Computational Intelligence for Modeling Drift and Noise in Mass Spectra for Detecting SARS CoV2 from Patients' Breaths. The COVID-19 pandemic is a global crisis that requires effective control measures to prevent further spread of the virus. The virus is primarily spread through droplets, making the identification of clusters of positive cases a crucial step in limiting its transmission. Mass testing is an effective way to quickly identify positive cases, but many available tests are invasive and may require medical assistance, which can be stressful or dangerous. Therefore, there is a need for non-invasive testing methods that can aid in the prompt and accurate diagnosis of COVID-19, while reducing the risk of transmission and minimizing patient discomfort.