作者: O. G. Pybus , C. Fraser , A. Rambaut
关键词: Infectious Disease Epidemiology 、 Genomics 、 Evolutionary biology 、 Sustained growth 、 Epidemiology 、 Molecular evolution 、 Mathematical modelling of infectious disease 、 Statistical inference 、 Molecular epidemiology 、 Biology 、 Data science 、 General Biochemistry, Genetics and Molecular Biology 、 General Agricultural and Biological Sciences
摘要: The fields of infectious disease epidemiology and molecular evolution have a surprising amount in common. At the most fundamental level they aim to describe explain basic biological processes transmission loss, pathogens parasites one case, genetic polymorphisms other. Both disciplines are rigorously quantitative underpinned by mature framework dynamical mathematical models. These frameworks were derived logically from first principles survived mostly intact as empirical data sufficient accuracy examine them became available: situation far more common physical sciences than biology. Furthermore, stochastic models evolution, progress both has been accelerated recent decades rapid sustained growth computer processing power concomitant advances methods statistical inference.