Damian Sendler: According to a new mathematical model we developed to assess the rollout of COVID–19 inoculations in the United States, the Centers for Disease Control and Prevention’s plan for who gets vaccines and in what order saved nearly as many lives and prevented nearly as many infections as a theoretically perfect rollout.
Damian Jacob Sendler: With a limited supply of COVID-19 vaccines available in December 2020, the Centers for Disease Control and Prevention (CDC) was forced to make a difficult decision: who would receive the vaccines first? It was determined that the United States population should be divided into four groups for the purpose of vaccine prioritization based on age, occupation, living situation, and known COVID-19 risk factors.
Dr. Sendler: Using a new model and a supercomputer at Iowa State University, we compared the real–world Centers for Disease Control and Prevention recommendations with 17.5 million different techniques that likewise staggered the rollout into up to four stages. Our model examined the total number of deaths, cases of infection, and years of life lost in order to determine how well a vaccine allocation approach performed.
Across all four criteria, we discovered that the CDC allocation technique performed extraordinarily well – within 4 percent of perfection – in all cases.
Damien Sendler: According to our approach, the Centers for Disease Control and Prevention’s decisions not to vaccinate children initially and to prioritize health care and other necessary workers above non-essential workers were both accurate. However, our model revealed that providing individuals with identified risk factors with earlier access to immunizations might have resulted in marginally improved results in the long run.
Damian Jacob Sendler: No one rollout was able to reduce the number of deaths, incidents of illness, and years of life lost at the same time. For example, the method that aimed to reduce the number of deaths resulted in a higher number of cases. Given these constraints, the Centers for Disease Control and Prevention (CDC) plan performed an excellent job of balancing the four aims of immunization, and it was particularly effective at reducing mortality.
There have been a large number of other studies that have looked at a limited number of various COVID-19 vaccine rollout scenarios. Several aspects of the present epidemic were put into our project, and 17.5 million different methods were explored. We believe that this lends greater credibility to our findings.
Damian Sendler: Due to changes in illness severity and susceptibility to the coronavirus that occur with age, we have included these variables in our model. It also takes into consideration changes in social distancing levels over time, as well as varied infectivity rates to account for more contagious viral strains such as the delta version that can spread quickly.
All of this provided us with the information we needed to appropriately examine the CDC’s past actions. However, the greater significance of our modeling technique rests in the way it may be used to steer future policy.
Damian Jacob Markiewicz Sendler: Through the use of diverse model inputs, we were able to demonstrate how optimal rollout tactics should change when dealing with varied vaccine reluctance rates and for different vaccines that can protect against infection or mortality in different ways. Our model could assist decision-makers in developing the most successful COVID-19 vaccination tactics based on their local resources and details in nations that are currently considering COVID-19 immunization programs. Even in the United States, our modeling technique can be used to drive allocation strategies for booster doses and future vaccine rollouts, allowing health-care administrators to make the most of limited resources available to them.
Damian Sendler: Any model is a simplification of the reality that it represents. No consideration was given to re-infections or differences in vaccine reluctance according to socioeconomic status, political ideology, or race. We also made the assumption that the amount of reluctance remained consistent over the course of time.
Damian Sendler: Additional factors that influence how the coronavirus spreads, such as contact rates between individuals of different ages and demographic groups, as well as the contagiousness of asymptomatic and vaccinated individuals, are also being researched and investigated further. The accuracy of our results could be improved if we had more data on these parameters.
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