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SARS-COV-2 Delta and Omicron community transmission networks

Murray, J.; Murray, D.; Schvoerer, E.; Akand, E.

2022-05-31 epidemiology
10.1101/2022.05.30.22275787 medRxiv
Show 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 summaryAs 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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