Glossary Section: General modelling terms

A simplified representation of a real-world phenomenon.

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.

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.

Equations used to illustrate the relationships between the dependent and independent variables following calculus principles.

A State variable often referring to the number of individuals who are infectious (seed), at the start of an epidemic simulation.

Methods used to test assumptions made about the model parameters or the simulated scenarios in a model.

A mathematical operation mimicking real-world phenomena described by a model.

Number of individuals in a compartment that can vary over time.

Refers to a certain time point in the future when the effect(s) of intervention(s) will be evaluated.

A type of Sensitivity analysis that further restricts parameter values to represent reality for specific population(s). Parameter values are often obtained after model fitting. Uncertainty analysis helps assess the degree to which parameters influence model outcomes.

Assessing model performance (usually against data) to determine the applicability of the model.

Adapting parameter values according to changes (e.g., behavioral, environmental).