Granger causality and time series regression for modelling the migratory dynamics of influenza into Brazil
Foerster Grande, Aline (Universidade Federal do Rio Grande do Sul (Brasil))
Pumi, Guilherme (Universidade Federal do Rio Grande do Sul (Brasil))
Cybis, Gabriela Bettella (Universidade Federal do Rio Grande do Sul (Brasil))

Fecha:	2022
Resumen:	In this work we study the problem of modelling and forecasting the dynamics of the influenza virus in Brazil at a given month, from data on reported cases and genetic diversity collected from previous months, in other locations. Granger causality is employed as a tool to assess possible predictive relationships between covariates. For modelling and forecasting purposes, a time series regression approach is applied considering lagged information regarding reported cases and genetic diversity in other regions. Three different models are analysed, including stepwise time series regression and LASSO.
Nota:	cknowledgments.Aline F. Grande and Guilherme Pumi gratefully acknowledge the support of CNPq and FAPERGS. Gabriela B. Cybis gratefully acknowledges the support of the Serrapilheira Institute (grant number Serra-G1709-18939). The authors are also grateful to Rafaela Gomes de Jesus for helping with the genetic diversity data assembly.
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Flu ; Time series regression ; Variable selection ; Genetic diversity ; Granger causality
Publicado en:	SORT : statistics and operations research transactions, Vol. 46 Núm. 2 (2022) , p. 161-188 (Articles) , ISSN 2013-8830

Adreça original: https://raco.cat/index.php/SORT/article/view/409378
DOI: 10.2436/20.8080.02.122

28 p, 875.4 KB

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