The current paper proposes to use convolutional neural networks (CNN) to analyze human genome single nucleotide variants (SNVs) from nuclear deoxyribonucleic acid (DNA) and mitochondrial deoxyribonucleic acid (mtDNA) presented as a 2D image structure to understand if the answer to COVID-19 severities can be found in the human genome. That methodology was implemented with 447 Mexican population samples. From the results, two main groups were formed divided into symptomatic and asymptomatic cases composed of 80.986% and 19.014% respectively and the model was validated through an online survey of individuals, giving a 91.89% of accuracy.