Model-Based Planning and Delivery of Mass Vaccination Campaigns against Infectious Disease: Application to the COVID-19 Pandemic in the UK (original) (raw)
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Optimization Modeling for Pandemic Vaccine Supply Chain Management: A Review
arXiv (Cornell University), 2023
During various stages of the COVID-19 pandemic, countries implemented diverse vaccine management approaches, influenced by variations in infrastructure and socioeconomic conditions. This article provides a comprehensive overview of optimization models developed by the research community throughout the COVID-19 era, aimed at enhancing vaccine distribution and establishing a standardized framework for future pandemic preparedness. These models address critical issues such as site selection, inventory management, allocation strategies, distribution logistics, and route optimization encountered during the COVID-19 crisis. A unified framework is employed to describe the models, emphasizing their integration with epidemiological models to facilitate a holistic understanding. This article also summarizes evolving nature of literature, relevant research gaps, and authors' perspectives for model selection. Finally, future research scopes are detailed both in the context of modeling and solutions approaches.
An Operations Research-Based Approach to the Allocation of COVID-19 Vaccines
Chemical Engineering Transactions, 2021
The global scientific community has been successful in their efforts to develop, test, and commercialize vaccines for COVID-19. However, the limited supply of these vaccines remains to be a widespread problem as different nations have started their respective vaccine rollouts. Policymakers continue to deal with the difficult task of determining how to allocate them. This research work will present how the use of mathematical models can provide valuable decision support under such conditions. Both a linear programming model and a nonlinear programming model have been developed to determine the optimal allocation of COVID-19 vaccines that minimize fatalities and COVID-19 transmission, respectively. These scenarios have to be dealt with when not enough vaccines are available, and the pandemic is still in progress. The model is capable of handling large scale allocation problems such as those intended for the general population of a country. It could also be scaled down for organization...
Scientia Iranica
Nowadays, the healthcare industry focuses on the COVID-19 more than any other issues and it uses any approach or solution that is helpful to battle against this pandemic disease. There are many close similarities between the symptoms of the coronavirus and the Influenza (flu) virus, which sometimes make it difficult to distinguish between them. So, it has prompted countries to start flu vaccination to prevent potential problems. As a result, it has caused a significant increase in demand for the flu vaccine. To consider it, this study presents a multi-level supply chain for the flu vaccine during the COVID-19 pandemic. The problem pursues three main goals: cost minimization, maximizing demand allocation based on customer prioritization, and minimizing maximum lost customer demand. Due to the limited number of vaccines, a rate indicating the priority of each group of customers to receive the vaccine in the proposed model is considered. Customer prioritization can undermine justice because a flu patient is in critical condition but has low priority. Therefore, the third objective seeks to create justice and morality by minimizing the maximum lost demand. To evaluate the model, it is conducted based on a case study in Mazandaran province, Iran. The findings illuminate that 79 % of the demand will be met. Besides it shows that by increasing the capacity to 10%, the demand will be satisfied 9 percent more. Finally, some worthwhile and practical managerial insights are suggested.
How influenza vaccination policy may affect vaccine logistics
2012
Background: When policymakers make decision about the target populations and timing of influenza vaccination, they may not consider the impact on the vaccine supply chains, which may in turn affect vaccine availability. Purpose: Our goal is to explore the effects on the Thailand vaccine supply chain of introducing influenza vaccines and varying the target populations and immunization time-frames. Methods: We Utilized our custom-designed software HERMES (Highly Extensible Resource for Modeling Supply Chains), we developed a detailed, computational discrete-event simulation model of the Thailand's National Immunization Program (NIP) supply chain in Trang Province, Thailand. A suite of experiments simulated introducing influenza vaccines for different target populations and over different time-frames prior to and during the annual influenza season. Results: Introducing influenza vaccines creates bottlenecks that reduce the availability of both influenza vaccines as well as the other NIP vaccines, with provincial to district transport capacity being the primary constraint. Even covering only 25% of the Advisory Committee on Immunization Practice-recommended population while administering the vaccine over six months hinders overall vaccine availability so that only 62% of arriving patients can receive vaccines. Increasing the target population from 25% to 100% progressively worsens these bottlenecks, while increasing influenza vaccination time-frame from 1 to 6 months decreases these bottlenecks. Conclusion: Since the choice of target populations for influenza vaccination and the time-frame to deliver this vaccine can substantially affect the flow of all vaccines, policy-makers may want to consider supply chain effects when choosing target populations for a vaccine.
