Evidence map›Paper›PMID 34006340›Full record

ArticleEpidemiology and infection2021

Risk factors associated with the incidence of self-reported COVID-19-like illness: data from a web-based syndromic surveillance system in the Netherlands.

Scott A McDonald, Cees C van den Wijngaard, Cornelia C H Wielders, Ingrid H M Friesema, Loes Soetens, Daniela Paolotti, Susan van den Hof, Albert Jan van Hoek

Abstract read
In one paragraph

Article in Epidemiology and infection, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Designing Digital COVID-19 Screening: Insights and Deliberations.International journal of environmental research and public health · 2023
    Article
  11. Article
  12. 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

8 authors.

Scott A McDonaldCentre for Infectious Disease Control, Netherlands National Institute for Public Health and the Environment, Bilthoven, the Netherlands.ORCID 0000-0003-0788-6011
Cees C van den WijngaardCentre for Infectious Disease Control, Netherlands National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Cornelia C H WieldersCentre for Infectious Disease Control, Netherlands National Institute for Public Health and the Environment, Bilthoven, the Netherlands.ORCID 0000-0002-2413-9088
Ingrid H M FriesemaCentre for Infectious Disease Control, Netherlands National Institute for Public Health and the Environment, Bilthoven, the Netherlands.ORCID 0000-0001-9943-0518
Loes SoetensCentre for Infectious Disease Control, Netherlands National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Daniela PaolottiInstitute for Scientific Interchange Foundation, Torino, Italy.
Susan van den HofCentre for Infectious Disease Control, Netherlands National Institute for Public Health and the Environment, Bilthoven, the Netherlands.
Albert Jan van HoekCentre for Infectious Disease Control, Netherlands National Institute for Public Health and the Environment, Bilthoven, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the first wave of the severe acute respiratory syndrome-coronavirus-2 epidemic in the Netherlands, notifications consisted mostly of patients with relatively severe disease. To enable real-time monitoring of the incidence of mild coronavirus disease 2019 (COVID-19) - for which medical consultation might not be required - the Infectieradar web-based syndromic surveillance system was launched in mid-March 2020. Our aim was to quantify associations between Infectieradar participant characteristics and the incidence of self-reported COVID-19-like illness. Recruitment for this cohort study was via a web announcement. After registering, participants completed weekly questionnaires, reporting the occurrence of a set of symptoms. The incidence rate of COVID-19-like illness was estimated and multivariable Poisson regression used to estimate the relative risks associated with sociodemographic variables, lifestyle factors and pre-existing medical conditions. Between 17 March and 24 May 2020, 25 663 active participants were identified, who reported 7060 episodes of COVID-19-like illness over 131 404 person-weeks of follow-up. The incidence rate declined over the analysis period, consistent with the decline in notified cases. Male sex, age 65+ years and higher education were associated with a significantly lower COVID-19-like illness incidence rate (adjusted rate ratios (RRs) of 0.80 (95% CI 0.76-0.84), 0.77 (0.70-0.85), 0.84 (0.80-0.88), respectively) and the baseline characteristics ever-smoker, asthma, allergies, diabetes, chronic lung disease, cardiovascular disease and children in the household were associated with a higher incidence (RRs of 1.11 (1.04-1.19) to 1.69 (1.50-1.90)). Web-based syndromic surveillance has proven useful for monitoring the temporal trends in, and risk factors associated with, the incidence of mild disease. Increased relative risks observed for several patient factors could reflect a combination of exposure risk, susceptibility to infection and propensity to report symptoms.

Indexed as

SARS-CoV-2Self ReportSentinel SurveillanceAdolescentAdultAgedAged, 80 and overCOVID-19FemaleHumansIncidenceInternetMaleMiddle AgedNetherlandsRisk FactorsCOVID-19Netherlandsrisk factorssyndromic surveillance

Identifiers

PMID34006340
PMCPMC8160488

What OpenQuestion holds

Textmetadata
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.