The inflammatory response to influenza A virus (H1N1): An experimental and mathematical study. (7th June 2015)

• Record Type: Journal Article
• Authors: Price, Ian; Mochan-Keef, Ericka D.; Swigon, David; Ermentrout, G. Bard; Lukens, Sarah; Toapanta, Franklin R.; Ross, Ted M.; Clermont, Gilles
• Is Part Of: Journal of theoretical biology. Volume 374(2015)
• Page Start: 83
• Page End: 93
• Publication Date: 2015-06-07
• Subjects: Mathematical model -- Inflammation -- Immune response -- Survival curve -- Bayesian inference; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2015.03.017
• Languages: English
• ISSNs: 0022-5193

Abstract

Abstract: Mortality from influenza infections continues as a global public health issue, with the host inflammatory response contributing to fatalities related to the primary infection. Based on Ordinary Differential Equation (ODE) formalism, a computational model was developed for the in-host response to influenza A virus, merging inflammatory, innate, adaptive and humoral responses to virus and linking severity of infection, the inflammatory response, and mortality. The model was calibrated using dense cytokine and cell data from adult BALB/c mice infected with the H1N1 influenza strain A/PR/8/34 in sublethal and lethal doses. Uncertainty in model parameters and disease mechanisms was quantified using Bayesian inference and ensemble model methodology that generates probabilistic predictions of survival, defined as viral clearance and recovery of the respiratory epithelium. The ensemble recovers the expected relationship between magnitude of viral exposure and the duration of survival, and suggests mechanisms primarily responsible for survival, which could guide the development of immuno-modulatory interventions as adjuncts to current anti-viral treatments. The model is employed to extrapolate from available data survival curves for the population and their dependence on initial viral aliquot. In addition, the model allows us to illustrate the positive effect of controlled inflammation on influenza survival.