Various methods are employed for anomaly detection in epidemiology:
1. Statistical Methods: Techniques such as control charts, time-series analysis, and regression models are commonly used to detect deviations from expected trends. 2. Machine Learning: Advanced machine learning algorithms, including clustering, classification, and neural networks, can identify complex patterns and anomalies in large datasets. 3. Spatial Analysis: Geographic Information Systems (GIS) and spatial statistics help in detecting anomalies based on location data, identifying hotspots of disease occurrence. 4. Syndromic Surveillance: This involves monitoring symptom data from various sources (e.g., emergency departments, pharmacies) to detect unusual patterns indicative of an outbreak.
