An Evaluation System for COVID-19 Vaccine Transportation Quality Based on Fuzzy Analytic Hierarchy Process

Abstract

COVID-19 vaccines have become pivotal in combating the pandemic since 2019. However, risks stemming from human errors, equipment malfunctions, and emergencies during cold-chain transportation can jeopardize vaccine security without effective safety standards. To ensure COVID-19 vaccine transportation safety, efficiency, and quality while mitigating risks, this study employed the modified Delphi method (MDM) to create a cold-chain vaccine transportation quality evaluation system. With the fuzzy analytic hierarchy process (FAHP), it then ranked indicator importance. The system comprises 5 criteria and 26 sub-criteria, highlighting factors like local weather conditions, topography, road characteristics, cold-chain logistics standardization, and national economic development. These significantly impact vaccine transport quality and risk. Regional authorities are advised to address these high-priority indicators by enhancing equipment, refining operational procedures, strengthening monitoring, offering training, etc. This comprehensive approach could minimize potential transportation setbacks, ensuring vaccine safety and quality. Crucially, this system offers valuable insights for health policies, transportation bodies, and companies. It sets safety benchmarks for cold-chain vaccine transportation and can be extended to other vaccines or medicines. This contribution is pivotal for future vaccine transportation management.