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Due to its high transmissibility, Omicron BA.1 ousted the Delta variant tobecome a dominating variant in late 2021 and was replaced by more transmissibleOmicron BA.2 in March 2022. An important question is which new variants willdominate in the future. Topology-based deep learning models have had tremendoussuccess in forecasting emerging variants in the past. However, topology isinsensitive to homotopic shape variations in virus-human protein-proteinbinding, which are crucial to viral evolution and transmission. This challengeis tackled with persistent Laplacian, which is able to capture both thetopology and shape of data. Persistent Laplacian-based deep learning models aredeveloped to systematically evaluate variant infectivity. Our comparativeanalysis of Alpha, Beta, Gamma, Delta, Lambda, Mu, and Omicron BA.1, BA.1.1,BA.2, BA.2.11, BA.2.12.1, BA.3, BA.4, and BA.5 unveils that Omicron BA.2.11,BA.2.12.1, BA.3, BA.4, and BA.5 are more contagious than BA.2. In particular,BA.4 and BA.5 are about 36\% more infectious than BA.2 and are projected tobecome new dominating variants by natural selection. Moreover, the proposedmodels outperform the state-of-the-art methods on three major benchmarkdatasets for mutation-induced protein-protein binding free energy changes.

Persistent Laplacian projected Omicron BA.4 and BA.5 to become new dominating variants