When it comes to slowing the spread of COVID-19, one key is figuring out the best way to prioritize and allocate the vaccine. 

But how?

That’s the question researchers affiliated with California-based Kaiser Permanente asked for a recent study, the findings of which have been published at JAMA Network.

For the study, the team simulated the association of different risk-based, age-based and CDC-phased vaccine allocation strategies with COVID-19–associated morbidity and mortality factors across a range of across racial and ethnic groups.

“Using data from a large, diverse, and integrated health care delivery system, we simulated the implementation of different COVID-19 vaccine allocation strategies and compared their association with estimates of vaccine allocation effectiveness and equity,” the team wrote. “We found that risk-based strategies that identified patients at high risk for adverse outcomes were associated with the highest estimates of avoidable hospital admissions and deaths, followed by the CDC proxy and age-based strategies. We also found that a risk-based approach that identified patients at high risk for COVID-19 infection, followed by the CDC proxy strategy, achieved the goal of earlier vaccinations being administered to Hispanic and Black patients.”

Specifically, the researchers identified 3,202,679 adult patients who tested positive for COVID-19 between February 1, 2020, and December 3, 2020. They studied transmission and death rates of COVID-19, but they also examined the vaccination rate among four broad racial and ethnic groups; White, Black, Hispanic, and Asian.

The study created six simulated vaccine strategies with a targeted goal of vaccinating 75 percent of KPNC members in eight months. “To estimate the association between allocation strategies and outcomes,” they wrote, “we conducted 250 simulations in which we permuted the month of COVID-19–related hospitalization month to simulate random monthly outcome distributions over the vaccination period. We assumed that any vaccination would be 100% effective at preventing hospitalization; thus, we removed hospitalizations that occurred at any time after 1 month from the vaccination date. In each simulation, we calculated the difference between the actual and simulated number of hospitalizations to estimate the number of avoided hospitalizations.”

In the end, the risk-based strategies showed the largest estimated reductions in nonelective hospitalizations, deaths, and household transmission. By creating COVID-19 risk scores, the researchers determined higher-risk patients and simulated their early vaccination.

“The major strength of this study,” the team concluded, “was the ability to find an association between detailed population-level data with SARS-CoV-2 test results and COVID-19 hospital admissions, deaths, and household transmission through facilitating the use of 2 risk models and simulating key outcomes. The study also quantifies the effectiveness and equity of these approaches in a large and diverse patient population.”

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