What are the Challenges in Time Series Analysis in Epidemiology?
Despite its advantages, time series analysis in epidemiology faces several challenges:
Data Quality: Incomplete or inaccurate data can lead to misleading conclusions. Non-Stationarity: Many epidemiological time series are non-stationary, meaning their statistical properties change over time. Techniques like differencing or transformation are needed to stabilize the series. Outliers: Sudden spikes or drops in data, often due to outbreaks or reporting errors, can skew analysis and predictions. Complex Interactions: Diseases may interact with multiple factors, making it challenging to isolate individual effects.
