Data Management in EpiGraph COVID-19 Epidemic Simulator

Miguel Guzmán-Merino; Christian Durán; Maria Cristina Marinescu; Concepción Delgado-Sanz; Diana Gomez-Barroso; Jesus Carretero; David E. Singh

doi:10.1007/978-3-031-06156-1_22

Data Management in EpiGraph COVID-19 Epidemic Simulator

Miguel Guzmán-Merino
, Christian Durán
, Maria Cristina Marinescu
, Concepción Delgado-Sanz
, Diana Gomez-Barroso
, Jesus Carretero
, David E. Singh^*

^*Autor corresponent d’aquest treball

Producció científica: Capítol de llibre › Contribució a congrés/conferència › Avaluat per experts

Resum

The transmission of COVID-19 through a population depends on many factors which model, incorporate, and integrate many heterogeneous data sources. The work we describe in this paper focuses on the data management aspect of EpiGraph, a scalable agent-based virus-propagation simulator. We describe the data acquisition and pre-processing tasks that are necessary to map the data to the different models implemented in EpiGraph in a way that is efficient and comprehensible. We also report on post-processing, analysis, and visualization of the outputs, tasks that are fundamental to make the simulation results useful for the final users. Our simulator captures complex interactions between social processes, virus characteristics, travel patterns, climate, vaccination, and non-pharmaceutical interventions. We end by demonstrating the entire pipeline with one evaluation for Spain for the third COVID wave starting on December 27th of 2020.

Idioma original	Anglès
Títol de la publicació	Euro-Par 2021
Subtítol de la publicació	Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers
Editors	Ricardo Chaves, Dora B. Heras, Aleksandar Ilic, Didem Unat, Rosa M. Badia, Andrea Bracciali, Patrick Diehl, Anshu Dubey, Oh Sangyoon, Stephen L. Scott, Laura Ricci
Editor	Springer Science and Business Media Deutschland GmbH
Pàgines	267-278
Nombre de pàgines	12
ISBN (imprès)	9783031061554
DOIs	https://doi.org/10.1007/978-3-031-06156-1_22
Estat de la publicació	Publicada - 2022
Publicat externament	Sí
Esdeveniment	27th International Conference on Parallel and Distributed Computing, Euro-Par 2021 - Virtual, Online Durada: 30 d’ag. 2021 → 31 d’ag. 2021

Sèrie de publicacions

Nom	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volum	13098 LNCS
ISSN (imprès)	0302-9743
ISSN (electrònic)	1611-3349

Conferència

Conferència	27th International Conference on Parallel and Distributed Computing, Euro-Par 2021
Ciutat	Virtual, Online
Període	30/08/21 → 31/08/21

SDG de les Nacions Unides

Aquest resultat contribueix als següents objectius de desenvolupament sostenible.

ODS 3 Salut i benestar

Accés al document

10.1007/978-3-031-06156-1_22

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Com citar-ho

Guzmán-Merino, M., Durán, C., Marinescu, M. C., Delgado-Sanz, C., Gomez-Barroso, D., Carretero, J., & Singh, D. E. (2022). Data Management in EpiGraph COVID-19 Epidemic Simulator. In R. Chaves, D. B. Heras, A. Ilic, D. Unat, R. M. Badia, A. Bracciali, P. Diehl, A. Dubey, O. Sangyoon, S. L. Scott, & L. Ricci (Ed.), Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers (pàg. 267-278). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13098 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-06156-1_22

Guzmán-Merino, Miguel ; Durán, Christian ; Marinescu, Maria Cristina et al. / Data Management in EpiGraph COVID-19 Epidemic Simulator. Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. editor / Ricardo Chaves ; Dora B. Heras ; Aleksandar Ilic ; Didem Unat ; Rosa M. Badia ; Andrea Bracciali ; Patrick Diehl ; Anshu Dubey ; Oh Sangyoon ; Stephen L. Scott ; Laura Ricci. Springer Science and Business Media Deutschland GmbH, 2022. pàg. 267-278 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{29cd46e35f05498c8db1b3609f987269,

title = "Data Management in EpiGraph COVID-19 Epidemic Simulator",

abstract = "The transmission of COVID-19 through a population depends on many factors which model, incorporate, and integrate many heterogeneous data sources. The work we describe in this paper focuses on the data management aspect of EpiGraph, a scalable agent-based virus-propagation simulator. We describe the data acquisition and pre-processing tasks that are necessary to map the data to the different models implemented in EpiGraph in a way that is efficient and comprehensible. We also report on post-processing, analysis, and visualization of the outputs, tasks that are fundamental to make the simulation results useful for the final users. Our simulator captures complex interactions between social processes, virus characteristics, travel patterns, climate, vaccination, and non-pharmaceutical interventions. We end by demonstrating the entire pipeline with one evaluation for Spain for the third COVID wave starting on December 27th of 2020.",

keywords = "COVID-19, Epidemiological simulation, Heterogeneous data processing, Parallel tool",

author = "Miguel Guzm{\'a}n-Merino and Christian Dur{\'a}n and Marinescu, \{Maria Cristina\} and Concepci{\'o}n Delgado-Sanz and Diana Gomez-Barroso and Jesus Carretero and Singh, \{David E.\}",

note = "Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.; 27th International Conference on Parallel and Distributed Computing, Euro-Par 2021 ; Conference date: 30-08-2021 Through 31-08-2021",

year = "2022",

doi = "10.1007/978-3-031-06156-1\_22",

language = "English",

isbn = "9783031061554",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "267--278",

