Covid19Vaxplorer: A free, online, user-friendly COVID-19 vaccine allocation comparison tool

Abstract

There are many COVID-19 vaccines currently available, however, Low- and middle-income countries (LMIC) still have large proportions of their populations unvaccinated. Decision-makers must decide how to effectively allocate available vaccines (e.g. boosters or primary series vaccination, which age groups to target) but LMIC often lack the resources to undergo quantitative analyses of vaccine allocation, resulting in ad-hoc policies. We developed Covid19Vaxplorer (https://covid19vaxplorer.fredhutch.org/), a free, user-friendly online tool that simulates region-specific COVID-19 epidemics in conjunction with vaccination with the purpose of providing public health officials worldwide with a tool for vaccine allocation planning and comparison. We developed an age-structured mathematical model of SARS-CoV-2 transmission and COVID-19 vaccination. The model considers vaccination with up to three different vaccine products, primary series and boosters. We simulated partial immunity derived from waning of natural infection and vaccination. The model is embedded in an online tool, Covid19Vaxplorer that was optimized for its ease of use. By prompting users to fill information through several windows to input local parameters (e.g. cumulative and current prevalence), epidemiological parameters (e.g basic reproduction number, current social distancing interventions), vaccine parameters (e.g. vaccine efficacy, duration of immunity) and vaccine allocation (both by age groups and by vaccination status). Covid19Vaxplorer connects the user to the mathematical model and simulates, in real time, region-specific epidemics. The tool then produces key outcomes including expected numbers of deaths, hospitalizations and cases, with the possibility of simulating several scenarios of vaccine allocation at once for a side-by-side comparison. We provide two usage examples of Covid19Vaxplorer for vaccine allocation in Haiti and Afghanistan, which had as of Spring 2023, 2% and 33% of their populations vaccinated, and show that for these particular examples, using available vaccine as primary series vaccinations prevents more deaths than using them as boosters.

Fig 1. Flow diagram of the disease progression and vaccine allocation.

Transitions between infection or disease status are depicted with black solid arrows while black dotted arrows describe waning immunity. Dashed and dotted-dashed arrows represent movement between different levels of protection (unvaccinated to vaccinated with primary series to boosted). The colored arrows represent the change in immune state with vaccination. For example, people in the unvaccinated RA compartment move to the corresponding $R{A}_{V_j}$ compartment in the primary series class. This is depicted by a dark green dashed arrow coming out of RA and going into $R{A}_{V_j}$. Similarly, compartments that move to the booster compartments are represented by dotted-dashed colored arrows. For example, people in the R_W compartment move to the corresponding boosted compartment, $R_{B_j}$ (represented by a red dotted-dashed arrow coming out of R_W and coming into $R_{B_j}$. The i-age group indices are omitted for clarity.

Fig 2. Landing page for Covid19Vaxplorer.

The user can start a new simulation, import data from their computer or load a preset example.

Fig 3. Example of the region window in Covid19Vaxplorer.

The user can select among 183 regions and they can input a value for the basic reproduction number R₀, with some values suggested.

Fig 4. Example of the infection prevalence window in Covid19Vaxplorer.

The user inputs the percentage of the population in each age group who has been previously infected (cumulative prevalence) and who is currently infected. Default values for the cumulative prevalence are given based on Barber et al. (2022) [60].

Fig 5. Example of the vaccine options window in Covid19Vaxplorer.

The user can select up to three vaccine products for their simulation, to choose among 10 pre-loaded vaccines or they can input their own vaccine. For each vaccine product, there is a corresponding vaccine effectiveness value (S2 Table).

Fig 6. Example of the vaccine allocation window in Covid19Vaxplorer.

For each vaccine given, the user is presented with two tables to allocate the available vaccine. The user indicates the percentage of available vaccine to be given as primary series and the percentage to be given as boosters. Within each table, the user then determines what percentage of vaccine will be allocated as primary series for each age group, and what percentage of vaccine will be allocated as boosters among age groups and previously vaccinated groups.

Fig 7. Covid19Vaxplorer results page for comparing two strategies in a hypothetical situation in Haiti.

Strategy 1, “boosters first” strategy, would result in 18,665 cumulative deaths at the end of the simulation period and 6860 hospitalizations at the peak. In contrast, Strategy 2, “primary series first” would result in 16,737 cumulative deaths and 6,918 hospitalizations at the peak over the same simulation period.

Fig 8. Covid19Vaxplorer results page for comparing two strategies in a hypothetical situation in Afghanistan.

Strategy 1, “boosters first” strategy, would result in 23907 cumulative deaths at the end of the simulation period and 8519 hospitalizations at the peak of the epidemic wave. In contrast, Strategy 2, “primary series first” would result in 23084 cumulative deaths and 5647 hospitalizations at the peak.