## Transmission dynamics model

Primarily describes the dynamics of infectious diseases between infected and susceptible individuals. The model accounts for the risk of infection in the susceptible individuals by considering the prevalence of infected individuals and may consider other environmental factors (e.g., reservoir, vectors).

## State‐transition model

Involves various health states and assumes that individuals are able to transition between the health states. These models are often built upon Markov or agent-based models.

## Stochastic model

In contrast to deterministic models, stochastic models have random components; parameters or variables could be random (i.e., can be represented with a probability distribution).

## Static model

All variables do not vary across time; variables are constant.

## Within-host model

Used to describe cell-pathogen interactions (compare Between-host model).

## Theory‐driven model

Builds upon assumptions or existing knowledge about relationships (e.g., effectiveness of an intervention) (compare to data-driven model).

## Mathematical model

Any model represented by equations (mathematical framework) to describe observed phenomena (e.g., data) or predict an outcome.

## Micro‐simulation model

Individual-based model/agent-based model.

## Individual‐based model

A Stochastic model where individuals are described as discrete entities with their own characteristics. This model may be used when heterogeneity should be considered in a population. Also known as agent-based model/micro-simulation model.

## Mallows model

A model based on probability for distribution on permutation. The probability of a permutation can be estimated as a function of the Kendall distance from the centre permutation when the spread of the distribution is known.

## Mechanistic model

Describes real-world interactions pertaining to infection transmission, pathogenesis, and measures of control such as vaccination (compare Phenomenological model).

## Metapopulation model

Accounts for subpopulations (patches) and their within and between dynamics. This model can be employed to investigate the movements and contact structures of host subpopulations.