Many mathematical studies have focused on modelling COVID-19 and the effect of interventions on its containment. Statistical analysis of epidemiological data is useful to describe, quantify and summarize the mode of disease transmission in susceptible populations. In this study, mobility as a factor in the spread of the pandemic is addressed.
Mobility is a key factor; the greater travel volumes, the greater probability of virus spread. In this project, different generalized linear models (gamma distribution) were built to predict how many trips were made between two OD pairs (Origin-Destination) and thus this information was used for the epidemiological model that was built to calculate the spread of the virus and the probability of infection.
CENIT provided cell phone data analysis, modelling to predict the number of trips between two OD peers and an analysis of mobility patterns.
Client: Technology Center of Catalonia