Data quality in epidemiology is defined by several attributes, including accuracy, completeness, reliability, and timeliness. Accuracy refers to the correctness of the data, ensuring that it correctly represents the real-world conditions it aims to measure. Completeness involves the inclusion of all necessary data points, preventing gaps that could skew results. Reliability indicates the consistency of the data when measured under the same conditions. Timeliness refers to the availability of data within a suitable time frame to be relevant for current health assessments and interventions.
