2024 AIChE Annual Meeting

(735bl) Optimizing Vaccine Distribution Using Attainable Region Theory

The emergence of COVID-19 presented a unique global challenge, with a race to develop vaccines and distribute them rapidly and equitably. A range of vaccines were developed at an unprecedented pace, but bottlenecks of manufacturing and distribution obstructed their optimal use in the global context. The experiences of COVID-19 clearly show that to be prepared for future pandemics, methods are needed to select optimal vaccine strategies within the constraints of manufacturing capacity and cost so that supply chains can be developed to support this.

Attainable Region Theory, a field of mathematics developed initially for the design and optimization of chemical reactor networks, provides a systematic framework for this task, providing the ability to visualize different vaccination strategies, both homologous and heterologous, and combinations of those strategies. In the same way that Attainable Region Theory allows a reactor designer to map the hyper-volume of possible process outputs into a two-dimensional space of Enthalpy and Gibbs Free Energy of reaction, it also offers a means of mapping the hyper-volume of all feasible vaccination strategies into a two-dimensional space of total preventive efficacy and cost, within the constraints of available manufacturing capacity.

We demonstrate that this approach allows for rapid comparisons of vast sets of possible strategies at both local and global scales and allows for the projection of those strategies over multiple time scales. This approach allows for rapid optimization for utilizing all available resources, showcasing the potential of Attainable Region Theory to inform data-driven, cost-effective, and adaptable vaccine distribution strategies. By optimizing the deployment of vaccines, including heterologous approaches, we can develop supply chains that support global vaccination, ultimately enhancing public health outcomes.