There are several strategies to mitigate computational overhead in epidemiology:
Data Preprocessing: Clean and preprocess data to reduce its size and complexity without losing essential information. Efficient Algorithms: Utilize optimized algorithms and code practices that minimize computational demands. Parallel Processing: Implement parallel processing techniques to distribute computational tasks across multiple processors. Cloud Computing: Leverage cloud computing resources to access higher computational power on-demand. Model Simplification: Simplify models where possible, focusing on the most critical variables and parameters.
