Hybrid Modeling of Ebola Propagation.

Autor: Tanade C; Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA., Pate N; Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA., Paljug E; Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA., Hoffman RA; Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA., Wang MD; Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA.
Jazyk: angličtina
Zdroj: Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering [Proc IEEE Int Symp Bioinformatics Bioeng] 2019 Oct; Vol. 2019, pp. 204-210. Date of Electronic Publication: 2019 Dec 26.
DOI: 10.1109/bibe.2019.00044
Abstrakt: The Ebola virus disease (EVD) epidemic that occurred in West Africa between 2014-16 resulted in over 28,000 cases and 11,000 deaths - one of the deadliest to date. A generalized model of the spatiotemporal progression of EVD for Liberia, Guinea, and Sierra Leone in 2014-16 remains elusive. There is also a disconnect in the literature on which interventions are most effective in curbing disease progression. To solve these two key issues, we designed a hybrid agent-based and compartmental model that switches from one paradigm to the other on a stochastic threshold. We modeled disease progression with promising accuracy using WHO datasets.
Databáze: MEDLINE