Evidence map›Paper›PMID 35627487›Full record

ArticleInternational journal of environmental research and public health2022

Emergency Medical Services Calls Analysis for Trend Prediction during Epidemic Outbreaks: Interrupted Time Series Analysis on 2020-2021 COVID-19 Epidemic in Lazio, Italy.

Antonio Vinci, Amina Pasquarella, Maria Paola Corradi, Pelagia Chatzichristou, Gianluca D'Agostino, Stefania Iannazzo, Nicoletta Trani, Maria Annunziata Parafati, Leonardo Palombi, Domenico Antonio Ientile

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Observational
  6. Article
  7. Article
  8. Increases in Ambulance Call Volume Are an Early Warning Sign of Major COVID-19 Surges in Children.International journal of environmental research and public health · 2022
    Article
  9. 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

10 authors.

Antonio VinciLocal Health Authority "Roma 1", 00193 Rome, Italy.ORCID 0000-0002-4915-7733
Amina PasquarellaAzienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy.
Maria Paola CorradiAzienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy.
Pelagia ChatzichristouAzienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy.
Gianluca D'AgostinoAzienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy.
Stefania IannazzoAzienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy.
Nicoletta TraniAzienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy.
Maria Annunziata ParafatiAzienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy.
Leonardo PalombiDepartment of Biomedicine and Prevention, University of Rome "Tor Vergata", 00166 Rome, Italy.ORCID 0000-0003-1806-5278
Domenico Antonio IentileAzienda Regionale Emergenza Sanitaria ARES 118, 00149 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

(1) Background: During the COVID-19 outbreak in the Lazio region, a surge in emergency medical service (EMS) calls has been observed. The objective of present study is to investigate if there is any correlation between the variation in numbers of daily EMS calls, and the short-term evolution of the epidemic wave. (2) Methods: Data from the COVID-19 outbreak has been retrieved in order to draw the epidemic curve in the Lazio region. Data from EMS calls has been used in order to determine Excess of Calls (ExCa) in the 2020−2021 years, compared to the year 2019 (baseline). Multiple linear regression models have been run between ExCa and the first-order derivative (D’) of the epidemic wave in time, each regression model anticipating the epidemic progression (up to 14 days), in order to probe a correlation between the variables. (3) Results: EMS calls variation from baseline is correlated with the slope of the curve of ICU admissions, with the most fitting value found at 7 days (R2 0.33, p < 0.001). (4) Conclusions: EMS calls deviation from baseline allows public health services to predict short-term epidemic trends in COVID-19 outbreaks, and can be used as validation of current data, or as an independent estimator of future trends.

Indexed as

COVID-19Emergency Medical ServicesEpidemicsDisease OutbreaksHumansInterrupted Time Series AnalysisCOVID-19emergency medical servicesprediction modelspublic healthtime series analysis

Identifiers

PMID35627487
PMCPMC9140838

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.