Using mobile phone data to estimate dynamic population changes and improve the understanding of a pandemic: A case study in Andorra.

ABSTRACT: Compartmental models are often used to understand and predict the progression of an infectious disease such as COVID-19. The most basic of these models consider the total population of a region to be closed. Many incorporate human mobility into their transmission dynamics, usually based on static and aggregated data. However, mobility can change dramatically during a global pandemic as seen with COVID-19, making static data unsuitable. Recently, large mobility datasets derived from mobile devices have been used, along with COVID-19 infections data, to better understand the relationship between mobility and COVID-19. However, studies to date have relied on data that represent only a fraction of their target populations, and the data from mobile devices have been used for measuring mobility

SUBMITTER: Berke A 

PROVIDER: S-EPMC9041757 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature