Fuente, D.; Hervás-Marín, D.; Rebollo Pedruelo, M.; Conejero, JA.; Oliver, N. (2022). COVID-19 outbreaks analysis in the Valencian Region of Spain in the prelude of the third wave. Frontiers in Public Health. 10:1-14. https://doi.org/10.3389/fpubh.2022.1010124
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/194586
Title:
|
COVID-19 outbreaks analysis in the Valencian Region of Spain in the prelude of the third wave
|
Author:
|
Fuente, David
Hervás-Marín, David
Rebollo Pedruelo, Miguel
Conejero, J. Alberto
Oliver, Nuria
|
UPV Unit:
|
Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
Universitat Politècnica de València. Escuela Politécnica Superior de Alcoy - Escola Politècnica Superior d'Alcoi
|
Issued date:
|
|
Abstract:
|
[EN] IntroductionThe COVID-19 pandemic has led to unprecedented social and mobility restrictions on a global scale. Since its start in the spring of 2020, numerous scientific papers have been published on the characteristics ...[+]
[EN] IntroductionThe COVID-19 pandemic has led to unprecedented social and mobility restrictions on a global scale. Since its start in the spring of 2020, numerous scientific papers have been published on the characteristics of the virus, and the healthcare, economic and social consequences of the pandemic. However, in-depth analyses of the evolution of single coronavirus outbreaks have been rarely reported. MethodsIn this paper, we analyze the main properties of all the tracked COVID-19 outbreaks in the Valencian Region between September and December of 2020. Our analysis includes the evaluation of the origin, dynamic evolution, duration, and spatial distribution of the outbreaks. ResultsWe find that the duration of the outbreaks follows a power-law distribution: most outbreaks are controlled within 2 weeks of their onset, and only a few last more than 2 months. We do not identify any significant differences in the outbreak properties with respect to the geographical location across the entire region. Finally, we also determine the cluster size distribution of each infection origin through a Bayesian statistical model. DiscussionWe hope that our work will assist in optimizing and planning the resource assignment for future pandemic tracking efforts.
[-]
|
Subjects:
|
COVID-19
,
SARS-CoV-2
,
Epidemiological analysis
,
Cluster
,
Outbreak modeling
,
Biomedical data science
,
Bayesian statistical model
|
Copyrigths:
|
Reconocimiento (by)
|
Source:
|
Frontiers in Public Health. (eissn:
2296-2565
)
|
DOI:
|
10.3389/fpubh.2022.1010124
|
Publisher:
|
Frontiers Media S.A.
|
Publisher version:
|
https://doi.org/10.3389/fpubh.2022.1010124
|
Coste APC:
|
4500 €
|
Project ID:
|
info:eu-repo/grantAgreement/GVA//COVID19%2F2021%2F100//VALENCIA IA4COVID/
|
Thanks:
|
NO has been partially supported by funding received by the ELLIS Unit Alicante Foundation from the Regional Government of Valencia in Spain (Generalitat Valenciana, Conselleria d'Innovacio, Universitats, Ciencia i Societat ...[+]
NO has been partially supported by funding received by the ELLIS Unit Alicante Foundation from the Regional Government of Valencia in Spain (Generalitat Valenciana, Conselleria d'Innovacio, Universitats, Ciencia i Societat Digital, Direccion General para el Avance de la Sociedad Digital), by virtue of a collaboration agreement (Convenio Singular). MR, JC, and NO have been partially funded by grants from the BBVA Foundation through the IA4COVID19 research project and from the Valencian Government, grant VALENCIA IA4COVID (GVA-COVID19/2021/100) research projects, technological development, and innovation (R+D+i) by COVID-19.
[-]
|
Type:
|
Artículo
|