Evidence map›Paper›PMID 37166513›Full record

ArticleBulletin of mathematical biology2023

The Role of Mobility in the Dynamics of the COVID-19 Epidemic in Andalusia.

Z Rapti, J Cuevas-Maraver, E Kontou, S Liu, Y Drossinos, P G Kevrekidis, M Barmann, Q-Y Chen, G A Kevrekidis

Open access · bronzeAbstract read
In one paragraph

Article in Bulletin of mathematical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

2 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. On modelling airborne infection risk.Royal Society open science · 2024
    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

9 authors at 5 institutions in 3 countries.

Z RaptiDepartment of Mathematics and Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Champaign, IL, USA. zrapti@illinois.edu.ORCID http://orcid.org/0000-0003-3988-0888
J Cuevas-MaraverGrupo de Física No Lineal, Departamento de Física Aplicada I, Universidad de Sevilla, Escuela Politécnica Superior, C/ Virgen de Africa, 7, 41011, Seville, Spain.
E KontouDepartment of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Champaign, IL, USA.
S LiuDepartment of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Champaign, IL, USA.
Y DrossinosThermal Hydraulics and Multiphase Flow Laboratory, Institute of Nuclear and Radiological Sciences and Technology, Energy and Safety, N.C.S.R. "Demokritos", 15341, Agia Paraskevi, Greece.
P G KevrekidisDepartment of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA, 01003-4515, USA.
M BarmannDepartment of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA, 01003-4515, USA.
Q-Y ChenDepartment of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, MA, 01003-4515, USA.
G A KevrekidisDepartment of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, 21218, USA.
University of Illinois Urbana-Champaign · USUniversity of Massachusetts Amherst · USInstituto de Recursos Naturales y Agrobiología de Sevilla · ESJohns Hopkins University · USNational Centre of Scientific Research "Demokritos" · GR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metapopulation models have been a popular tool for the study of epidemic spread over a network of highly populated nodes (cities, provinces, countries) and have been extensively used in the context of the ongoing COVID-19 pandemic. In the present work, we revisit such a model, bearing a particular case example in mind, namely that of the region of Andalusia in Spain during the period of the summer-fall of 2020 (i.e., between the first and second pandemic waves). Our aim is to consider the possibility of incorporation of mobility across the province nodes focusing on mobile-phone time-dependent data, but also discussing the comparison for our case example with a gravity model, as well as with the dynamics in the absence of mobility. Our main finding is that mobility is key toward a quantitative understanding of the emergence of the second wave of the pandemic and that the most accurate way to capture it involves dynamic (rather than static) inclusion of time-dependent mobility matrices based on cell-phone data. Alternatives bearing no mobility are unable to capture the trends revealed by the data in the context of the metapopulation model considered herein.

Indexed as

COVID-19HumansMathematical ConceptsModels, BiologicalPandemicsTimeCOVID-19 epidemicGravity lawHuman mobilityMetapopulation

Identifiers

PMID37166513
PMCPMC10173246
OpenAlexW4376131948

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.