Several challenges affect data quality in epidemiology. Bias can occur during data collection, leading to inaccurate representations. Underreporting is another significant issue, especially in low-resource settings where health infrastructure might be inadequate. Data may also be affected by inconsistent coding and classification systems, making it hard to standardize and compare data across different regions or time periods. Additionally, ethical concerns around privacy and consent can limit the availability of detailed individual-level data.
