Vaccine optimization for COVID-19: who to vaccinate first?

Abstract

A vaccine, when available, will likely become our best tool to control the current COVID-19 pandemic. Even in the most optimistic scenarios, vaccine shortages will likely occur. Using an age-stratified mathematical model paired with optimization algorithms, we determined optimal vaccine allocation for four different metrics (deaths, symptomatic infections, and maximum non-ICU and ICU hospitalizations) under many scenarios. We find that a vaccine with effectiveness ≥50% would be enough to substantially mitigate the ongoing pandemic provided that a high percentage of the population is optimally vaccinated. When minimizing deaths, we find that for low vaccine effectiveness, irrespective of vaccination coverage, it is optimal to allocate vaccine to high-risk (older) age-groups first. In contrast, for higher vaccine effectiveness, there is a switch to allocate vaccine to high-transmission (younger) age-groups first for high vaccination coverage. While there are other societal and ethical considerations, this work can provide an evidence-based rationale for vaccine prioritization.

Figure 1:. Simulated prevalence of symptomatic COVID-19 infections for VE ranging from 10% (A) to 100% (J) in 10% increments.

For each VE and each vaccination coverage, the optimal vaccine allocation for minimizing symptomatic infections was used in these simulations. Colors represent different vaccination coverage, ranging from 0 (black, “baseline”) to 100% (magenta). For clarity, we present here epidemic curves for the main set of parameters only and show a complete figure with uncertainty bounds in Fig. S2.

Figure 2:. Four key metrics of COVID-19 burden under optimal distribution of vaccine.

Percentage of symptomatic infections (A) and deaths (B) averted, number of maximum non-ICU (C) and ICU (D) hospitalizations as a function of VE and vaccination coverage (total vaccine available as a percentage of the population). The dotted lines correspond to VE = 50% and vaccine available to cover 50% of the population. The isoclines indicate the current goal for WA state of having 10% of licensed general (non-ICU) hospital beds occupied by COVID-19 patients in (C) and total ICU licensed hospital beds in WA state in (D).

Figure 3:. Percentage of deaths averted for the optimal allocation strategy (blue) and the pro-rata strategy (green) for VE ranging from 10% (A) to 100% (J) in 10% increments and vaccination coverage ranging from 10% to 100% of the total population.

The shaded areas represent results of 1,000 simulations with the top and bottom 2.5% simulations removed.

Figure 4:. Optimal allocation strategies for minimizing deaths for VE ranging from 10% (A) to 100% (J) in 10% increments (additional figures for minimizing symptomatic infections, number of non-ICU hospitalizations at peak and number of ICU hospitalizations at peak are given in SM).

For each plot, each row represents the total vaccination coverage available (percentage of the total population to be vaccinated) and each column represents a different vaccination group. Colors represent the percentage of the population in a given vaccination group to be vaccinated.

Figure 5:. Optimal allocation strategies for minimizing: symptomatic infections (A), Number of non-ICU hospitalizations at peak (B), Number of ICU hospitalizations at peak (C) and total number of deaths (D). Here, we assumed VE = 60%.

For each plot, each row represents the total vaccination coverage available (percentage of the total population to be vaccinated) and each column represents a different vaccination group. Colors represent the percentage of the population in a given vaccination group to be vaccinated.

Figure 6:. Optimal allocation strategies for minimizing total symptomatic infections for VE ranging from 10% (A) to 60% (F) in 10% increments for VE_COV = 60%.

For each plot, each row represents the total vaccination coverage available (percentage of the total population to be vaccinated) and each column represents a different vaccination group. Colors represent the percentage of the population in a given vaccination group to be vaccinated.

Figure 7:. Three key metrics of COVID-19 burden under optimal distribution of vaccine for VE_COV = 60%.

Percentage of symptomatic infections averted (A), number of maximum non-ICU (C) and ICU (D) hospitalizations as a function of VE and vaccination coverage (total vaccine available as a percentage of the population). The dotted lines correspond to VE = 50% and vaccine available to cover 50% of the population. The isoclines indicate the current goal for WA state of having 10% of licensed general (non-ICU) hospital beds occupied by COVID-19 patients in (C) and total ICU licensed hospital beds in WA state in (D).

Figure 8:. Optimal allocation strategies for minimizing deaths assuming 10% (A), 20%(B) 30% (C) and 40% (D) of the population has natural immunity to COVID-19 at the start of the simulations.

Here, we assumed VE = 60%. For each plot, each row represents the total vaccination coverage available (percentage of the total population to be vaccinated) and each column represents a different vaccination group. Colors represent the percentage of the population in a given vaccination group to be vaccinated.

Figure 9:. Optimal allocation strategies for minimizing deaths for two VE = 50% (A-C) and VE = 90% (D-F) and for three different vaccination rates: 75K (A and D), 150 (B and E) and 300 (C and F) thousand vaccine doses administered per week.

For each plot, each row represents the total vaccination coverage available (percentage of the total population to be vaccinated) and each column represents a different vaccination group. Colors represent the percentage of the population in a given vaccination group to be vaccinated.

Figure 10:. Optimal allocation strategies for minimizing deaths for three different VE: 30% (A-C), 60%(D-F) and 90% (G-I) for three different values of R₀ = 1.5, 2, and 2.5 (additional figures for minimizing symptomatic infections, number of non-ICU hospitalizations at peak and number of ICU hospitalizations at peak are given in SM).

For each plot, each row represents the total vaccination coverage available (percentage of the total population to be vaccinated) and each column represents a different vaccination group. Colors represent the percentage of the population in a given vaccination group to be vaccinated.