The Integrated Information Architecture: A Pilot Study Approach to Leveraging Logistics Management with Regard to Influenza Preparedness (original) (raw)
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Being logistically prepared for an influenza pandemic
Journal of Business Continuity & Emergency …, 2008
Critical to any healthcare professional's pandemicpreparedness is an understanding of the disease's processes and how it can affect a population. Administrators and healthcare logistics professionals must be prepared to assist, as necessary, in risk mitigation through advance planning, demand forecasting and provision of support services once the crisis occurs. Healthcare administrative personnel and other emergency management professionals should begin their preparation by asking specific questions related to organisational readiness. While the rest of the world reacts to the impending pandemic with a degree of fatalistic apathy, healthcare logistics professionals must be determined to engage, continuously, effective countermeasures to help mitigate significant losses and the degradation of people's health.
Being prepared logistically for a pandemic influenza
Health authorities agree that no longer is there a question of if a pandemic is going to occur; the question now is when will one occur? Critical to any healthcare professional’s understanding of being prepared for a pandemic is an understanding, initially, of the disease processes and how it can affect a population. Administrators and healthcare logistics professionals must be prepared to assist, as necessary, in risk mitigation through advance planning, forecasting of demands, and support services needed for locations when the crisis occurs. Healthcare administrative personnel and other emergency management professionals should begin posturing for a pandemic by asking some rather specific questions related to organizational readiness. While the rest of the world reacts to the impending strike of a pandemic with a degree of fatalistic apathy, healthcare logistics professionals must be determined to engage, continuously, effective countermeasures to help mitigate significant losses ...
2008 Winter Simulation Conference, 2008
Recent incidents of avian flu (H5N1) in Asia and the pandemic influenza cases in history (1918, 1957 and 1968) suggest that a future pandemic influenza is inevitable and likely imminent. Governments and non-governmental organizations prepare response plans on how to react to a pandemic influenza. In this paper, we study the logistics side of the problem, specifically, food distribution logistics during the pandemic influenza. For this purpose, we develop a disease spread model that assists in estimating the food need geographically at a given time. Then, we develop an integrated solution approach called the Dynamic Update Approach to build the food distribution network. We run our integrated disease spread and facility location model for the state of Georgia and present the estimated number of infections and meals needed in each census tract for a one year period.
Knowledge management as a support for supply chain logistics planning in pandemic cases
Brazilian Journal of Operations & Production Management, 2020
Objective: This study presents how the knowledge management can be an excellent ally to logistics for planning the supply chain in actions in cases of pandemic. Project / Methodology / Approach: The present study was based on a bibliographic review sought in the main existing databases. From there, it was possible to obtain subsidies to support the proposal of this work. Results: The results showed that a correct application of knowledge management can assist in logistical planning in a very effective way, reducing gaps and shortages, providing very effective actions to mitigate the main obstacles that a pandemic can generate. Research limitations: The most important limitation in this study was the fact that the COVID-19 pandemic is still very active and logistics operations do not yet have effective and consolidated data to bring even more reliable results. Practical implications: According to the conclusions obtained, governmental organizations, at their three levels (municipal, ...
Simulation as Decision Support in Pandemic Influenza Preparedness and Response
Outbreak of a destructive pandemic influenza threatens to disrupt societies worldwide. International agencies and national governments have prepared plans and recommendations, but it is often decision-makers with the local authorities that are responsible for implementing the response. A central issue for these decision makers is what interventions are available and effective for the specific local community. The paper presents a simulator architecture and its relation to a workflow for decision support in influenza preparedness and response. The simulator can simulate pandemic scenarios, using localized community models, in the presence of various interventions to support an evaluation of potential response strategies. The architecture includes a customized modeling tool, separated from the simulation engine, which facilitates swift scenario modification and recalculation. This flexibility is essential both to explore alternative solutions in planning, and to adapt to changing requirements, information, and resources in outbreak response. An example simulation, based on actual population data from a reference city, illustrates the approach.
Inventory Management in Response to an Unfolding Epidemic
2016
A generic production-inventory (PI) management framework is developed for a hospital to respond to an unfolding epidemic. The framework is modelled as a closed feedback loop, where the future epidemic behaviour is governed by the medicine supply of current period which further influences the demand for medicine in the future. A Susceptible-Infected-Recovered (SIR) disease diffusion model is coupled with the PI model as a forecasting tool to anticipate the medicine demands of a novel epidemic during production lead time, where the forecasting model parameters in every decision cycle are estimated by calibrating forecasting disease model with past epidemic data. With an illustrative example of a hypothetical outbreak, the performance of SIR model is compared against a näıve forecasting method (defined as next period’s forecast is current period’s demand) and found that SIR model outperforms näıve method in terms of reducing epidemic impact and inventory leftover.
Disaster Medicine and Public Health Preparedness, 2013
ObjectivesTo assess local, state, federal, and global pandemic influenza preparedness by identifying pandemic plans at the local, state, federal, and global levels, and to identify any information technology (IT) systems in these plans to support critical care triage during an influenza pandemic in the Canadian province of Ontario.MethodsThe authors used advanced MEDLINE and Google search strategies and conducted a comprehensive review of key pandemic influenza Web sites. Descriptive data extraction and analysis for IT systems were conducted on all of the included pandemic plans.ResultsA total of 155 pandemic influenza plans were reviewed: 29 local, 62 state, 63 federal, and 1 global. We found 70 plans that examined IT systems (10 local, 33 state, 26 federal, 1 global), and 85 that did not (19 local, 29 state, 37 federal). Of the 70 plans, 64 described surveillance systems (10 local, 32 state, 21 federal, 1 global), 2 described patient data collection systems (1 state, 1 federal); 4...
Inventory management strategies for mitigating unfolding epidemics
IISE Transactions on Healthcare Systems Engineering, 2018
This paper provides a generic framework, comprising a hospital, a forecasting, and an inventory management module for medicine stock management of any regional level hospital during both regular and epidemic season. The performance of the proposed dynamic disease diffusion models with parameter update is compared against a traditional naïve forecasting policy. The disease diffusion forecasting models are found to outperform the naïve policy in terms of epidemic alleviation and inventory savings. Further analyses are carried out on choosing suitable ordering policies, quantifying the effect of key factors like safety stockpile, epidemic declaration threshold on epidemic dynamics. The findings of this research are summarized and the managerial implications are derived for practical applications.