While alternative methods offer numerous benefits, they also come with challenges. For instance, computational models rely heavily on the quality and accuracy of input data. Inaccurate or incomplete data can lead to misleading results. Similarly, syndromic surveillance can produce false positives, leading to unnecessary alarm. In participatory epidemiology, ensuring the reliability and validity of the data collected by community members can be challenging.
