Evidence map›Paper›PMID 36718198›Full record

ArticleAdvanced theory and simulations2023

Exploring a COVID-19 Endemic Scenario: High-Resolution Agent-Based Modeling of Multiple Variants.

Agnieszka Truszkowska, Lorenzo Zino, Sachit Butail, Emanuele Caroppo, Zhong-Ping Jiang, Alessandro Rizzo, Maurizio Porfiri

Open access · bronzeAbstract read
In one paragraph

Article in Advanced theory and simulations, 2023. 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
0.8field-weighted citation impact, top 31% of its field
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, 6 citations in OpenAlex.

  1. Observational
  2. Article
  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

7 authors at 6 institutions in 4 countries.

Agnieszka TruszkowskaCenter for Urban Science and Progress Tandon School of Engineering New York University 370 Jay Street Brooklyn NY 11201 USA.
Lorenzo ZinoEngineering and Technology Institute Groningen University of Groningen Nijenborgh 4 Groningen AG 9747 The Netherlands.
Sachit ButailDepartment of Mechanical Engineering Northern Illinois University DeKalb IL 60115 USA.
Emanuele CaroppoDepartment of Mental Health Local Health Unit ROMA 2 Rome 00159 Italy.
Zhong-Ping JiangDepartment of Electrical and Computer Engineering Tandon School of Engineering New York University 370 Jay Street Brooklyn NY 11201 USA.
Alessandro RizzoDepartment of Electronics and Telecommunications Politecnico di Torino Corso Duca degli Abruzzi 24 Turin 10129 Italy.
Maurizio PorfiriCenter for Urban Science and Progress Tandon School of Engineering New York University 370 Jay Street Brooklyn NY 11201 USA.ORCID https://orcid.org/0000-0002-1480-3539
City University of New York · USNew York University · USNorthern Illinois University · USPolitecnico di Torino · ITUniversità Cattolica del Sacro Cuore · ITUniversity of Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our efforts as a society to combat the ongoing COVID-19 pandemic are continuously challenged by the emergence of new variants. These variants can be more infectious than existing strains and many of them are also more resistant to available vaccines. The appearance of these new variants cause new surges of infections, exacerbated by infrastructural difficulties, such as shortages of medical personnel or test kits. In this work, a high-resolution computational framework for modeling the simultaneous spread of two COVID-19 variants: a widely spread base variant and a new one, is established. The computational framework consists of a detailed database of a representative U.S. town and a high-resolution agent-based model that uses the Omicron variant as the base variant and offers flexibility in the incorporation of new variants. The results suggest that the spread of new variants can be contained with highly efficacious tests and mild loss of vaccine protection. However, the aggressiveness of the ongoing Omicron variant and the current waning vaccine immunity point to an endemic phase of COVID-19, in which multiple variants will coexist and residents continue to suffer from infections.

Indexed as

agent‐based modelCOVID‐19epidemiologymultiple variantsurban science

Identifiers

PMID36718198
PMCPMC9878004
OpenAlexW4308787116

What Socratic 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 Socratic graph.