Modeling Challenges of Ebola Virus-Host Dynamics during Infection and Treatment
Daniel S Chertow1, Louis Shekhtman2,3, Yoav Lurie4
1Critical Care Medicine Department, National Institutes of Health Clinical Center, Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA.
Viruses
|January 23, 2020
Summary
Mathematical models of Ebola virus (EBOV) infection struggle with limited data. This study compared patient data to a model, revealing challenges in predicting EBOV dynamics and treatment efficacy.
Area of Science:
- Virology
- Mathematical Biology
- Infectious Disease Modeling
Background:
- Mathematical modeling of Ebola virus (EBOV) in-host dynamics is limited by scarce kinetic data and lack of approved therapies.
- Current models often simplify EBOV infection to a single compartment, potentially overestimating rapid refractoriness to infection.
Purpose of the Study:
- To compare in-host EBOV kinetics and hepatocellular injury in a patient with Ebola virus disease (EVD) against existing mathematical model predictions.
- To explore the predictive accuracy of a specific EBOV model under various conditions, including antiviral therapy.
Main Methods:
- Analysis of EBOV kinetics across multiple anatomical compartments and hepatocellular injury in a critically ill EVD patient.
- Recapitulation and comparison of a published mathematical model's predictions using established inputs and assumptions, with and without simulated antiviral treatment.
Main Results:
- Observed EBOV kinetics and patient injury patterns differed from the predictions of a simplified, single-compartment model.
- The study identified significant challenges in accurately modeling EBOV-host dynamics and the efficacy of antiviral interventions.
Conclusions:
- Existing mathematical models for EBOV infection require refinement due to complexities in viral dissemination and host response.
- Iterative, interdisciplinary efforts are crucial to improve EBOV mathematical models for better understanding of pathogenesis and treatment strategies.
