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. |
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. |