Data contamination is particularly concerning in epidemiology because it can lead to erroneous epidemiological outcomes. Misleading data can skew the results of a study, leading to incorrect conclusions about disease causation, prevalence, and risk factors. This can have serious implications for public health policy and intervention strategies.
