Implementation study demonstrates accelerated adoption of forecasting best practices across pilot countries, suggesting improved vaccine supply security and stockout prevention.
Purpose Before 2023, detailed guidance and tools to support end-to-end strengthening of forecasting and supply planning (FSP) for vaccines and immunization supplies were lacking. This gap can undermine planning for national needs, increasing the risk of stockouts and death from vaccine-preventable diseases. In response, United Nations Children's Fund (UNICEF) developed and operationalized an immunization FSP toolbox (IFSPT). This paper aims to present a practice-based perspective on the development and operationalization of the IFSPT, its application in FSP strengthening, findings from pilot countries, key lessons learned and ongoing implementation efforts. Design/methodology/approach The development of the toolbox followed a four-phase process. First, an assessment was conducted to inform its content and structure. Second, strategy development and literature review were undertaken to ensure alignment with global best practices. Third, guidance materials and tools were created and refined with input from stakeholders. Finally, feedback was incorporated before publication, and the toolbox was promoted through multiple platforms. The toolbox was also pilot-tested in selected countries. Findings The IFSPT, comprising relevant and adaptable tools and guidance, was developed to strengthen immunization FSP. Feedback from three countries indicated that the resources could accelerate the adoption of immunization FSP best practices. Practical implications Countries can leverage the comprehensive resources of the IFSPT to improve forecast accuracy and the effectiveness of supply plans. The insights presented can also be applied to address other public health challenges, including the development of global goods. Originality/value The IFSPT is the first freely available, end-to-end IFSPT to consolidate guidance, tools and resources into a single operational package.
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Itiola et al. (2026) studied this question.
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