SARS-COV-2 Delta and Omicron community transmission networks
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Abstract
To date, calculations of SARS-CoV-2 transmission networks at a population level have not been performed. Networks that estimate infections between individuals and whether this results in a mutation, can evaluate fitness of a mutational clone by how much it expands in number as well as determining the likelihood a transmission results in a new variant.
Transmission networks of SARS-CoV-2 infection between individuals in Australia were estimated for Delta and Omicron variants using a novel method. Many of the sequences were identical, with clone sizes following power law distributions driven by negative binomial probability distributions for both the number of infections per individual and the number of mutations per transmission (mean 1.0 nucleotide change for Delta and 0.79 for Omicron). Using these distributions, an agent based model was able to replicate the observed clonal network structure, providing a basis for more detailed COVID-19 modelling. Recombination events, tracked by insertion/deletion (indel) patterns, occurred for each variant in these outbreaks. The residue at position 142 in the S open reading frame (ORF), frequently changed between G and D for Delta sequences, but this was independent of other mutations. On the other hand, several Omicron mutations were significantly connected across different ORF. This model reveals key transmission characteristics of SARS-CoV-2 and may complement traditional contact tracing and other public health strategies. This methodology can also be applied to other diseases as genetic sequencing of viruses becomes more commonplace.
Author summary
As SARS-COV-2 spreads through a community, it can mutate and generate new variants. How likely this is to occur and how much a particular viral clone expands, can indicate mutational probabilities and whether some mutations are fitter than others. By better understanding these aspects, future predictions can more accurately encapsulate possible changes in the epidemic within a community. We have developed a new method for piecing together the individual SARS-COV-2 cases that have been sequenced, to generate the structure of transmissions and mutational clones for an outbreak. While this method can be applied to other virus epidemics given sufficient sequenced data, we apply it to Delta and Omicron outbreaks in Australia. Interestingly, transmissions between individuals frequently do not result in mutations, with some clones growing very large. We characterise the probability that a mutation will occur, and track how these changes lead to sequential mutations in these outbreaks.
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SciScore for 10.1101/2022.05.30.22275787: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources All computations were performed with Matlab R2021b (The Mathworks Inc., Natick MA, USA). Matlabsuggested: (MATLAB, RRID:SCR_001622)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:There are many limitations in these calculations, in particular the uncertainties of many nt in the sequences. The Omicron sequences contained more uncertain nt than Delta which made estimation of the ORF domains particularly difficult for many of the groups, resulting in approximations in …
SciScore for 10.1101/2022.05.30.22275787: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources All computations were performed with Matlab R2021b (The Mathworks Inc., Natick MA, USA). Matlabsuggested: (MATLAB, RRID:SCR_001622)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:There are many limitations in these calculations, in particular the uncertainties of many nt in the sequences. The Omicron sequences contained more uncertain nt than Delta which made estimation of the ORF domains particularly difficult for many of the groups, resulting in approximations in distances between sequences (and clones), and the inability to assess some of the mutational pathways over all ORF (S2 Fig). The Omicron sequences were only collected in some states for individuals whose treatment was dependent on knowledge of the variant, so the networks and resulting mutation rate estimates would have been impacted. However, to the best of our knowledge, this is the first method to provide a population level transmission network for any virus based solely on data, something that has only been possible due to the huge investment in viral sequencing throughout the COVID-19 pandemic. Contact tracing efforts have limited scalability in large outbreaks, while viral sequencing efforts are becoming more popular and more rapid. By using the method developed here, it may be possible to complement traditional contact tracing efforts for not only this virus, but for any infectious diseases where sequencing can be used to link cases. In conclusion, we provide a data driven model of SARS-CoV-2 transmission networks. We observed relatively high mutation and recombination, highlighting the need for ongoing vigilance and research into future escape variants. Further, the model itself may...
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