Preliminary modeling estimates of the relative transmissibility and immune escape of the Omicron SARS-CoV-2 variant of concern in South Africa
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Abstract
We develop a stochastic, multi-strain, compartmental epidemic model to estimate the relative transmissibility and immune escape of the Omicron variant of concern (VOC) in South Africa. The model integrates population, non-pharmaceutical interventions, vaccines, and epidemiological data and it is calibrated in the period May 1 st , 2021 – November 23 rd , 2021. We explore a parameter space of relative transmissibility with respect to the Delta variant and immune escape for Omicron by assuming an initial seeding, from unknown origin, in the first week of October 2021. We identify a region of the parameter space where combinations of relative transmissibility and immune escape are compatible with the growth of the epidemic wave. We also find that changes in the generation time associated with Omicron infections strongly affect the results concerning its relative transmissibility. The presented results are informed by current knowledge of Omicron and subject to changes.
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SciScore for 10.1101/2022.01.04.22268721: (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 Modeling of mitigation policies: We quantify the time varying variation in contacts due to mitigation policies by using Google mobility reports [29]. Googlesuggested: (Google, RRID:SCR_017097)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:It is important to acknowledge the limitations of our approach. The compartmental structure adopted is relatively simple and does not …
SciScore for 10.1101/2022.01.04.22268721: (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 Modeling of mitigation policies: We quantify the time varying variation in contacts due to mitigation policies by using Google mobility reports [29]. Googlesuggested: (Google, RRID:SCR_017097)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:It is important to acknowledge the limitations of our approach. The compartmental structure adopted is relatively simple and does not account explicitly for asymptomatic transmission, and different degrees of severity (i.e., hospitalizations and ICUs). While our model accounts for the COVID-19 vaccine rollout, we have access to limited information about the exact number of different vaccines (i.e., AstraZeneca, J&J, Pfizer, Moderna) administered. For simplicity we assume a two doses regiment across the board. We set several parameters driving the natural history of the disease using estimates from previous SARS-CoV-2 variants. The large number of mutations and divergence of Omicron could affect some of these values. We model immune escape from previous infections and vaccines with a single parameter. Finally, our model does not consider geographical heterogeneity. Our results confirm that more data is necessary to estimate the key characteristics of the Omicron VOC. Nevertheless, region of values (capturing its relative transmissibility with respect to Delta and its potential for immune escape) compatible with current observations confirms the likelihood for the Omicron variant of igniting new pandemic waves in regions with high attack rates from previous strains and/or vaccination rates. Data about the severity of Omicron with respect to Delta and the ancestral SARS-CoV-2 viruses are going to be crucial in assessing the impact of on the health-care system of countries affect...
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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- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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