Data quality is crucial in epidemiology. Inaccurate or incomplete data can lead to incorrect conclusions and recommendations. Poor data quality can result from various factors, including inadequate data collection methods, reporting biases, and errors in data analysis. This can have a cascading negative impact, affecting public health policies and interventions.
