Designing Drone Delivery Networks for Vaccine Supply Chain: A Case Study of Niger

TL;DR

This paper evaluates drone delivery networks for vaccines in remote Niger, proposing a mixed integer linear program to optimize hub locations, resulting in significant improvements in vaccine availability under budget constraints.

Contribution

It introduces a novel optimization model for drone hub placement tailored to vaccine delivery in low-resource settings, considering operational constraints and cold chain requirements.

Findings

Vaccine availability increased by 0.71 to 2.21 times.

Model adapts to budget and population density constraints.

Demonstrates potential of drones to improve healthcare access.

Abstract

The focus of this research is to evaluate the use of drones for the delivery of pediatric vaccines in remote areas of low income and low and middle income countries. Delivering vaccines in these regions is challenging because of the inadequate road networks, and long transportation distances that make it difficult to maintain the cold chain integrity during transportation. We propose a mixed integer linear program to determine the location of drone hubs to facilitate the delivery of vaccines. The model considers the operational attributes of drones, vaccine wastage in the supply chain, cold storage and transportation capacities. We develop a case study using data from Niger to determine the impact of drone deliveries in improving vaccine availability in Niger. Our numerical analysis show an 0.71 to 2.21 increase in vaccine availability. These improvements depend on the available budget to build drone hubs and purchase drones, and the population density in the region of study.