SARS-CoV-2 worldwide emergence and evolution has resulted in variants containing mutations resulting in immune evasive epitopes that decrease vaccine efficacy. We acquired clinical samples, analyzed SARS-CoV-2 genomes, used the most worldwide emerged spike mutations from Variants of Concern/Interest, and developed an algorithm for monitoring the SARS-CoV-2 vaccine platform. The algorithm partitions logarithmic-transformed prevalence data monthly and Pearson's correlation determines exponential emergence. The SARS-CoV-2 genome evaluation indicated 49 mutations. Nine of the ten most worldwide prevalent (>70%) spike protein changes have r- values >0.9. The tenth, D614G, has a prevalence >99% and r -value of 0.67. The resulting algorithm is based on the patterns these ten substitutions elucidated. The strong positive correlation of the emerged spike protein changes and algorithmic predictive value can be harnessed in designing vaccines with relevant immunogenic epitopes. SARS-CoV-2 is predicted to remain endemic and continues to evolve, so must SARS-CoV-2 monitoring and next-generation vaccine design.