Computational overhead refers to the additional computing resources, such as time and memory, required to perform tasks beyond the basic processing of data. In the context of epidemiology, it pertains to the extra computational effort needed to run complex epidemiological models, conduct simulations, and analyze large datasets. Understanding and managing computational overhead is crucial for efficient disease surveillance and control.
