A phenomenological model for COVID-19 data taking into account neighboring-provinces effect and random noise
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Títol
A phenomenological model for COVID-19 data taking into account neighboring-provinces effect and random noiseData de publicació
2022Editor
WileyISSN
0039-0402; 1467-9574Cita bibliogràfica
CALATAYUD, Julia; JORNET, Marc; MATEU, Jorge. A phenomenological model for COVID‐19 data taking into account neighboring‐provinces effect and random noise. Statistica Neerlandica, 2023, 77, 2, p. 146-155Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
https://onlinelibrary.wiley.com/doi/full/10.1111/stan.12278Versió
info:eu-repo/semantics/submittedVersionParaules clau / Matèries
Resum
We model the incidence of the COVID-19 disease during the first wave of the epidemic
in Castilla-Leon (Spain). Within-province dynamics may be governed by a generalized logistic
map, but this lacks of spatial ... [+]
We model the incidence of the COVID-19 disease during the first wave of the epidemic
in Castilla-Leon (Spain). Within-province dynamics may be governed by a generalized logistic
map, but this lacks of spatial structure. To couple the provinces, we relate the daily new infec-
tions through a density-independent parameter that entails positive spatial correlation. Pointwise
values of the input parameters are fitted by an optimization procedure. To accommodate the
significant variability in the daily data, with abruptly increasing and decreasing magnitudes, a
random noise is incorporated into the model, whose parameters are calibrated by maximum like-
lihood estimation. The calculated paths of the stochastic response and the probabilistic regions
are in good agreement with the data. [-]
Publicat a
Statistica Neerlandica, 2023, 77, 2Entitat finançadora
Universitat Jaume I | Generalitat Valenciana | Ministerio de Ciencia e Innovación
Codi del projecte o subvenció
PID2019‐107392RB‐I00 | AICO/2019/198
Drets d'accés
"This is the pre-peer reviewed version of the following article: CALATAYUD, Julia; JORNET, Marc; MATEU, Jorge. A phenomenological model for COVID‐19 data taking into account neighboring‐provinces effect and random noise. Statistica Neerlandica, 2023, 77, 2, which has been published in final form at https://doi.org/10.1111/stan.12278. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions."
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info:eu-repo/semantics/openAccess
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