Resilient Humanitarian Supply Chain: A Simulation Study of COVID-19 Vaccine Logistics in Kenya
ABSTRACT
The study explores the existing distribution network (As Is model) and proposes two alternative configurations (To Be models) based on global health organizations’ guidelines. The simulation utilizes actual data from Kenya’s COVID-19 vaccination campaign and the national vaccine distribution network.
The context of the study is Kenya, a low-middle income country in East Africa, divided into 47 counties. The As Is model reflects the current vaccine distribution structure, involving vaccine production factories, a national depot in Kitengela, regional depots, and hospitals. To Be scenarios consider variations in the number and positioning of central depots, focusing on proximity or centralization. The simulation assesses key performance indicators, including demand coverage, flexibility of depots, fleet utilization, and fulfillment time.
The study aims to enhance the efficiency and effectiveness of the humanitarian supply chain, emphasizing fair and rapid vaccine access. The To Be 2 scenario, featuring a centralized distribution with increased transport strength, outperforms others, achieving a higher service level (99.7%) and reducing vaccine inventory in the network. This is facilitated by innovations such as aerial drones for remote deliveries, which prove effective in mitigating uncertainties in transport times.
Results highlight the sensitivity of the As Is and To Be 1 scenarios to variations in system parameters, emphasizing the need for a robust supply chain configuration. The study underscores the importance of simulation models in testing proposed improvements, complementing analytical optimization methods. The research contributes to the exploration of alternative distribution network designs in humanitarian contexts and underscores the necessity for further modeling and analysis to enhance the resilience and efficiency of vaccine distribution systems
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