Topic 1: Key Components Of Mathematical Models
Topic 1: Key components of mathematical models
Now that you know more about how modeling is used in public health, you might be wondering what goes into models to produce the results.
Mathematical models describe the relationship between inputs and outputs in mathematical terms. They use data and assumptions to make projections about the future and to answer specific questions.
Click on the plus signs below to learn about the key components of mathematical models.
Input: data and assumptions used in the model
Data: Numbers that have been measured in the real world. Examples of data used in mathematical models include measurements of how effective interventions are, numbers of new infections in a certain place and time period, the cost of delivering services, rates of disease transmission or disease progression, population sizes.
Assumption: A modeler’s best guess at numbers or relationships that are unknown but required as part of a model. For example, a modeler might assume a cost of an intervention if the cost is unknown, or they might assume a specific type of mathematical relationship between two parts of the model.
Output: the findings and results from the model. Outputs from the model can be anything from projections about the future to answers to the research questions the modelers were originally asking.