Development of forecast models for COVID-19 hospital admissions using anonymized and aggregated mobile network data

Development of forecast models for COVID-19 hospital admissions using anonymized and aggregated mobile network data

Abstract Reliable forecast of COVID-19 hospital admissions in near-term horizons can help enable effective resource management which is vital in reducing pressure from healthcare services. The use of mobile network data has come to attention in response to COVID-19 pandemic leveraged on their abilit...

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Bibliographic Details
Main Authors: Jalil Taghia, Valentin Kulyk, Selim Ickin, Mats Folkesson, Cecilia Nyström, Kristofer Ȧgren, Thomas Brezicka, Tore Vingare, Julia Karlsson, Ingrid Fritzell, Ralph Harlid, Bo Palaszewski, Magnus Kjellberg, Jörgen Gustafsson
Format: Article
Language:English
Published: Nature Portfolio 2022-10-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-22350-6

Internet

https://doi.org/10.1038/s41598-022-22350-6

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