Dynamic prioritization of COVID-19 vaccines when social distancing is limited for essential workers
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Abstract
Vaccines are a key intervention to reduce the burden of the COVID-19 pandemic. However, vaccine supply and administration capacity will initially be limited. Due to these constraints, it is critical to understand how vaccine deployment can be targeted to minimize the overall burden of disease. In this paper, we solve for optimal dynamic strategies to allocate a limited supply of vaccines over a population differentiated by age and essential worker status that minimizes the number of total deaths, years of life lost, or infections. We find that older essential workers are typically targeted first. However, depending on the objective and alternative model scenarios considered, younger essential workers may be prioritized to control spread or seniors to directly control mortality.
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SciScore for 10.1101/2020.09.22.20199174: (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: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Together these lessons show the strong implications of considering dynamic solutions, social distancing and essential workers (given their limitations in social distancing) for vaccine prioritization. Our analysis of COVID-19 vaccine prioritization uniquely accounts for two critical needs: (1) dynamic prioritization given gradual roll out of vaccine during an active pandemic, and (2) attending to significant heterogeneities in work …
SciScore for 10.1101/2020.09.22.20199174: (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: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Together these lessons show the strong implications of considering dynamic solutions, social distancing and essential workers (given their limitations in social distancing) for vaccine prioritization. Our analysis of COVID-19 vaccine prioritization uniquely accounts for two critical needs: (1) dynamic prioritization given gradual roll out of vaccine during an active pandemic, and (2) attending to significant heterogeneities in work contacts among the adult population due to the ability of many to work from home. These two novel features significantly change optimal vaccine prioritization. Given gradual vaccine deployment, static policies are out-performed by dynamic polices, which narrowly target a small number of demographic groups and (after substantial coverage of them) switch to lower priority groups. Static policies identify a set of high priority groups but not how to order them when phased deployment is necessary. More significantly, targeting essential workers (or other adults with large number of work contacts) significantly reduces not just the adverse outcome of focus but also trade offs for remaining outcomes. For example, when minimizing deaths, allocation that differentiates essential workers substantial lessens the degree to which infections and YLL climb from the minimum achieved when each is optimized on its own. Notable existing analysis of optimal COVID-19 vaccination targeting in preprint form includes Matrajt et al. (15), Bubar et al. (16) and Hogan et al...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
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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