Efficient and effective large-scale vaccine distribution

The goal of pandemic response is to provide the greatest protection, for the most people, in the least amount of time. Short response times minimize both current and future health impacts for evolving pathogens that pose global threats. To achieve this goal, efficient and effective systems are needed for distributing and administering vaccines, a cornerstone of pandemic response. COVID-19 vaccines were developed in record time in the U.S. and abroad, but U.S. data shows that they were not distributed efficiently and effectively once available. In an effort to “put vaccines on every corner”, pharmacies and other small venues were a primary means for vaccinating individuals, but daily throughput rates at these locations were very low. This contributed to extended times from manufacture to administration. An important contributing factor to slow administration rates for COVID-19 was vaccine transport and storage box size. In this paper, we establish a general system objective and provide a computationally tractable approach for allocating vaccines in a rolling horizon manner optimally. We illustrate the consequences of both box size and the number and capacity of dispensing locations on achieving system objectives. Using U.S. CDC data, we demonstrate that if vaccines are allocated and distributed according to our proposed strategy, more people would have been vaccinated sooner in the U.S. Many additional days of protection would have occurred, meaning there would have been fewer infections, less demand for healthcare resources, lower overall mortality, and fewer opportunities for the evolution of vaccine-evading strains of the disease

Oxygen transfer rate model for cell-free and predictive D.O. control in intensified bioreactor processes

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COVID-19 Models for Hospital Surge Capacity Planning: A Systematic Review

Objective: Health system preparedness for coronavirus disease (COVID-19) includes projecting the number and timing of cases requiring various types of treatment. Several tools were developed to assist in this planning process. This review highlights models that project both caseload and hospital capacity requirements over time. Methods: We systematically reviewed the medical and engineering literature according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We completed searches using PubMed, EMBASE, ISI Web of Science, Google Scholar, and the Google search engine. Results: The search strategy identified 690 articles. For a detailed review, we selected 6 models that met our predefined criteria. Half of the models did not include age-stratified parameters, and only 1 included the option to represent a second wave. Hospital patient flow was simplified in all models; however, some considered more complex patient pathways. One model included fatality ratios with length of stay (LOS) adjustments for survivors versus those who die, and accommodated different LOS for critical care patients with or without a ventilator. Conclusion: The results of our study provide information to physicians, hospital administrators, emergency response personnel, and governmental agencies on available models for preparing scenario-based plans for responding to the COVID-19 or similar type of outbreak

Analysis and algorithms for service parts supply chains

Services requiring parts has become a $1.5 trillion business annually worldwide, creating a tremendous incentive to manage the logistics of these parts efficiently by making planning and operational decisions in a rational and rigorous manner. This book provides a broad overview of modeling approaches and solution methodologies for addressing service parts inventory problems found in high-powered technology and aerospace applications. The focus in this work is on the management of high cost, low demand rate service parts found in multi-echelon settings. This unique book, with its breadth of topics and mathematical treatment, begins by first demonstrating the optimality of an order-up-to policy [or (s-1,s)] in certain environments. This policy is used in the real world and studied throughout the text. The fundamental mathematical building blocks for modeling and solving applications of stochastic process and optimization techniques to service parts management problems are summarized extensively. A wide range of exact and approximate mathematical models of multi-echelon systems is developed and used in practice to estimate future inventory investment and part repair requirements. The text may be used in a variety of courses for first-year graduate students or senior undergraduates, as well as for practitioners, requiring only a background in stochastic processes and optimization. It will serve as an excellent reference for key mathematical concepts and a guide to modeling a variety of multi-echelon service parts planning and operational problems

Exact Analysis of a Lost Sales Model under Stuttering Poisson Demand

We investigate the (S-1,S) inventory policy under stuttering Poisson demand and generally distributed lead time when the excess demand is lost. We correct results presented in Feeney and Sherbrooke's seminal paper (1966). We also prove that the distribution of ?ordered unit delivery times? becomes increasingly concentrated as the variance-to-mean ratio of demand increases

A Model for a Multi-Item, Multi-Echelon, Multi-Indenture Inventory System

The purpose of this paper is to describe a mathematical model, called MOD-METRIC, for the control of a multi-item, multi-echelon, multi-indenture inventory-system for recoverable items, that is, items subject to repair when they fail. Discussion is limited to two-echelon multi-item systems in which an item may be demanded at any one of several locations called bases; in turn, these bases receive inventory from a central location called a depot. The objectives of the model are to describe the logistics relationship between an assembly and its subassemblies, and to compute spare stock levels for both echelons for the assembly and subassemblies with explicit consideration of this logistics relationship. In particular, the model is used to determine the base and depot spare stock levels which minimize total expected base backorders for the assembly subject to a system investment constraint. An example is given showing how the model can be used to calculate spare engine and engine module stock levels. MOD-METRIC has been implemented by the Air Force as the method for computing recoverable spare stock levels for the F-15 weapon system.

Analytic Methods for Estimating Labor Requirements at a Parts Distribution Center

Picking and put-away operations must be executed quickly and efficiently in warehouses within multi-echelon supply chains. The ability to perform these picking and put-away tasks in a timely fashion is a function of the distance the workers must travel within the warehouse. Two analytic methods for estimating the labor requirements associated with these activities are presented. The first method is a stochastic model in which demand at each location is described by a random variable. The second method is based on the assumption that demand is always equal to its expected value. 1 Introduction Multi-echelon inventory systems exist to provide excellent customer service in a timely manner without requiring each retailer or other stocking location to hold high levels of inventory. In one such environment, automotive service parts are produced, packaged, stocked, and distributed. In this instance there are four echelons in the system. At the lowest level, car dealers stock parts to ..

Note--Comments on "Single Cycle Continuous Review Policies for Arborescent Production/Inventory Systems"

In the paper by Graves and Schwarz [Graves, Stephen C., Leroy B. Schwarz. 1977. Single cycle continuous review policies for arborescent production/inventory systems. Management Sci. 23 (5, January) 529-540.], we observed an error in their discussion of optimal policies for the one warehouse-m retailer system. Specifically, Theorem 1, which states that the optimal stationary policy is a single-cycle policy, is incorrect.inventory/production, inventory/production: deterministic models

The Effects of Load Smoothing on Inventory Levels in a Capacitated Production and Inventory System

In most inventory-focused research, system control is achieved through controlling inventories while permitting production levels to vary substantially each period. However, in many firms, fluctuations in production levels may be very costly; in some firms it is impossible to vary production levels substantially through time due to the physical constraints found in the processes. We examine a system in which the production level is constrained between a maximum and minimum level each period, and in which inventory levels are allowed to vary accordingly. We explore the effects of production smoothing on several system performance metrics.