Network Self-Exciting Point Processes To Measure Health Impacts of COVID-19
28 Pages Posted: 12 Aug 2021
Date Written: July 25, 2021
Abstract
The assessment of the health impacts of the COVID-19 pandemic requires the consideration of mobility networks. To this aim, we propose to augment spatio-temporal point process models with mobility network covariates. We show how the resulting model can be employed to predict contagion patterns and to help important decisions such as the distribution of vaccines. The application of the proposed methodology to 27 European countries shows that human mobility, along with vaccine doses and government policies, are significant predictors of the number of new COVID-19 reported infections and are therefore key variables for decision making.
Note: Funding: This study is funded by the European Union, Horizon 2020, research and innovation
program "PERISCOPE: Pan European Response to the ImpactS of COVID-19
and future Pandemics and Epidemics", grant agreement No. 101016233,
H2020-SC1-PHE-CORONAVIRUS-2020-2-RTD.
Declaration of Interests: None to declare
Keywords: COVID-19, Epidemic Modelling, Hawkes Process, Interconnectedness, Mobility Networks.
JEL Classification: C45, C53
Suggested Citation: Suggested Citation