Sentence examples for models in epidemiology from inspiring English sources

The SIR (susceptible, infectious, recovered) epidemic model is one of the most popular epidemic models in epidemiology; it was initially proposed by Kermack and Mckendrick [1 4].

Therefore, considering the impact of mathematical models in epidemiology, it is important to build them on realistic assumptions.

The susceptible-infected-susceptible model (SIS model) is one of the simplest classical models in epidemiology.

This attenuates concerns expressed about the robustness of predictive models in epidemiology [ 16].

A lot of models in epidemiology, historically [ 32, 39], have been linear-based on the principle of parsimony [ 1- 3].

The unique capacity of epidemiologic transition theory to identify ultimate causes in disease risk means that transition theory models can be usefully incorporated into socioecological models in epidemiology.

Although epidemiology largely maintains its focus on single disease conditions and proximate causes, the rise of the socioecological model in epidemiology represents an opportunity for integrating epidemiologic transition theory into epidemiologic theory and practice.

Mathematical modeling in epidemiology provides understanding of the mechanisms that influence the spread of a disease and suggests control strategies.

Some researchers have exploited the framework of compartmental modeling in epidemiology and tried to introduce the concept of networks-based models either for the description of social contagion processes as done in [19] or for the study of the propagation of electronic and computer viruses as in [20, 21].

Mathematical modeling in epidemiology (MME) is being used increasingly.

The increased use of mathematical modeling in epidemiology (MME) is widely acknowledged [1].