Evidence map›Paper›PMID 35215795›Full record

ArticleViruses2022

Using an Administrative and Clinical Database to Determine the Early Spread of COVID-19 at the US Department of Veterans Affairs during the Beginning of the 2019-2020 Flu Season: A Retrospective Longitudinal Study.

Lilia R Lukowsky, Claudia Der-Martirosian, William Neil Steers, Kiran S Kamble, Aram Dobalian

Abstract read
In one paragraph

Article in Viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023
    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

5 authors.

Lilia R LukowskyVeteran Emergency Management Evaluation Center (VEMEC), US Department of Veterans Affairs, North Hills, CA 91343, USA.
Claudia Der-MartirosianVeteran Emergency Management Evaluation Center (VEMEC), US Department of Veterans Affairs, North Hills, CA 91343, USA.
William Neil SteersVeteran Emergency Management Evaluation Center (VEMEC), US Department of Veterans Affairs, North Hills, CA 91343, USA.
Kiran S KambleSchool of Public Health, University of Memphis, Memphis, TN 38152, USA.
Aram DobalianVeteran Emergency Management Evaluation Center (VEMEC), US Department of Veterans Affairs, North Hills, CA 91343, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrevious studies examining the early spread of COVID-19 have used influenza-like illnesses (ILIs) to determine the early spread of COVID-19. We used COVID-19 case definition to identify COVID-like symptoms (CLS) independently of other influenza-like illnesses (ILIs).

methodsUsing data from Emergency Department (ED) visits at VA Medical Centers in CA, TX, and FL, we compared weekly rates of CLS, ILIs, and non-influenza ILIs encounters during five consecutive flu seasons (2015-2020) and estimated the risk of developing each illness during the first 23 weeks of the 2019-2020 season compared to previous seasons.

resultsPatients with CLS were significantly more likely to visit the ED during the first 23 weeks of the 2019-2020 compared to prior seasons, while ED visits for influenza and non-influenza ILIs did not differ substantially. Adjusted CLS risk was significantly lower for all seasons relative to the 2019-2020 season: RR15-16 = 0.72, 0.75, 0.72; RR16-17 = 0.81, 0.77, 0.79; RR17-18 = 0.80, 0.89, 0.83; RR18-19 = 0.82, 0.96, 0.81, in CA, TX, and FL, respectively.

conclusionsThe observed increase in ED visits for CLS indicates the likely spread of COVID-19 in the US earlier than previously reported. VA data could potentially help identify emerging infectious diseases and supplement existing syndromic surveillance systems.

Indexed as

Sentinel SurveillanceCOVID-19Databases, FactualDisease OutbreaksEmergency Service, HospitalHumansInfluenza, HumanLongitudinal StudiesRetrospective StudiesUnited StatesVeteransCOVID-19 symptomsinfluenza-like illnessesVeterans

Identifiers

PMID35215795
PMCPMC8879908

What OpenQuestion holds

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LicenceCC BY
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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.