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Open AccessArticle

Modeling Challenges of Ebola Virus–Host Dynamics during Infection and Treatment

1
Critical Care Medicine Department, National Institutes of Health Clinical Center, Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA
2
The Program for Experimental and Theoretical Modeling, Division of Hepatology, Department of Medicine, Loyola University Medical Center, Maywood, IL 60153, USA
3
Network Science Institute, Northeastern University, Boston, MA 02115, USA
4
Liver Unit, Shaare Zedek Medical Center and the Hebrew University of Jerusalem, Jerusalem 9103102, Israel
5
Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
6
Translational Hepatology Unit, Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA
*
Author to whom correspondence should be addressed.
Viruses 2020, 12(1), 106; https://doi.org/10.3390/v12010106
Received: 1 November 2019 / Revised: 10 December 2019 / Accepted: 14 January 2020 / Published: 16 January 2020
(This article belongs to the Special Issue Medical Advances in Viral Hemorrhagic Fever Research)
Mathematical modeling of Ebola virus (EBOV)–host dynamics during infection and treatment in vivo is in its infancy due to few studies with frequent viral kinetic data, lack of approved antiviral therapies, and limited insight into the timing of EBOV infection of cells and tissues throughout the body. Current in-host mathematical models simplify EBOV infection by assuming a single homogeneous compartment of infection. In particular, a recent modeling study assumed the liver as the largest solid organ targeted by EBOV infection and predicted that nearly all cells become refractory to infection within seven days of initial infection without antiviral treatment. We compared our observations of EBOV kinetics in multiple anatomic compartments and hepatocellular injury in a critically ill patient with Ebola virus disease (EVD) with this model’s predictions. We also explored the model’s predictions, with and without antiviral therapy, by recapitulating the model using published inputs and assumptions. Our findings highlight the challenges of modeling EBOV–host dynamics and therapeutic efficacy and emphasize the need for iterative interdisciplinary efforts to refine mathematical models that might advance understanding of EVD pathogenesis and treatment. View Full-Text
Keywords: Ebola virus; mathematical modeling; viral kinetics; liver Ebola virus; mathematical modeling; viral kinetics; liver
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Chertow, D.S.; Shekhtman, L.; Lurie, Y.; Davey, R.T.; Heller, T.; Dahari, H. Modeling Challenges of Ebola Virus–Host Dynamics during Infection and Treatment. Viruses 2020, 12, 106.

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