The performance of vaccine logistics systems (i.e., the steps in a supply chain necessary to get vaccines from manufacturers to patients) can impact whether vaccines are delivered at the right time, place and in the right condition for patients during immunization sessions. Immunization coverage in a population depends on a well-functioning vaccine supply chain. If target populations are not immunized before exposure, they are left unprotected against vaccine preventable diseases (VPDs) and can contribute to infectious disease transmission in their communities.
Changes may be made to logistics systems without considering their potential effects on vaccine distribution and availability at vaccinating health centers. The combined works of this dissertation illustrate such changes and resulting impacts on vaccine availability, including: changes to vaccine presentations, changes to the vaccine supply chain structure, and changes to a vaccine regimen.
The Vaccine Modeling Initiative (VMI) developed the Highly Extensible Resource for Modeling Supply chains (HERMES), a stochastic, discrete-event simulation model. VMI collected information on vaccine cold chain equipment (e.g., refrigerators and freezers), transportation fleets, demographic indicators for target populations, and supply chain operating policies (e.g., shipping frequencies) for the country Niger and for Trang province in Southern Thailand. HERMES was then used to evaluate various supply chain interventions and determine their impacts on logistics indicators including: vaccine availability at health centers, transportation and storage utilization, and additional capacity requirements.
With over a dozen new vaccines being introduced into national immunization programs in the next decade, logistics systems will be further pressed to ensure vaccines are delivered to their target populations. These studies will highlight the importance of considering vaccine logistics systems when making changes to immunization programs, and suggest potential alternative strategies to improve the performance of supply chains and ultimately vaccination coverage rates. Furthermore, these studies will demonstrate the utility in using computational models to evaluate and provide solutions for public health challenges by representing relationships that would not otherwise be apparent.
| Identifer | oai:union.ndltd.org:PITT/oai:PITTETD:etd-08012011-204117 |
| Date | 23 September 2011 |
| Creators | Assi, Tina-Marie |
| Contributors | Bruce Y. Lee, MD, MBA, Stephen R. Wisniewski, Jayant Rajgopal, Shawn T. Brown, Bryan A. Norman |
| Publisher | University of Pittsburgh |
| Source Sets | University of Pittsburgh |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.pitt.edu/ETD/available/etd-08012011-204117/ |
| Rights | restricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Pittsburgh or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
Page generated in 0.0019 seconds