Why is Computational Overhead Significant in Epidemiology?
The significance of computational overhead in epidemiology cannot be overstated. Epidemiologists often work with large datasets that include information on disease incidence, demographics, environmental factors, and more. Running complex models on these datasets can be computationally demanding. High computational overhead can slow down analyses, delay the response to epidemics, and limit the scope of studies.
