Evidence map›Paper›PMID 33402754›Full record

ArticleColombia medica (Cali, Colombia)2020

COVID-19: Adaptation of a model to predicting healthcare resources needs in Valle del Cauca, Colombia.

Nicolas Iragorri, Carlos Gómez-Restrepo, Kali Barrett, Socrates Herrera, Isabel Hurtado, Yasin Khan, Stephen Mac, David Naimark, Petros Pechlivanoglou, Diego Rosselli and 5 more

Abstract read
In one paragraph

Article in Colombia medica (Cali, Colombia), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

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

  1. Pooled it
  2. Review
  3. Nefrologia : publicacion oficial de la Sociedad Espanola Nefrologia · 2022
    Article
  4. Article
  5. Article
  6. 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

15 authors.

Nicolas IragorriInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.ORCID 0000-0002-8300-5784
Carlos Gómez-RestrepoFacultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia.ORCID 0000-0002-9013-5384
Kali BarrettInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.ORCID 0000-0001-7147-2222
Socrates HerreraComité Público Privado de Expertos en Salud COPESA, Cali, Colombia.
Isabel HurtadoSecretaría Departamental de Salud, Cali, Colombia.
Yasin KhanInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.ORCID 0000-0002-0426-1780
Stephen MacInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.ORCID 0000-0003-4736-1770
David NaimarkInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.ORCID 0000-0002-0621-0637
Petros PechlivanoglouInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.ORCID 0000-0001-5090-7936
Diego RosselliFacultad de Medicina, Pontificia Universidad Javeriana, Bogotá, Colombia.ORCID 0000-0003-0960-9480
Dilian ToroComité Público Privado de Expertos en Salud COPESA, Cali, Colombia.ORCID 0000-0003-2128-9133
Pedro VillamizarFacultad de Medicina, Pontificia Universidad Javeriana, Cali, Colombia.ORCID 0000-0003-4753-0159
Raphael XimenesToronto Health Economics and Technology Assessment (THETA) collaborative, University Health Network, Toronto, Canada.ORCID 0000-0003-2536-951X
Helmer ZapataCentro de Investigación Científica Caucaseco, Cali, Colombia.ORCID 0000-0003-0883-6825
Beate SanderInstitute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundValle del Cauca is the region with the fourth-highest number of COVID-19 cases in Colombia (>50,000 on September 7, 2020). Due to the lack of anti-COVID-19 therapies, decision-makers require timely and accurate data to estimate the incidence of disease and the availability of hospital resources to contain the pandemic.

methodsWe adapted an existing model to the local context to forecast COVID-19 incidence and hospital resource use assuming different scenarios: (1) the implementation of quarantine from September 1

resultsWe estimated 67,700 cases by October 15

conclusionSlowly lifting social distancing restrictions and reopening the economy is not expected to result in full resource depletion by October if the daily growth rate is maintained below 8%. Increasing the number of available beds provides a safeguard against slightly higher infection rates. Predictive models can be iteratively used to obtain nuanced predictions to aid decision-making.

Indexed as

Models, StatisticalColombiaCOVID-19Delivery of Health CareHealth ResourcesHospital Bed CapacityHumansIntensive Care UnitsColombiaCOVID-19Global healthhealthcare resourcesresource constraintsSARS-CoV-2Valle del Cauca

Identifiers

PMID33402754
PMCPMC7744107

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.