Timely identification and reporting of rare infectious diseases has important economic, social and health implications. In this study, we investigate how different stakeholders in the existing reporting system influence the timeliness in identification and reporting of rare infectious diseases. Building on the vision of the information supply chain (Marinos, 2005; Sun & Yen, 2005) and drawing upon co-ordination theory to investigate inter-organizational dependencies, this dissertation treats information processing and transfer as an information supply chain system whose key performance indicator is timeliness. Jajosky and Groseclose (2004) identified that information reporting lead time is related to the number of layers of reporting. In this dissertation, we look at three layers of reporting rare infectious diseases in the Ohio Disease Reporting System (ODRS), and identify factors that influence the delay in processing and reporting of these diseases. The three layers considered are those for which the county public health system is responsible for the preventive and control measures of any event of rare infectious diseases and is also responsible for entering the confirmatory information into the state reporting system i.e. ODRS. This dissertation investigates the rare infectious disease reporting system in a way different from traditional approaches. Our view of a reporting system is an information supply chain, just as any product supply chain, with different layers in reporting, in which exist interactions between the members (hospitals, laboratories and public health system). We no longer treat the rare infectious disease information supply chain system as point-to-point, but instead as layer-to-layer relationships and examine in detail the factors influencing the delay in these layers. We use simulation based modeling to represent in a more natural way the individual interactive entities in the information supply chain system and to investigate the lead times at various stages during the transfer of information between these entities. In this dissertation, we demonstrate that interactions between different stakeholders in the reporting system have plausible consequences on the information supply chain performance for managing rare infectious diseases. In particular, we looked at the lead times at various stakeholder sites including laboratories, hospitals and local health jurisdictions. Through the trace-driven simulation study, using data collected for last two years, we replicated the results in real life settings in a decentralized system of reporting and compared it with a centralized, actively monitored reporting system and confirmed that the proposed centralized reporting method ensures considerable reduction in lead time in an information supply chain system for managing rare infectious diseases. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]