Full metadata record
DC FieldValueLanguage
dc.contributor.authorWu, Chia-Yuanen_US
dc.contributor.authorChen, Sheng-Ien_US
dc.description.abstractSeasonal influenza outbreak has been a grave issue in Taiwan. Over 10% of populations are infected by influenza viruses, and the epidemics have caused loses on both health and economics. Recently, the government has implemented vaccination campaigns to prevent the diseases by providing 3 million doses of free vaccines to the high-risk populations in each year. However, there are still issues in the vaccine supply chain that post a threat for the implementation of the immunization program. This thesis focuses on two research topics. We first formulate a stochastic inventory model to investigate the cost effectiveness of vaccine inventory pooling policies. This study is motivated by the government recommendations of sharing and redistributing vaccine inventories when a shortage occurs. To the best of our knowledge, there is no such research focusing on this specific topic. The results show that the sharing policies reduce costs. In particular, the policy of sharing adult and pediatric vaccines has more cost reductions than the centralized policy. Our findings suggest that the pediatric vaccine obtains more savings than the adult vaccine through sharing and redistribution policies. In the second study, we develop a two-stage stochastic programming model to investigate the end-to-end decisions in a vaccine supply chain. Instead of considering to the herd immunity, the objective is to minimize the overall economic impact of prevention and treatment caused by the influenza. The first-stage decisions are to determine the ordering quantities of both adult and pediatric vaccines, and the second-stage decisions are to allocate vaccines among age-group populations and to determine the expedite requirements. Various uncertain factors are considered including vaccine efficacy, infection rate and demand. We implement an automatic process to obtain solutions from a large-scale setting of scenarios from the real-world data. The stochastic model provides us a more robust solution than the model only considering to a deterministic parameter verified by the computational results. By using the epidemic data, our findings offer valuable insights for decision makers across government, healthcare providers and other organizations to impact to the operational design of healthcare process.en_US
dc.subjectSeasonal influenzaen_US
dc.subjectVaccine supply chainen_US
dc.subjectCost analysisen_US
dc.subjectInventory modelen_US
dc.subjectStochastic programmingen_US
dc.titleAnalysis of Vaccine Supply Chain Policies for Seasonal Influenza Intervention under Uncertaintiesen_US
Appears in Collections:Thesis