Assi, Tina-Marie (2011) Impacts of Vaccine Cold Chain Logistics on Vaccine Epidemiology. Doctoral Dissertation, University of Pittsburgh.
Abstract
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 (VPD's) 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.
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Details |
| Item Type: | University of Pittsburgh ETD |
| ETD Committee: | | ETD Committee Type | Committee Member | Email |
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| Committee Chair | Lee, Bruce Y. | byl1@pitt.edu | | Committee Member | Norman, Bryan A. | banorman@pitt.edu | | Committee Member | Rajgopal, Jayant | rajgopal@pitt.edu | | Committee Member | Brown, Shawn T. | stbrown@psc.edu | | Committee Member | Wisniewski, Stephen R. | wisniew@edc.pitt.edu | | Committee Member | , | |
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| Title: | Impacts of Vaccine Cold Chain Logistics on Vaccine Epidemiology |
| Status: | Unpublished |
| Abstract: | 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 (VPD's) 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. |
| Date: | 23 September 2011 |
| Date Type: | Completion |
| Defense Date: | 22 July 2011 |
| Approval Date: | 23 September 2011 |
| Submission Date: | 01 August 2011 |
| Access Restriction: | 5 year -- Restrict access to University of Pittsburgh for a period of 5 years. |
| Patent pending: | No |
| Institution: | University of Pittsburgh |
| Thesis Type: | Doctoral Dissertation |
| Refereed: | Yes |
| Degree: | PhD - Doctor of Philosophy |
| URN: | etd-08012011-204117 |
| Uncontrolled Keywords: | global health; logistics; supply chain; Vaccines |
| Schools and Programs: | Graduate School of Public Health > Epidemiology |
| Date Deposited: | 10 Nov 2011 14:56 |
| Last Modified: | 11 Jan 2012 16:18 |
| Other ID: | http://etd.library.pitt.edu/ETD/available/etd-08012011-204117/, etd-08012011-204117 |
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