Evidence map›Paper›PMID 32415751›Full record

ArticleInfluenza and other respiratory viruses2020

Active surveillance documents rates of clinical care seeking due to respiratory illness.

Marta Galanti, Devon Comito, Chanel Ligon, Benjamin Lane, Nelsa Matienzo, Sadiat Ibrahim, Atinuke Shittu, Eudosie Tagne, Ruthie Birger, Minhaz Ud-Dean and 8 more

Open access · goldAbstract read
In one paragraph

Article in Influenza and other respiratory viruses, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

6 citing papers in PubMed, 11 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

18 authors at 3 institutions in 1 country.

Marta GalantiDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.ORCID 0000-0002-9060-1250
Devon ComitoDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Chanel LigonDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Benjamin LaneDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Nelsa MatienzoDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Sadiat IbrahimDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Atinuke ShittuDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Eudosie TagneDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Ruthie BirgerDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Minhaz Ud-DeanDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Ioan FilipDepartment of Systems Biology, Columbia University, New York, NY, USA.
Haruka MoritaDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.ORCID 0000-0001-9400-9521
Raul RabadanDepartment of Systems Biology, Columbia University, New York, NY, USA.
Simon AnthonyDepartment of Epidemiology, Columbia University, New York, NY, USA.
Greg A FreyerDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.
Peter DayanDepartment of Pediatrics, Columbia University, New York, NY, USA.
Bo ShopsinDepartments of Medicine and Microbiology, New York University School of Medicine, New York, NY, USA.
Jeffrey ShamanDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA.ORCID 0000-0002-7216-7809
Columbia University · USEarth Island Institute · USNew York University · US

Funding

Host-pathogen interactions during hospital adaptation of MRSAR01AI137336 · NIAID · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI SHOPSIN, BO, YANAI, ITAI · 2019 to 2022
$3.3M
Undergraduate Research Program to Promote Diversity in EHSR25ES025505 · NIEHS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI NAVAS-ACIEN, ANA · 2015 to 2024
$979k
Defense Advanced Research Projects Agency W911NF-16-2-0035NIAID NIH HHS R01 AI137336NIEHS NIH HHS R25 ES025505
6 · The paper itself

Abstract

backgroundRespiratory viral infections are a leading cause of disease worldwide. However, the overall community prevalence of infections has not been properly assessed, as standard surveillance is typically acquired passively among individuals seeking clinical care.

methodsWe conducted a prospective cohort study in which participants provided daily diaries and weekly nasopharyngeal specimens that were tested for respiratory viruses. These data were used to analyze healthcare seeking behavior, compared with cross-sectional ED data and NYC surveillance reports, and used to evaluate biases of medically attended ILI as signal for population respiratory disease and infection.

resultsThe likelihood of seeking medical attention was virus-dependent: higher for influenza and metapneumovirus (19%-20%), lower for coronavirus and RSV (4%), and 71% of individuals with self-reported ILI did not seek care and half of medically attended symptomatic manifestations did not meet the criteria for ILI. Only 5% of cohort respiratory virus infections and 21% of influenza infections were medically attended and classifiable as ILI. We estimated 1 ILI event per person/year but multiple respiratory infections per year.

conclusionStandard, healthcare-based respiratory surveillance has multiple limitations. Specifically, ILI is an incomplete metric for quantifying respiratory disease, viral respiratory infection, and influenza infection. The prevalence of respiratory viruses, as reported by standard, healthcare-based surveillance, is skewed toward viruses producing more severe symptoms. Active, longitudinal studies are a helpful supplement to standard surveillance, can improve understanding of the overall circulation and burden of respiratory viruses, and can aid development of more robust measures for controlling the spread of these pathogens.

Indexed as

Epidemiological MonitoringAdolescentAdultChildChild, PreschoolCoronavirus InfectionsCross-Sectional StudiesFemaleHospitalizationHumansInfantInfant, NewbornInfluenza, HumanLongitudinal StudiesMaleMiddle AgedILImedically attended respiratory infectionspopulation-based estimate of respiratory infectionsrespiratory illness surveillance

Identifiers

PMID32415751
PMCPMC7276732
OpenAlexW3025055958

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.