The perfect COVID-19 vaccination strategy

Who should get the COVID-19 vaccine first? Since I am an economist, let’s try to figure this out mathematically. Let’s give each person or group of people a score or ranking and vaccinate each individual in priority.

One key factor, is that we should the vaccine to the people most at risk for the disease. In this case, our ranking (R) is just a function of people’s mortality risk conditional on getting COVID-19. Older individuals and those in nursing homes are at much higher risk. Thus, we should vaccinate based on how likely people are to die if they get COVID

R = f[mortality]

However, fairness is also important. Front line health care workers are putting their lives on the line to treat patients with COVID and should also be prioritized. Let’s make sure that fairness considerations are included. I’ll update our prioritization as follows: where both mortality and fairness matter. Of course we’ll have to weigh these priorities, but we can worry about that later. The relative weighting coefficient’s I’ll include with the vector θ.

R = f[mortality, fairness; θ]
Getting back to mortality, previously, we (implicitly) noted that older people are at higher risk of dying if they get COVID. But so are younger people such as those with comoribidities such as asthma or COPD. Thus, let’s be a bit more specific on the factors that affect mortality.

R = f[mortality(age, nursing home, comorbidities),fairness; θ]

We focus on the risk of people dying conditional on getting COVID-19. In practice, however, the chance of getting COVID-19 may depend on individual behavior. Older people may be more cautious and less likely to leave the house or travel than younger individuals., especially if they are retired and do not need to work As younger individuals have less health risk and will need to work as they have less savings, they may be more likely to engage in risky behaviors and spread COVID-19. Thus, we’ll want to focus on likelihood of getting COVID-19 or the cost of staying at home. We will update the scoring to incorporate COVID-19 incidence and cost of isolation as follows:

R = f[mortality(age, nursing home, comorbidities), fairness,incidence,cost of isolation; θ]

Now we’re getting closer. However, the vaccinating people in rural areas may be more challenging than those in urban areas. Those in urban areas come into contact with more people and are more likely to spread the disease. Let’s add that dimension to our ranking formula.

R = f[mortality(age, nursing home, comorbidities), fairness,incidence,cost of isolation, urban; θ]

Now we have the perfect system…once we figure out θ.

But wait! The cost of figuring out each individuals risk score will require an army of statisticians at each vaccination site or at a minimum a data entry team that can feed each individual’s characteristics into a computers algorithm to calculate each person’s priority score.

Hmmm, this is becoming become problematic. In fact, California experienced problems with vaccination due to their complex tiering structure. Perhaps our focus on prioritization is missing the point: let’s get people vaccinated fast! Maybe the Israeli approach of vaccinating everyone 65 and older first, and then everyone else is the right way to go. Perhaps we should follow Voltaire’s advice:

Dans ses écrits, un sage Italien
Dit que le mieux est l’ennemi du bien.
[In his writings, a wise Italian
says that the best is the enemy of the good]

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