Original title: A bi-objective MILP model for pandemic vaccine allocation and distribution with behavioral adaptation
The researchers build a planning tool for sending different vaccines to regions over time. It chooses routes and allocations while accounting for cold storage, vehicle limits and upkeep, and spoilage. It also adjusts the vaccination rate based on earlier public acceptance trends. The tool compares plans by delivery cost and disease-related deaths, and examines how the tradeoffs change with transport capacity and disease spread.
Imagine packing lunches for several schools while using a limited number of delivery vans. Some foods need to stay cold, and each trip takes time, so a route that works for one school may not work for another. In this paper, the lunches stand for vaccines, the vans and routes stand for delivery resources, and changing demand stands for public acceptance shifting the vaccination rate.
Health ministries and humanitarian planners must get vaccines to people while dealing with limited vehicles, storage needs, and changing public acceptance. This model helps compare plans that trade delivery cost against deaths and equity, under stated assumptions.
The results are illustrated with a scenario inspired by Iran’s COVID-19 vaccination campaign, not evidence that the framework will work equally well in every setting. The tradeoffs depend on the modeled epidemiological and behavioral assumptions. The abstract does not report specific numerical results or establish real-world effects.
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A bi-objective MILP model for pandemic vaccine allocation and distribution with behavioral adaptation — Sara Aryaee, Nathan Kunz, Mahnaz Hosseinzadeh et al. — Journal of Humanitarian Logistics and Supply Chain Management — doi:10.1108/jhlscm-11-2025-0229
Abstract licence: CC BY
Explanation generated by Synthesis from the abstract — it is not the original paper.