Distribution and transportation model for COVID-19 vaccine
International Journal of Enterprise Network Management
The pandemic that began in December 2019 in Wuhan, China has spread worldwide and infected millions of people across the globe. To combat COVID-19, scientists developed vaccines in record time. Without proper vaccine distribution, the country would suffer from low coverage rates and the virus would continue to spread. We are losing over 3,000 lives each day to COVID-19; this means a single day of delay in the distribution of vaccine is costing thousands of innocent lives. In this paper we have formulated a distribution model using mixed integer programming (MIP) that maximises the number of people vaccinated, minimises the cost of transportation over the entire network while ensuring widespread access.
Annals of Operations Research, 2021
Developing countries scramble to contain and mitigate the spread of coronavirus disease 2019 (COVID-19), and world leaders demand equitable distribution of vaccines to trigger economic recovery. Although numerous strategies, including education, quarantine, and immunization, have been used to control COVID-19, the best method to curb this disease is vaccination. Due to the high demand for COVID 19 vaccine, developing countries must carefully identify and prioritize vulnerable populations and rationalize the vaccine allocation process. This study presents a mixed-integer linear programming model for equitable COVID-19 vaccine distribution in developing countries. Vaccines are grouped into cold, very cold, and ultra-cold categories where specific refrigeration is required for their storage and distribution. The possibility of storage for future periods, facing a shortage, budgetary considerations, manufacturer selection, order allocation, time-dependent capacities, and grouping of the...
2019
Existing modelling work on preparedness to pandemic influenza has focused on evaluating specific countermeasures for pandemics with specific characteristics (typically based on historical instances). The aim of this study was to inform policy on preparedness planning for pandemic influenza based on the assessment of a wide range of scenarios and free from restrictive assumptions about timing and features of the next pandemic.We carried out epidemiological modelling and health economic analysis of an extensive set of scenarios, each comprising a combination of pandemic, vaccine and immunisation programme characteristics in presence or absence of access to effective antivirals. Preparedness policies that incorporate mass immunisation were evaluated on the basis of there being a given chance of a pandemic each year. To support understanding and exploration of model output, an interactive visualisation tool was devised and made available online.We evaluated over 29 million combinations ...
2021
The importance of vaccination and the logistics involved in the procurement, storage and distribution of vaccines across their cold chain has come to the forefront during the COVID-19 pandemic. In this paper, we present a decision support framework for optimizing multiple aspects of vaccine distribution across a multitier cold chain network. We propose two multi-period optimization formulations within this framework: first to minimize inventory, ordering, transportation, personnel and shortage costs associated with a single vaccine; the second being an extension of the first for the case when multiple vaccines with differing efficacies and costs are available for the same disease. Vaccine transportation and administration lead times are also incorporated within the models. We use the case of the Indian state of Bihar and COVID-19 vaccines to illustrate the implementation of the framework. We present computational experiments to demonstrate: (a) the organization of the model outputs;...
Optimization methods for large-scale vaccine supply chains: a rapid review
Annals of Operations Research
Global vaccine revenues are projected at $59.2 billion, yet large-scale vaccine distribution remains challenging for many diseases in countries around the world. Poor management of the vaccine supply chain can lead to a disease outbreak, or at worst, a pandemic. Fortunately, a large number of those challenges, such as decision-making for optimal allocation of resources, vaccination strategy, inventory management, among others, can be improved through optimization approaches. This work aims to understand how optimization has been applied to vaccine supply chain and logistics. To achieve this, we conducted a rapid review and searched for peer-reviewed journal articles, published between 2009 and March 2020, in four scientific databases. The search resulted in 345 articles, of which 25 unique studies
Operational analysis of school-based delivery models to vaccinate children against influenza
Health Systems, 2020
Large-scale immunisation programmes against seasonal influenza are characterised by logistical challenges related to the need for vaccinating large cohorts of people in a short amount of time. Careful operational planning of resources is essential for a successful implementation of such programmes. We focused on the process of child vaccination in schools and analysed the staffing and workflow aspects of a school-aged children vaccination programme in England. Our objectives were to document vaccination processes and analyse times and costs associated with different models deployed across England. We collected data through direct nonparticipatory observations. Statistical data analysis enabled us to identify potential factors influencing vaccine delivery time and informed the development of a tool to simulate vaccination sessions. Using this tool, we carried out scenario analyses and explored trade-offs between session times and costs in different settings. Our work ultimately supported the local implementation of school-based vaccination.