Evidence map›Paper›PMID 29623242›Full record

ArticlePLoS currents2018

The Impact of a Case of Ebola Virus Disease on Emergency Department Visits in Metropolitan Dallas-Fort Worth, TX, July, 2013-July, 2015: An Interrupted Time Series Analysis.

Noelle-Angelique M Molinari, Tanya Telfair LeBlanc, William Stephens

Abstract read
In one paragraph

Article in PLoS currents, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Coronavirus Disease (COVID-19): A primer for emergency physicians.The American journal of emergency medicine · 2021
    Review
  2. Review
  3. 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

3 authors.

Noelle-Angelique M MolinariOffice of Public Health Preparedness and Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Tanya Telfair LeBlancApplied Science and Evaluation Branch, Office of Public Health Preparedness and Response, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
William StephensOffice of Public Health Informatics, Tarrant County Public Health, Tarrant County, Texas, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe first Ebola virus disease (EVD) case in the United States (US) was confirmed September 30, 2014 in a man 45 years old. This event created considerable media attention and there was fear of an EVD outbreak in the US.

methodsThis study examined whether emergency department (ED) visits changed in metropolitan Dallas-Fort Worth--, Texas (DFW) after this EVD case was confirmed. Using Texas Health Services Region 2/3 syndromic surveillance data and focusing on DFW, interrupted time series analyses were conducted using segmented regression models with autoregressive errors for overall ED visits and rates of several chief complaints, including fever with gastrointestinal distress (FGI). Date of fatal case confirmation was the "event."

resultsResults indicated the event was highly significant for ED visits overall (P<0.05) and for the rate of FGI visits (P<0.0001). An immediate increase in total ED visits of 1,023 visits per day (95% CI: 797.0, 1,252.8) was observed, equivalent to 11.8% (95% CI: 9.2%, 14.4%) increase ED visits overall. Visits and the rate of FGI visits in DFW increased significantly immediately after confirmation of the EVD case and remained elevated for several months even adjusting for seasonality both within symptom specific chief complaints as well as overall.

conclusionsThese results have implications for ED surge capacity as well as for public health messaging in the wake of a public health emergency.

Indexed as

Ebola Virus Diseaseemergency department visitsstatistical model

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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.