Opinion: CDC has 17.5 million ways to deploy a COVID-19 vaccine – practical strategy ‘works exceptionally well’

Centers for Disease Control and Prevention’s plan for who gets vaccinated and in what order Almost as many lives have been saved and nearly as many infections have been prevented is a theoretically perfect rollout, following a new mathematical model we developed to evaluate COVID-19 product rollout in the United States

In December 2020, with a limited number of vaccines, the CDC had to make a difficult decision: Who should receive the COVID-19 vaccine first? It decides divide the US population into four groups to prioritize vaccines based on age, occupation, living conditions, and known COVID-19 risk factors.

Using a new model and an Iowa State University supercomputer, we compared CDC recommendations in the real world with 17.5 million possible strategies. To calculate how well the vaccine allocation strategy worked, our model measured total deaths, cases, infections, and life years lost.

We’ve found that the CDC attribution strategy works exceptionally well – within 4% of perfect – in all four measures.

According to our model, CDC Decisions not giving primary immunizations to children and prioritizing healthcare and other essential workers over non-essential workers are both right. But our model also shows that giving people with known risk factors early access to the vaccine leads to slightly better outcomes.

No implementation can simultaneously reduce deaths, cases, infections, and life years lost. For example, a strategy of minimizing deaths leads to a higher number of cases. Given these limitations, the CDC plan does a good job of balancing the four goals of immunization and is particularly good at reducing deaths.

Why is it important?

Many other studies looked at a small number of alternative COVID-19 vaccine rollouts. Our project combines more features of the current pandemic and considers 17.5 million possible strategies. We believe this gives our results more authority.

Our models include differences in disease severity and susceptibility for coronavirus due to age. It also incorporates time-varying levels of social distancing as well as infection rate change to account for more contagious virus strains such as the delta variant.

All of this has given us the ability to accurately assess past decisions by CDC. But the greater value of our modeling approach lies in how it can help guide future policy.

By varying the input of the model, we can show how the optimal implementation strategies will change with the vaccine hesitancy rate and for different possible vaccines protect in different ways against infection or death.

For countries currently planning a COVID-19 vaccination strategy, our model can help decision-makers develop the most effective strategies based on their local resources and specifics. And even in the United States, our modeling technique can inform future vaccine deployment and booster allocation strategies so that healthcare administrators can use it. make the best use of limited resources.

What is still unknown?

Any model is a simplification of reality. Our model does not account for reinfection or different degrees of vaccine hesitancy based on socioeconomic status, political ideology, or race. We also assume that the degree of hesitation is constant over time.

In addition, several factors are important to how the coronavirus spreads – like contact rates between individuals of different ages and demographic groups and the spread of asymptomatic and vaccinated individuals – remain unknown. Better data on these parameters will improve the accuracy of our results.

What’s next?

Now that we have built the model, we can extend it. For example, we can study how Impaired immunity and booster shots can affect the spread of the disease. Our computer code is available to the public, and we hope it will guide healthcare policymakers in the United States and around the world.

Audrey L. McCombs is Dr. candidate in ecology and statistics at Iowa State University in Ames, Iowa. Claus Kadelka is an assistant professor of mathematics at Iowa State University. This was first published by Conversation – “U.S. vaccine deployment is near-optimal in reducing deaths and infections, according to a model comparing 17.5 million alternative approaches.“.

https://www.marketwatch.com/story/the-cdc-had-17-5-million-ways-to-roll-out-the-covid-19-vaccine-the-actual-strategy-performed-exceptionally-well-11637256823?rss=1&siteid=rss Opinion: CDC has 17.5 million ways to deploy a COVID-19 vaccine – practical strategy ‘works exceptionally well’


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