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Modelling Mobility Data during COVID-19 in Portugal with R-INLA
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Orientador(es)
Resumo(s)
The COVID-19 pandemic underscored the vital role of mathematical modelling in epidemiology, supporting the forecasting of disease trends and informing public health strategies. In Portugal, modelling efforts highlighted the effectiveness of physical distancing in reducing transmission and offered important insights into the impacts of deconfinement and vaccination on disease burden. The period also saw an increased use of non-traditional data sources, particularly human mobility data, which acted as a proxy for contact patterns and helped refine models of disease spread.
In this context, we aim to model mobility patterns across districts in Portugal during the COVID-19 pandemic using Google Mobility Reports. Our objective is to identify which covariates are most relevant for predicting mobility dynamics during this period within a spatiotemporal modelling framework.
Descrição
Palavras-chave
INLA Mobility Spatio-Temporal Modelling COVID-19 Portugal