Abstract

We adapt the Covasim agent-based model for predicting new COVID-19 cases by tuning the transmissibility rate with information on the impact of the most common non-pharmaceutical interventions (NPIs) obtained through machine learning models. Such impact has been estimated thanks to the information on applying pools of NPIs worldwide from the Oxford COVID-19 Government Response Tracker.

This approach permits the simulation of a whole country or a smaller region, providing information about asymptomatic, recovery, severe, and critical new cases and enabling governments and authorities to set NPIs plans to cope with the pandemic.

Details

Title
Adaptation of the COVASIM model to incorporate non-pharmaceutical interventions: Application to the Dominican Republic during the second wave of COVID-19
Author
Solares-Hernández, Pedro A 1 ; Garibo-i-Orts, Òscar 2 ; Conejero, J Alberto 3 ; Manzano, Fernando A 4 

 Universidad APEC. Santo Domingo, Dominican Republic; Instituto Universitario de Matemática Pura y Aplicada. Universitat Politècnica de València, Spain 
 Instituto Universitario de Matemática Pura y Aplicada. Universitat Politècnica de València, Spain; GRID - Grupo de Investigación en Ciencia de Datos. Valencian International University - VIU, Spain 
 Instituto Universitario de Matemática Pura y Aplicada. Universitat Politècnica de València, Spain 
 Universidad APEC. Santo Domingo, Dominican Republic 
Pages
2319-2332
Publication year
2023
Publication date
2023
Publisher
De Gruyter Poland
e-ISSN
24448656
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3191247560
Copyright
© 2023. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.