Statistics and Biostatistics seminar series
Location: M3 3127
Quantifying the risk of travelling during a pandemic using cellphone-derived mobility data
Since the beginning of the COVID-19 pandemic, public health authorities across the globe have implemented policies such as lockdowns in an attempt to reduce population mobility, and consequently, person-to-person contacts. It is well known that lockdowns reduce mobility, but the relationship between mobility and COVID-19 cases is still relatively unexplored. In this talk, we investigate methods for using cellphone-derived mobility networks to augment spatial/spatio-temporal models for COVID-19 using data from two Spanish autonomous communities. We start by developing extensions to Besag, York, and Mollié (BYM) models that utilizes these mobility data and show that they are superior to their purely spatial counterparts. We then develop a principled, interpretable spatio-temporal infectious disease model in an attempt to quantify the risk of travelling during the pandemic.