Towards multiscale modeling of influenza infection

TL;DR: A conceptual framework is presented and examples of studies that have taken first steps towards development of a quantitative framework that scales from within-host infections to population-level fitness of different pathogens are provided.

TL;DR: In this paper, a mathematical model for the single-cell reproductive cycle of influenza A virus in animal cells is presented, which accounts for the individual steps of the process such as attachment, internalization, genome replication and translation, and progeny virion assembly.

TL;DR: This paper presents mathematical models of quasispecies theory and exact results for the dynamics of viral population dynamics, which show that viral evolutionary strategies based on lethal mutagenesis and error threshold based on fidelity variants and RNA quasipecies are viable.

TL;DR: Overall, VK modeling has provided new insights into the understanding of the disease progression and the modes of action of several drugs and it is expected that VK modeling will be increasingly used in the coming years to optimize drug regimens in order to improve therapeutic outcomes and treatment tolerability for infectious diseases.

TL;DR: This book discusses the biology of host-microparasite associations, dynamics of acquired immunity heterogeneity within the human community indirectly transmitted helminths, and the ecology and genetics of hosts and parasites.

TL;DR: Threshold theorems involving the basic reproduction number, the contact number, and the replacement number $R$ are reviewed for classic SIR epidemic and endemic models and results with new expressions for $R_{0}$ are obtained for MSEIR and SEIR endemic models with either continuous age or age groups.

TL;DR: Social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals achieve their goals.

TL;DR: This work proposes a model of an assortatively mixed network and finds that networks percolate more easily if they are assortative and that they are also more robust to vertex removal.