Evidence map›Paper›PMID 33506154›Full record

ArticleInfectious Disease Modelling2021

Statistical data driven approach of COVID-19 in Ecuador:

Raúl Patricio Fernández-Naranjo, Eduardo Vásconez-González, Katherine Simbaña-Rivera, Lenin Gómez-Barreno, Juan S Izquierdo-Condoy, Doménica Cevallos-Robalino, Esteban Ortiz-Prado

Abstract read
In one paragraph

Article in Infectious Disease Modelling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

7 authors.

Raúl Patricio Fernández-NaranjoOne Health Research Group, Faculty of Medicine, Universidad de las Americas, Quito, Ecuador.
Eduardo Vásconez-GonzálezOne Health Research Group, Faculty of Medicine, Universidad de las Americas, Quito, Ecuador.
Katherine Simbaña-RiveraOne Health Research Group, Faculty of Medicine, Universidad de las Americas, Quito, Ecuador.
Lenin Gómez-BarrenoOne Health Research Group, Faculty of Medicine, Universidad de las Americas, Quito, Ecuador.
Juan S Izquierdo-CondoyOne Health Research Group, Faculty of Medicine, Universidad de las Americas, Quito, Ecuador.
Doménica Cevallos-RobalinoResident of Intensive Care Unit, Hospital Quito Sur IESS, Quito, Ecuador.
Esteban Ortiz-PradoOne Health Research Group, Faculty of Medicine, Universidad de las Americas, Quito, Ecuador.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growth of COVID-19 pandemic throughout more than 213 countries around the world have put a lot of pressures on governments and health services to try to stop the rapid expansion of the pandemic. During 2009, H1N1 Influenza pandemic, statistical and mathematical methods were used to track how the virus spreads around countries. Most of these models that were developed at the beginning of the XXI century are based on the classical susceptible-infected-recovered (SIR) model developed almost a hundred years ago. The evolution of this model allows us to forecast and compute basic and effective reproduction numbers (

Indexed as

Basic reproduction factorBayesian inferenceCOVID-19EcuadorR0Real time reproduction factor

Identifiers

PMID33506154
PMCPMC7811040

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.