Modeling and inference of cell population dynamics
Understanding the dynamic host-pathogen interactions can have a substantial impact in our fight against infectious diseases. In this regard, kinetic models are a robust means of analyzing experimental results and explaining biological phenomena without testing every scenario experimentally. By considering the dynamical interactions of populations of viruses, cells susceptible to infection (“target cells”), infected cells, and cells involved in the immune response, various aspects of the biology of infections have been quantified and elucidated. This modeling approach, termed “viral dynamics”, has been successfully used in many viral infections such as HIV, hepatitis C virus, hepatitis B virus, cytomegalovirus, and influenza virus. Substantial insights into the dynamics and pathogenesis of these infections have been gained through the development of mathematical models that describe host-pathogen interactions, allowing quantification of the rates of virus production and clearance and infected cell lifespans. In turn, this has facilitated the investigation of treatment strategies and predictions about how quickly drug resistant variants appear. Here, we discuss the power of this approach and use influenza viral dynamics and the effect of bacterial coinfection as case studies.