COVID-19 was declared by the World Health Organization in 2020 to be a pandemic. Analysis of COVID-19 related genetic pathways allows for a better understanding of the possible effects and sequelae of the disease. Using 6178 scRNA sequenced human cells, having a status of control/mild/severe COVID-19 disease status, differential expression of genes and pathways was analyzed. Using Gene Set Enrichment Analysis (GSEA), mild COVID-19 was found to over-express the Influenza Pathway. In order to identify genes important in COVID-19 severity, a deep learning classifier was trained. Classifiers were repeatedly trained for this task using 10 randomly selected genes from the total number of 18,958 genes. The highest performing classifier (AUC=0.748) was trained using: AC008626.1, SGO1, RHOBTB2, RBM41, NDUFAF4P1, COX5A, ZDHHC17, STX11, IPP, NUDT5 genes. These results further illustrate the other factors contributing to mild versus severe COVID-19, as well as evidence of potential misdiagnosis or overlapping pathway effects of Influenza and COVID-19.