Bjarke Frost Nielsen

The paper develops a Bayesian model to show that defective viral genomes modulate type I interferon dynamics by both inducing and suppressing IFN through cumulative exposure, explaining how pandemic viruses evade innate immunity.

The paper introduces LEAP, a mathematical model of respiratory viral infection that captures local plaque growth and long-range seeding, showing that few long-range events are needed for viral spread and that interferon has limited impact on growth in well-adapted viruses.

The paper develops a spatially explicit model of in vitro viral infection with DIPs, showing how they affect IFN response and plaque morphology.

This study models stochasticity in viral release and IFN response to show how timing variability affects early infection dynamics, finding asymmetrical impacts on virus expansion and host containment.

The paper quantifies how respiratory pathogens return to pre-pandemic dynamics after interventions, finding that susceptible population replenishment rates determine their resilience to perturbations.

The paper develops a stochastic framework to model how immunity influences viral adaptation rates, showing how parameters like immunity strength and transmissibility shape phylodynamic curves and escape variant emergence risks.

This study analyzes the evolution of the human influenza A NS gene using temporal distance measures, revealing a continuous genetic backbone and a deviation in the 2009 pandemic.

The paper models SARS-CoV-2 infection spread using a cellular automaton, showing that heterogeneity in infections arises from sensitivity near a critical threshold and that few IFN-primed cells can limit viral proliferation.

The paper challenges the two-step model of tube formation by showing that either cell intercalation or wedging alone can suffice for the sheet-to-tube transition, supported by simulations of Drosophila, Sea urchin, and mammalian systems.