Alamo T. , G. Reina D. , MILLÁN GATA, PABLO, Preciado V.M. , Giordano G.
No
Annu Rev Control
Review
Científica
10.699
3.742
01/01/2021
000734449000024
2-s2.0-85108971162
This survey analyses the role of data-driven methodologies for pandemic modelling and control. We provide a roadmap from the access to epidemiological data sources to the control of epidemic phenomena. We review the available methodologies and discuss the challenges in the development of data-driven strategies to combat the spreading of infectious diseases. Our aim is to bring together several different disciplines required to provide a holistic approach to epidemic analysis, such as data science, epidemiology, and systems-and-control theory. A 3M-analysis is presented, whose three pillars are: Monitoring, Modelling and Managing. The focus is on the potential of data-driven schemes to address three different challenges raised by a pandemic: (i) monitoring the epidemic evolution and assessing the effectiveness of the adopted countermeasures; (ii) modelling and forecasting the spread of the epidemic; (iii) making timely decisions to manage, mitigate and suppress the contagion. For each step of this roadmap, we review consolidated theoretical approaches (including data-driven methodologies that have been shown to be successful in other contexts) and discuss their application to past or present epidemics, such as Covid-19, as well as their potential application to future epidemics. © 2021 The Authors
Data Science; Data-driven methods; Holistic approach; Infectious disease; Modelling and controls; Modelling and forecasting; Survey analysis; Systems and control theory; Theoretical approach; Disease control