Mathematical Modeling of Vaccines That Prevent SARS-CoV-2 Transmission
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Abstract
SARS-CoV-2 vaccine clinical trials assess efficacy against disease (VEDIS), the ability to block symptomatic COVID-19. They only partially discriminate whether VEDIS is mediated by preventing infection completely, which is defined as detection of virus in the airways (VESUSC), or by preventing symptoms despite infection (VESYMP). Vaccine efficacy against transmissibility given infection (VEINF), the decrease in secondary transmissions from infected vaccine recipients, is also not measured. Using mathematical modeling of data from King County Washington, we demonstrate that if the Moderna (mRNA-1273QS) and Pfizer-BioNTech (BNT162b2) vaccines, which demonstrated VEDIS > 90% in clinical trials, mediate VEDIS by VESUSC, then a limited fourth epidemic wave of infections with the highly infectious B.1.1.7 variant would have been predicted in spring 2021 assuming rapid vaccine roll out. If high VEDIS is explained by VESYMP, then high VEINF would have also been necessary to limit the extent of this fourth wave. Vaccines which completely protect against infection or secondary transmission also substantially lower the number of people who must be vaccinated before the herd immunity threshold is reached. The limited extent of the fourth wave suggests that the vaccines have either high VESUSC or both high VESYMP and high VEINF against B.1.1.7. Finally, using a separate intra-host mathematical model of viral kinetics, we demonstrate that a 0.6 log vaccine-mediated reduction in average peak viral load might be sufficient to achieve 50% VEINF, which suggests that human challenge studies with a relatively low number of infected participants could be employed to estimate all three vaccine efficacy metrics.
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SciScore for 10.1101/2020.12.13.20248120: (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 approach has limitations. We combine several scales of models which reflect population conditions unique to King County Washington and virologic findings from across the globe. The models are not equipped to make precise vaccine schedule assessments for different locations and are not meant as predictions. Rather, we intend to make …
SciScore for 10.1101/2020.12.13.20248120: (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 approach has limitations. We combine several scales of models which reflect population conditions unique to King County Washington and virologic findings from across the globe. The models are not equipped to make precise vaccine schedule assessments for different locations and are not meant as predictions. Rather, we intend to make the conclusion that VEINF could theoretically provide substantial population level benefits and to provide a framework for most rapid evaluation of this metric. The scope of the ongoing third wave is difficult to forecast and will depend on changes in human behavior over the next several weeks. The number of cases and deaths during a possible fourth spring wave may be somewhat dependent on current events. In conclusion, in the situation where observed high VEDIS is predominately due to reduction in symptoms rather than absolute protection against infection, VEINF will be vital to measure as it may determine whether a severe fourth wave of cases and deaths is imminent in the spring. Using peak viral load as a proxy measure in human challenge studies is an efficient way to complement other clinical trial designs to assess VEINF.
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.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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