Evidence map›Paper›PMID 39559218›Full record

ArticleHeliyon2024

Predictive modelling of the effectiveness of vaccines against COVID-19 in Bogotá: Methodological innovation involving different variants and computational optimisation efficiency.

Oscar Espinosa, Lisa White, Valeria Bejarano, Ricardo Aguas, Duván Rincón, Laura Mora, Antonio Ramos, Cristian Sanabria, Jhonathan Rodríguez, Nicolás Barrera and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Oscar EspinosaEconomic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.
Lisa WhiteDepartment of Biology, University of Oxford, Oxford, United Kingdom.
Valeria BejaranoEconomic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.
Ricardo AguasNuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Duván RincónDirectorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, D.C., Colombia.
Laura MoraDirectorate of Synthesis and Technology Management, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, D.C., Colombia.
Antonio RamosEconomic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.
Cristian SanabriaDirectorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, D.C., Colombia.
Jhonathan RodríguezEconomic Models and Quantitative Methods Research Group, Centro de Investigaciones para el Desarrollo, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.
Nicolás BarreraDirectorate of Analytical, Economic and Actuarial Studies in Health, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, D.C., Colombia.
Carlos Álvarez-MorenoFaculty of Medicine, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.
Jorge CortésFaculty of Medicine, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.
Carlos SaavedraFaculty of Medicine, Universidad Nacional de Colombia, Bogotá, D.C., Colombia.
Adriana RobayoExecutive Directorate, Instituto de Evaluación Tecnológica en Salud (IETS), Bogotá, D.C., Colombia.
Bo GaoNuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
Oscar FrancoUniversity Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The uncertainty associated with the future of viruses such as SARS-CoV-2 poses a challenge to public health officials because of its implications for welfare, economics and population health. In this document, we develop an age-stratified epidemiological-mathematical model to predict various health outcomes, considering the effectiveness of COVID-19 vaccines. The analytical model proposed and developed for this research is based on the approach constructed by the COVID-19 International Modelling Consortium. Following this approach, this paper innovates at the frontier of knowledge by including the various variants of SARS-CoV-2 in the Consortium model. Furthermore, for the first time in international literature, a complete compilation of the formal mathematical development of this entire quantitative model is presented. Our model accurately fits the observed historical data of new infections, cumulative mortality, symptomatic infections, hospitalisations, and Intensive Care Units admissions, capturing the waves of contagion that have occurred in Bogotá, Colombia. In turn, the prognosis obtained indicates a considerable decrease in the incidence and lethality caused by SARS-CoV-2 under current conditions, thus evidencing the effectiveness of vaccines against infection, hospitalisation, and death. This model enables the evaluation of different scenarios in response to changes in the dynamics of this infectious disease, providing information to policymakers for real-world evidence-based decision-making.

Indexed as

COVID-19EffectivenessMathematical epidemiologyPredictive modellingPublic healthReal-world evidenceVaccines

Identifiers

PMID39559218
PMCPMC11570482

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.