Evidence map›Paper›PMID 34514500›Full record

ArticleThe Journal of infectious diseases2022

The Impact of Cocirculating Pathogens on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/Coronavirus Disease 2019 Surveillance: How Concurrent Epidemics May Introduce Bias and Decrease the Observed SARS-CoV-2 Percentage Positivity.

Aleksandra Kovacevic, Rosalind M Eggo, Marc Baguelin, Matthieu Domenech de Cellès, Lulla Opatowski

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 40% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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  4. Review
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

5 authors at 5 institutions in 3 countries.

Aleksandra KovacevicEpidemiology and Modelling of Antibiotic Evasion, Institut Pasteur, Paris, France.
Rosalind M EggoCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Marc BaguelinCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Matthieu Domenech de CellèsMax Planck Institute for Infection Biology, Infectious Disease Epidemiology Group, Berlin, Germany.
Lulla OpatowskiEpidemiology and Modelling of Antibiotic Evasion, Institut Pasteur, Paris, France.
London Centre for Neglected Tropical Disease Research · GBLondon School of Hygiene & Tropical Medicine · GBMax Planck Institute for Infection Biology · DEUniversité de Versailles Saint-Quentin-en-Yvelines · FRUniversité Paris-Saclay · FR

Funding

European UnionFrench government's Investissement d'AvenirHDR UK Innovation MR/S003975/1Institut PasteurLaboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases ANR-10-LABX-62 IBEIDMedical Research Council MC_PC 19065Medical Research Council MC_PC_19065Medical Research Council MR/S003975/1MRC Centre for Global Infectious Disease Analysis MR/R015600/1MRC/FCDO ConcordatNational Institute for Health and Medical ResearchUK Foreign, Commonwealth & Development Office (FCDO)University of Paris-SaclayUniversity of Versailles-Saint-Quentin-en-Yvelines
6 · The paper itself

Abstract

backgroundCirculation of seasonal non-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) respiratory viruses with syndromic overlap during the coronavirus disease 2019 (COVID-19) pandemic may alter the quality of COVID-19 surveillance, with possible consequences for real-time analysis and delay in implementation of control measures.

methodsUsing a multipathogen susceptible-exposed-infectious-recovered (SEIR) transmission model formalizing cocirculation of SARS-CoV-2 and another respiratory virus, we assessed how an outbreak of secondary virus may affect 2 COVID-19 surveillance indicators: testing demand and positivity. Using simulation, we assessed to what extent the use of multiplex polymerase chain reaction tests on a subsample of symptomatic individuals can help correct the observed SARS-CoV-2 percentage positivity and improve surveillance quality.

resultsWe find that a non-SARS-CoV-2 epidemic strongly increases SARS-CoV-2 daily testing demand and artificially reduces the observed SARS-CoV-2 percentage positivity for the duration of the outbreak. We estimate that performing 1 multiplex test for every 1000 COVID-19 tests on symptomatic individuals could be sufficient to maintain surveillance of other respiratory viruses in the population and correct the observed SARS-CoV-2 percentage positivity.

conclusionsThis study showed that cocirculating respiratory viruses can distort SARS-CoV-2 surveillance. Correction of the positivity rate can be achieved by using multiplex polymerase chain reaction tests, and a low number of samples is sufficient to avoid bias in SARS-CoV-2 surveillance.

Indexed as

CoinfectionCOVID-19SARS-CoV-2Disease OutbreaksHumansModels, TheoreticalMultiplex Polymerase Chain ReactionPandemicsPolymerase Chain ReactionRespiratory SystemRespiratory Tract InfectionsSentinel Surveillancecocirculating respiratory virusesCOVID-19 surveillancemathematical modelingmultiplex testingSARS-CoV-2

Identifiers

PMID34514500
PMCPMC8763960
OpenAlexW3201181422

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.