editor = "Ricardo Chaves and \{B. Heras\}, Dora and Aleksandar Ilic and Didem Unat and Badia, \{Rosa M.\} and Andrea Bracciali and Patrick Diehl and Anshu Dubey and Oh Sangyoon and \{L. Scott\}, Stephen and Laura Ricci",

booktitle = "Euro-Par 2021",

address = "Germany",

}

Guzmán-Merino, M, Durán, C, Marinescu, MC, Delgado-Sanz, C, Gomez-Barroso, D, Carretero, J & Singh, DE 2022, Data Management in EpiGraph COVID-19 Epidemic Simulator. in R Chaves, D B. Heras, A Ilic, D Unat, RM Badia, A Bracciali, P Diehl, A Dubey, O Sangyoon, S L. Scott & L Ricci (ed.), Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13098 LNCS, Springer Science and Business Media Deutschland GmbH, pàg. 267-278, 27th International Conference on Parallel and Distributed Computing, Euro-Par 2021, Virtual, Online, 30/08/21. https://doi.org/10.1007/978-3-031-06156-1_22

Data Management in EpiGraph COVID-19 Epidemic Simulator. / Guzmán-Merino, Miguel; Durán, Christian; Marinescu, Maria Cristina et al.
Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. ed. / Ricardo Chaves; Dora B. Heras; Aleksandar Ilic; Didem Unat; Rosa M. Badia; Andrea Bracciali; Patrick Diehl; Anshu Dubey; Oh Sangyoon; Stephen L. Scott; Laura Ricci. Springer Science and Business Media Deutschland GmbH, 2022. pàg. 267-278 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13098 LNCS).

Producció científica: Capítol de llibre › Contribució a congrés/conferència › Avaluat per experts

TY - GEN

T1 - Data Management in EpiGraph COVID-19 Epidemic Simulator

AU - Guzmán-Merino, Miguel

AU - Durán, Christian

AU - Marinescu, Maria Cristina

AU - Delgado-Sanz, Concepción

AU - Gomez-Barroso, Diana

AU - Carretero, Jesus

AU - Singh, David E.

PY - 2022

Y1 - 2022

N2 - The transmission of COVID-19 through a population depends on many factors which model, incorporate, and integrate many heterogeneous data sources. The work we describe in this paper focuses on the data management aspect of EpiGraph, a scalable agent-based virus-propagation simulator. We describe the data acquisition and pre-processing tasks that are necessary to map the data to the different models implemented in EpiGraph in a way that is efficient and comprehensible. We also report on post-processing, analysis, and visualization of the outputs, tasks that are fundamental to make the simulation results useful for the final users. Our simulator captures complex interactions between social processes, virus characteristics, travel patterns, climate, vaccination, and non-pharmaceutical interventions. We end by demonstrating the entire pipeline with one evaluation for Spain for the third COVID wave starting on December 27th of 2020.

AB - The transmission of COVID-19 through a population depends on many factors which model, incorporate, and integrate many heterogeneous data sources. The work we describe in this paper focuses on the data management aspect of EpiGraph, a scalable agent-based virus-propagation simulator. We describe the data acquisition and pre-processing tasks that are necessary to map the data to the different models implemented in EpiGraph in a way that is efficient and comprehensible. We also report on post-processing, analysis, and visualization of the outputs, tasks that are fundamental to make the simulation results useful for the final users. Our simulator captures complex interactions between social processes, virus characteristics, travel patterns, climate, vaccination, and non-pharmaceutical interventions. We end by demonstrating the entire pipeline with one evaluation for Spain for the third COVID wave starting on December 27th of 2020.

KW - COVID-19

KW - Epidemiological simulation

KW - Heterogeneous data processing

KW - Parallel tool

UR - https://www.scopus.com/pages/publications/85133029620

UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=pure_univeritat_ramon_llull&SrcAuth=WosAPI&KeyUT=WOS:000851509300022&DestLinkType=FullRecord&DestApp=WOS_CPL

U2 - 10.1007/978-3-031-06156-1_22

DO - 10.1007/978-3-031-06156-1_22

M3 - Conference contribution

AN - SCOPUS:85133029620

SN - 9783031061554

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 267

EP - 278

BT - Euro-Par 2021

A2 - Chaves, Ricardo

A2 - B. Heras, Dora

A2 - Ilic, Aleksandar

A2 - Unat, Didem

A2 - Badia, Rosa M.

A2 - Bracciali, Andrea

A2 - Diehl, Patrick

A2 - Dubey, Anshu

A2 - Sangyoon, Oh

A2 - L. Scott, Stephen

A2 - Ricci, Laura

PB - Springer Science and Business Media Deutschland GmbH

T2 - 27th International Conference on Parallel and Distributed Computing, Euro-Par 2021

Y2 - 30 August 2021 through 31 August 2021

ER -

Guzmán-Merino M, Durán C, Marinescu MC, Delgado-Sanz C, Gomez-Barroso D, Carretero J et al. Data Management in EpiGraph COVID-19 Epidemic Simulator. In Chaves R, B. Heras D, Ilic A, Unat D, Badia RM, Bracciali A, Diehl P, Dubey A, Sangyoon O, L. Scott S, Ricci L, editors, Euro-Par 2021: Parallel Processing Workshops - Euro-Par 2021 International Workshops, 2021, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2022. pàg. 267-278. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-06156-1_22

Data Management in EpiGraph COVID-19 Epidemic Simulator

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