoS pathogens2023

The interactions of SARS-CoV-2 with cocirculating pathogens: Epidemiological implications and current knowledge gaps.

Anabelle Wong, Laura Andrea Barrero Guevara, Elizabeth Goult, Michael Briga, Sarah C Kramer, Aleksandra Kovacevic, Lulla Opatowski, Matthieu Domenech de Cellès

Open access · goldAbstract readReview
In one paragraph

Review in PLoS pathogens, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
6.9field-weighted citation impact, top 2% 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

17 citing papers in PubMed, 34 citations in OpenAlex.

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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

8 authors at 2 institutions in 2 countries.

Anabelle WongInfectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany.
Laura Andrea Barrero GuevaraInfectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany.
Elizabeth GoultInfectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany.
Michael BrigaInfectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany.
Sarah C KramerInfectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany.
Aleksandra KovacevicEpidemiology and Modelling of Antibiotic Evasion, Institut Pasteur, Université Paris Cité, Paris, France.
Lulla OpatowskiEpidemiology and Modelling of Antibiotic Evasion, Institut Pasteur, Université Paris Cité, Paris, France.
Matthieu Domenech de CellèsInfectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany.ORCID 0000-0002-9302-4858
Max Planck Institute for Infection Biology · DEInserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the availability of effective vaccines, the persistence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suggests that cocirculation with other pathogens and resulting multiepidemics (of, for example, COVID-19 and influenza) may become increasingly frequent. To better forecast and control the risk of such multiepidemics, it is essential to elucidate the potential interactions of SARS-CoV-2 with other pathogens; these interactions, however, remain poorly defined. Here, we aimed to review the current body of evidence about SARS-CoV-2 interactions. Our review is structured in four parts. To study pathogen interactions in a systematic and comprehensive way, we first developed a general framework to capture their major components: sign (either negative for antagonistic interactions or positive for synergistic interactions), strength (i.e., magnitude of the interaction), symmetry (describing whether the interaction depends on the order of infection of interacting pathogens), duration (describing whether the interaction is short-lived or long-lived), and mechanism (e.g., whether interaction modifies susceptibility to infection, transmissibility of infection, or severity of disease). Second, we reviewed the experimental evidence from animal models about SARS-CoV-2 interactions. Of the 14 studies identified, 11 focused on the outcomes of coinfection with nonattenuated influenza A viruses (IAVs), and 3 with other pathogens. The 11 studies on IAV used different designs and animal models (ferrets, hamsters, and mice) but generally demonstrated that coinfection increased disease severity compared with either monoinfection. By contrast, the effect of coinfection on the viral load of either virus was variable and inconsistent across studies. Third, we reviewed the epidemiological evidence about SARS-CoV-2 interactions in human populations. Although numerous studies were identified, only a few were specifically designed to infer interaction, and many were prone to multiple biases, including confounding. Nevertheless, their results suggested that influenza and pneumococcal conjugate vaccinations were associated with a reduced risk of SARS-CoV-2 infection. Finally, fourth, we formulated simple transmission models of SARS-CoV-2 cocirculation with an epidemic viral pathogen or an endemic bacterial pathogen, showing how they can naturally incorporate the proposed framework. More generally, we argue that such models, when designed with an integrative and multidisciplinary perspective, will be invaluable tools to resolve the substantial uncertainties that remain about SARS-CoV-2 interactions.

Indexed as

CoinfectionCOVID-19Influenza, HumanAnimalsFerretsHumansMiceSARS-CoV-2

Identifiers

PMID36888684
PMCPMC9994710
OpenAlexW4323535357

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.