There are several methods to handle noise in epidemiological data: 1. Data Cleaning: Identifying and correcting errors in the dataset. 2. Statistical Techniques: Methods like smoothing or filtering can help reduce the impact of noise. 3. Replication: Conducting repeated measurements or studies to ensure consistency.
