Introduction
In the current literature, there is considerable heterogeneity in common terms related to infectious disease epidemiology and modelling. Furthermore, definitions of these terms are not often provided in research papers. This glossary presents a comprehensive list of terms and their definitions to unify the use and interpretation of infectious disease epidemiology and modelling terminology. Although the most frequently used definitions were included in this glossary, researchers may have alternative definitions for certain terms in the context of their research. Therefore, it is recommended that the readers first check for definitions provided by the authors when reading infectious disease mathematical modelling publications.
Filters
Analytical solution
Solving equations to reach a solution pertaining to the relationships between model parameters and outcomes.
Calibration (model fitting)
Fitting of model parameters to data. This is one step in model development to ensure that the model output is representative of the data used.
Credibility
The validity of model outcomes and results.
Forcing (extrinsic forcing)
Adapting parameter values according to changes (e.g., behavioral, environmental).
Kendall tau distance
A measure of the difference between two ranked, pairwise lists. Statistically, the Kendall tau distance measures the strength of the relationship between two variables.
A simplified representation of a real-world phenomenon.
Monte Carlo simulation/ Monte Carlo method/ multiple probability simulation
A mathematical technique predicting outcomes of an uncertain situation, which produces an estimate range of values using probability distributions. This method is used with stochastic models (i.e., compartmental, network, individual-based) and employs random sampling.
Numerical solution
In stochastic models, Numerical solution refers to events arising from probability at each time point. In compartmental models (whether deterministic or stochastic), Numerical solution indicates differential equations derived from computer programming or approximation techniques.
Ordinary differential equations
Equations used to illustrate the relationships between the dependent and independent variables following calculus principles.
Seed or initial conditions
A State variable often referring to the number of individuals who are infectious (seed), at the start of an epidemic simulation.