The state of the cardiovascular system can be assessed from time-series signals including heart rate and blood pressure. Characteristics of these signals are used to determine pathophysiology. Experienced clinicians can visually inspect signals and with high level of certainty determine key observed dynamics however analysis with computational models can uncover the underlying mechanisms driving these dynamics. This talk will address how mathematical modeling can be adapted to match patient specific behavior and how the optimized system equations can be used to predict emergent behavior. Sensitivity analysis, parameter estimation, and uncertainty quantification are mathematical tools used analyze models for individual patients. Focus will be on studying dynamics observed in patients diagnosed with postural orthostatic tachycardia (increased heart rate brought on by change in posture, e.g. sit to stand) observed in some girls after vaccination against the human papilloma virus (HPV). Girls exhibiting side-effects to this vaccine often feel dizzy, light-headed, and tired. It is believed that these symptoms are related to pathophysiology within the cardiovascular control system, which is supposed to keep heart rate and blood pressure constant. To understand how the system is impacted we use models to analyze patient specific changes observed during head-up tilt, Valsalva (breath holding), and deep breathing.