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Reviews of "Optimal SARS-CoV-2 vaccine allocation using real-time seroprevalence estimates in Rhode Island and Massachusetts"

Reviewers: Daniel Larremore (University of Colorado Boulder) | 📘📘📘📘📘 • François Castonguay (University of California Davis) | 📗📗📗📗◻️

Published onMar 01, 2021
Reviews of "Optimal SARS-CoV-2 vaccine allocation using real-time seroprevalence estimates in Rhode Island and Massachusetts"
key-enterThis Pub is a Review of
Optimal SARS-CoV-2 vaccine allocation using real-time seroprevalence estimates in Rhode Island and Massachusetts

AbstractAs three SARS-CoV-2 vaccines come to market in Europe and North America in the winter of 2020-2021, distribution networks will be in a race against a major epidemiological wave of SARS-CoV-2 that began in autumn 2020. Rapid and optimized vaccine allocation is critical during this time. With 95% efficacy reported for two of the vaccines, near-term public health needs require that distribution is prioritized to the elderly, health-care workers, teachers, essential workers, and individuals with co-morbidities putting them at risk of severe clinical progression. Here, we evaluate various age-based vaccine distributions using a validated mathematical model based on current epidemic trends in Rhode Island and Massachusetts. We allow for varying waning efficacy of vaccine-induced immunity, as this has not yet been measured. We account for the fact that known COVID-positive cases may not be included in the first round of vaccination. And, we account for current age-specific immune patterns in both states. We find that allocating a substantial proportion (> 75%) of vaccine supply to individuals over the age of 70 is optimal in terms of reducing total cumulative deaths through mid-2021. As we do not explicitly model other high mortality groups, this result on vaccine allocation applies to all groups at high risk of mortality if infected. Our analysis confirms that for an easily transmissible respiratory virus, allocating a large majority of vaccinations to groups with the highest mortality risk is optimal. Our analysis assumes that health systems during winter 2020-2021 have equal staffing and capacity to previous phases of the SARS-CoV-2 epidemic; we do not consider the effects of understaffed hospitals or unvaccinated medical staff. Vaccinating only seronegative individuals avoids redundancy in vaccine use on individuals that may already be immune, and will result in 1% to 2% reductions in cumulative hospitalizations and deaths by mid-2021. Assuming high vaccination coverage (> 28%) and no major relaxations in distancing, masking, gathering size, or hygiene guidelines between now and spring 2021, our model predicts that a combination of vaccination and population immunity will lead to low or near-zero transmission levels by the second quarter of 2021.

To read the original manuscript, click the link above.

Summary of Reviews: This preprint offers a model for directing vaccine allocation using seroprevalence data obtain from Rhode Island and Massachusetts. Reviewers recommend clarifying some model assumptions, but find the work well-crafted and significant in its contribution.

Reviewer 1 (Daniel Larremore) | 📘📘📘📘📘

Reviewer 2 (François Castonguay) | 📗📗📗📗◻️

RR:C19 Strength of Evidence Scale Key

📕 ◻️◻️◻️◻️ = Misleading

📙📙 ◻️◻️◻️ = Not Informative

📒📒📒 ◻️◻️ = Potentially Informative

📗📗📗📗◻️ = Reliable

📘📘📘📘📘 = Strong

To read the reviews, click the links below.

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Andree oren:

I was blown away by the quality of this shell shockers article! The topic is not only relevant but also highly intriguing. The author's unique perspective and innovative approach bring a fresh take to the subject matter.

Henny Smath:

We used a mathematical model to optimize the allocation of SARS-CoV-2 vaccines in Rhode Island and Massachusetts based on real-time seroprevalence estimates. The model takes into account the population wordle size, the number of contexto vaccinated individuals, the number of individuals with natural immunity, and the number of susceptible individuals