COVID19 Surge Prediction
Our dataset was last updated . The most recent samples represented are from .
Please scroll down past the chart for a description of our methodology and a more complete data summary. To view data for a different protein, click one of the links near the top of the page.
This service monitors SARS-CoV-2 mutations. Potential surge in human COVID19 infection cases is predicted based on the increase in rate of mutations.
Methodology in Brief: Mutations in DNA sequence that change the nucleotides corresponding to degenerate codons (silent mutations) and do not result in the change of the coded protein amino acids are considered synonymous mutations (Ks). Mutations that result in the change of amino acids are considered non-synonymous (Ka). The higher rate of non-synonymous mutations would correspond to changing viral proteins, and therefore is observed in proteins evolving with gain or improvement of function.
For our calculations, the original SARS-CoV-2 sequence from Wuhan is used as reference sequence for the calculated values (Ka and Ks). Sequences from NCBI/Genbank are used regularly to update the Ka and Ks values. All 26 proteins in SARS-CoV-2 are separately analyzed. The number of new COVID19 infections in humans (weekly) is also depicted.
Observations: Spike protein showed increased rates of mutations at the onset of SARS-CoV-2 Delta and Omicron variants. The rapid rate of mutations 7-10 days before the rapid increase in cases is observed.
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Only protein sequences noted as complete and lacking ambiguous bases have been included in our dataset. Accessions without at least one qualifying protein sequence are not represented.
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