RESUMO
We present a differential equation model of the innate immune response to SARS-CoV-2 within the alveolar epithelium. Critical determinants of the viral dynamics and host response, including type I and type II alveolar epithelial cells, interferons, chemokines, toxins and innate immune cells, are included. We estimate model parameters, compute the within-host basic reproductive number, and study the impacts of therapies, prophylactics, and host/pathogen variability on the course of the infection. Model simulations indicate that the innate immune response suppresses the infection and enables the alveolar epithelium to partially recover. While very robust antiviral therapy controls the infection and enables the epithelium to heal, moderate therapy is of limited benefit. Meanwhile interferon therapy is predicted to reduce viral load but exacerbate tissue damage. The deleterious effects of interferon therapy are especially apparent late in the infection. Individual variation in ACE2 expression, epithelial cell interferon production, and SARS-CoV-2 spike protein binding affinity are predicted to significantly impact prognosis.
RESUMO
The 2014 Ebola epidemic was the largest on record. It evidenced the need for improved models of the spread of Ebola. In this research we focus on modelling Ebola within a small village or community. Specifically, we investigate the potential of basic Susceptible-Exposed-Infectious-Recovered (SEIR) models to describe the initial Ebola outbreak, which occurred in Meliandou, Guinea. Data from the World Health Organization is used to compare the accuracy of various models in order to select the most accurate models of transmission and disease-induced responses. Our results suggest that (i) density-dependent transmission and mortality-induced behavioural changes shaped the course of the Ebola epidemic in Meliandou, while (ii) frequency-dependent transmission, disease-induced emigration, and infection-induced behavioural changes are not consistent with the data from this epidemic.
