Mueller Leslie E, Haidari Leila A, Wateska Angela R, Phillips Roslyn J, Schmitz Michelle M, Connor Diana L, Norman Bryan A, Brown Shawn T, Welling Joel S, Lee Bruce Y
Public Health Computational and Operations Research (PHICOR), Pittsburgh, PA, USA (formerly) and Baltimore, MD, USA (currently); Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Public Health Computational and Operations Research (PHICOR), Pittsburgh, PA, USA (formerly) and Baltimore, MD, USA (currently); Pittsburgh Supercomputing Center (PSC), Pittsburgh, PA, USA.
Vaccine. 2016 Jul 12;34(32):3663-9. doi: 10.1016/j.vaccine.2016.05.027. Epub 2016 May 21.
To evaluate the potential impact and value of applications (e.g. adjusting ordering levels, storage capacity, transportation capacity, distribution frequency) of data from demand forecasting systems implemented in a lower-income country's vaccine supply chain with different levels of population change to urban areas.
Using our software, HERMES, we generated a detailed discrete event simulation model of Niger's entire vaccine supply chain, including every refrigerator, freezer, transport, personnel, vaccine, cost, and location. We represented the introduction of a demand forecasting system to adjust vaccine ordering that could be implemented with increasing delivery frequencies and/or additions of cold chain equipment (storage and/or transportation) across the supply chain during varying degrees of population movement.
Implementing demand forecasting system with increased storage and transport frequency increased the number of successfully administered vaccine doses and lowered the logistics cost per dose up to 34%. Implementing demand forecasting system without storage/transport increases actually decreased vaccine availability in certain circumstances.
The potential maximum gains of a demand forecasting system may only be realized if the system is implemented to both augment the supply chain cold storage and transportation. Implementation may have some impact but, in certain circumstances, may hurt delivery. Therefore, implementation of demand forecasting systems with additional storage and transport may be the better approach. Significant decreases in the logistics cost per dose with more administered vaccines support investment in these forecasting systems.
Demand forecasting systems have the potential to greatly improve vaccine demand fulfilment, and decrease logistics cost/dose when implemented with storage and transportation increases. Simulation modeling can demonstrate the potential health and economic benefits of supply chain improvements.
评估在低收入国家疫苗供应链中实施的需求预测系统的应用(如调整订购水平、储存能力、运输能力、配送频率)对不同程度人口向城市地区迁移的潜在影响和价值。
我们使用HERMES软件生成了尼日尔整个疫苗供应链的详细离散事件模拟模型,包括每台冰箱、冰柜、运输工具、人员、疫苗、成本和地点。我们模拟了引入需求预测系统以调整疫苗订购的情况,该系统可在不同程度的人口流动期间,通过增加供应链中的配送频率和/或增加冷链设备(储存和/或运输)来实施。
实施增加储存和运输频率的需求预测系统,成功接种的疫苗剂量数量增加,每剂疫苗的物流成本降低了34%。在某些情况下,实施不增加储存/运输的需求预测系统实际上会降低疫苗的可及性。
只有在实施需求预测系统以增强供应链冷藏和运输能力时,才能实现该系统的潜在最大收益。实施可能会有一些影响,但在某些情况下,可能会损害配送。因此,实施增加储存和运输的需求预测系统可能是更好的方法。随着接种疫苗数量的增加,每剂疫苗的物流成本显著降低,这支持对这些预测系统进行投资。
需求预测系统有潜力极大地提高疫苗需求的满足率,并在增加储存和运输的情况下降低每剂疫苗的物流成本。模拟建模可以证明供应链改进带来的潜在健康和经济效益。