Multi-scale modelling reveals that early super-spreader events are a likely contributor to novel variant predominance
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Abstract
The emergence of new SARS-CoV-2 variants of concern (VOC) has hampered international efforts to contain the COVID-19 pandemic. VOCs have been characterized to varying degrees by higher transmissibility, worse infection outcomes and evasion of vaccine and infection-induced immunologic memory. VOCs are hypothesized to have originated from animal reservoirs, communities in regions with low surveillance and/or single individuals with poor immunologic control of the virus. Yet, the factors dictating which variants ultimately predominate remain incompletely characterized. Here we present a multi-scale model of SARS-CoV-2 dynamics that describes population spread through individuals whose viral loads and numbers of contacts (drawn from an over-dispersed distribution) are both time-varying. This framework allows us to explore how super-spreader events (SSE) (defined as greater than five secondary infections per day) contribute to variant emergence. We find stochasticity remains a powerful determinant of predominance. Variants that predominate are more likely to be associated with higher infectiousness, an SSE early after variant emergence and ongoing decline of the current dominant variant. Additionally, our simulations reveal that most new highly infectious variants that infect one or a few individuals do not achieve permanence in the population. Consequently, interventions that reduce super-spreading may delay or mitigate emergence of VOCs.
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SciScore for 10.1101/2021.03.23.21254185: (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
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our model has important limitations. While the model’s qualitative findings are robust, we cannot estimate the outbreak size necessary to ensure introduction of new variants into a population as many parameters required to do so are unknown. For instance, it is not yet clear whether the percentage of immunocompromised hosts varies across …
SciScore for 10.1101/2021.03.23.21254185: (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
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our model has important limitations. While the model’s qualitative findings are robust, we cannot estimate the outbreak size necessary to ensure introduction of new variants into a population as many parameters required to do so are unknown. For instance, it is not yet clear whether the percentage of immunocompromised hosts varies across populations based on factors such as HIV prevalence and availability and use of immunosuppression for organ transplantation and cancer treatment. The number of secondary infections created by a person with new variants may also differ from that of other members of the population in ways that are difficult to project. On the one hand, these individuals may shed for longer and at a higher viral load (5, 7). Yet, they also may be more ill and therefore quarantined at home or in the hospital limiting contact exposures. Moreover, while all variants will be impacted in the same way by the introduction of NPIs such as masking and physical distancing, the utilization of these interventions varies considerably among regions and over time. Our model does not capture these nuances and in this sense is intended to be phenomenological only. We demonstrate that new variants are frequently created and introduced into the population during large waves of SARS-CoV-2 infection. Yet, most variants ultimately burn out and those that ultimately predominate likely were associated with early super-spreader events. These variants are most likely to emerge when the p...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
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