Granger causality and time series regression for modelling the migratory dynamics of influenza into Brazil
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 r...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:269975 |
| Acceso en línea: | https://ddd.uab.cat/record/269975 https://dx.doi.org/urn:doi:10.2436/20.8080.02.122 |
| Access Level: | acceso abierto |
| Palabra clave: | Flu Time series regression Variable selection Genetic diversity Granger causality |
| Sumario: | 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. |
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