Evidence map›Paper›PMID 33956838›Full record

ArticlePloS one2021

Modeling the evolution of COVID-19 via compartmental and particle-based approaches: Application to the Cyprus case.

Constantia Alexandrou, Vangelis Harmandaris, Anastasios Irakleous, Giannis Koutsou, Nikos Savva

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Constantia AlexandrouDepartment of Physics, University of Cyprus, Nicosia, Cyprus.ORCID 0000-0001-9136-3621
Vangelis HarmandarisComputation-based Science and Technology Research Center, The Cyprus Institute, Nicosia, Cyprus.ORCID 0000-0002-9613-7639
Anastasios IrakleousDepartment of Physics, University of Cyprus, Nicosia, Cyprus.
Giannis KoutsouComputation-based Science and Technology Research Center, The Cyprus Institute, Nicosia, Cyprus.ORCID 0000-0002-6199-0242
Nikos SavvaComputation-based Science and Technology Research Center, The Cyprus Institute, Nicosia, Cyprus.ORCID 0000-0003-1549-3154

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present two different approaches for modeling the spread of the COVID-19 pandemic. Both approaches are based on the population classes susceptible, exposed, infectious, quarantined, and recovered and allow for an arbitrary number of subgroups with different infection rates and different levels of testing. The first model is derived from a set of ordinary differential equations that incorporates the rates at which population transitions take place among classes. The other is a particle model, which is a specific case of crowd simulation model, in which the disease is transmitted through particle collisions and infection rates are varied by adjusting the particle velocities. The parameters of these two models are tuned using information on COVID-19 from the literature and country-specific data, including the effect of restrictions as they were imposed and lifted. We demonstrate the applicability of both models using data from Cyprus, for which we find that both models yield very similar results, giving confidence in the predictions.

Indexed as

AlgorithmsComputer SimulationCOVID-19CyprusEpidemiological MonitoringHumansModels, StatisticalQuarantineSARS-CoV-2

Identifiers

PMID33956838
PMCPMC8101925

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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.