scholarly journals VaxiMap: optimal delivery of vaccinations for housebound patients

2021 ◽  
Author(s):  
Thomas F Kirk ◽  
Adam J Barker ◽  
Armen Bodossian ◽  
Robert Staruch
Keyword(s):  
Financial Support ◽  
Travelling Salesman Problem ◽  
Vaccination Campaign ◽  
Cost Savings ◽  
Divide And Conquer ◽  
Travelling Salesman ◽  
Excel Spreadsheet ◽  
Critical Moment ◽  
Oxford University ◽  
Number Of Patients

Background. Throughout the UK's Covid-19 vaccination campaign, responsibility for vaccinating housebound patients has rested with individual GP surgeries, posing them a difficult logistical challenge (the travelling salesman problem). In response to demand from GPs, and a lack of existing solutions tailored specifically to vaccination, VaxiMap was created. This tool provides optimal routes for vaccine delivery and has been free to all users since its inception in January 2021. Methods. VaxiMap generates optimal routes subject to the constraint that the number of patients per route should be fixed. This ensures that a known quantity of vaccine can be set aside for each route and minimises wastage. The user need only upload an Excel spreadsheet of patient postcodes to be visited. A divide-and-conquer approach of iterative k-means clustering followed by within-cluster route optimisation is used to generate the routes. Findings. We find substantial savings in the time taken to plan vaccinations, as well as savings in the time taken to visit housebound patients. We estimate total savings to date of 4,700 hours of practitioner time, equivalent to 2.5 work-years, or approximately GBP 91k at typical practitioner salaries. Interpretation. The adoption of VaxiMap yielded both time and cost savings for GP surgeries and accelerated the UK's Covid-19 vaccination campaign at a critical moment. Funding. Financial support was provided by Magdalen College, Oxford, Oxford University Innovation, and JHubMed, part of UK Strategic Command. These parties were not involved in the preparation of this manuscript.

Cost Avoidance and Clinical Benefits Derived from a Pharmacy-Managed Anemia Program

2000 ◽  
Vol 35 (2) ◽  
pp. 169-175 ◽  
Author(s):  
Robert A. Quercia ◽  
Ronald Abrahams ◽  
C. Michael White ◽  
John D'Avella ◽  
Mary Campbell
Keyword(s):  
Cost Savings ◽  
Cost Effective ◽  
Hemodialysis Patients ◽  
Cost Avoidance ◽  
Number Of Patients ◽  
Epoetin Alpha ◽  
Clinical Benefits ◽  
Unit Dose ◽  
One Year ◽  
Alpha Therapy

A pharmacy-managed anemia program included distribution and clinical components, with the goal of making epoetin alpha therapy for hemodialysis patients more cost-effective. The Pharmacy Department prepared epoetin alpha doses for patients in unit-dose syringes, utilizing and documenting vial overfill. Pharmacists dosed epoetin alpha and iron (oral and intravenous) per protocol for new and established patients. Baseline data were obtained in 1994, one year prior to implementation of the program, and were re-evaluated in 1995 and 1998. Cost avoidance from utilization of epoetin alpha vial overfill in 1995 and 1998 was $83,560 and $91,148 respectively. In 1995 and 1998, cost avoidance from pharmacy management of anemia was $191,159 and $203,985 respectively. The total cost avoidance from 1995 through 1998 was estimated at $1,018,638. The number of patients with hematocrits under 31% decreased from 32% in 1994 to 21% and 14% in 1995 and 1998 respectively. We conclude that a pharmacy-managed anemia program for hemodialysis patients results in significant cost savings and better achievement of target hematocrits.

scholarly journals Tourist Route Optimization in the Context of Covid-19 Pandemic

2021 ◽  
Vol 13 (10) ◽  
pp. 5492
Author(s):  
Cristina Maria Păcurar ◽  
Ruxandra-Gabriela Albu ◽  
Victor Dan Păcurar
Keyword(s):  
Travelling Salesman Problem ◽  
Route Planning ◽  
Route Optimization ◽  
Travelling Salesman ◽  
Social Distancing ◽  
Tourist Destinations ◽  
Innovative Method ◽  
The Social ◽  
Immediate Response

The paper presents an innovative method for tourist route planning inside a destination. The necessity of reorganizing the tourist routes within a destination comes as an immediate response to the Covid-19 crisis. The implementation of the method inside tourist destinations can bring an important advantage in transforming a destination into a safer one in times of Covid-19 and post-Covid-19. The existing trend of shortening the tourist stay length has been accelerated while the epidemic became a pandemic. Moreover, the wariness for future pandemics has brought into spotlight the issue of overcrowded attractions inside a destination at certain moments. The method presented in this paper proposes a backtracking algorithm, more precisely an adaptation of the travelling salesman problem. The method presented is aimed to facilitate the navigation inside a destination and to revive certain less-visited sightseeing spots inside a destination while facilitating conformation with the social distancing measures imposed for Covid-19 control.

A column-and-row generation approach for the flying sidekick travelling salesman problem

2021 ◽  
Vol 124 ◽  
pp. 102913
Author(s):  
Maurizio Boccia ◽  
Adriano Masone ◽  
Antonio Sforza ◽  
Claudio Sterle
Keyword(s):  
Travelling Salesman Problem ◽  
Travelling Salesman

scholarly journals Converting MST to TSP Path by Branch Elimination

2020 ◽  
Vol 11 (1) ◽  
pp. 177
Author(s):  
Pasi Fränti ◽  
Teemu Nenonen ◽  
Mingchuan Yuan
Keyword(s):  
Spanning Tree ◽  
Closed Loop ◽  
Minimum Spanning Tree ◽  
Travelling Salesman Problem ◽  
Open Loop ◽  
Travelling Salesman ◽  
Elimination Algorithm ◽  
Number Of Iterations ◽  
Number Of Branches

Travelling salesman problem (TSP) has been widely studied for the classical closed loop variant but less attention has been paid to the open loop variant. Open loop solution has property of being also a spanning tree, although not necessarily the minimum spanning tree (MST). In this paper, we present a simple branch elimination algorithm that removes the branches from MST by cutting one link and then reconnecting the resulting subtrees via selected leaf nodes. The number of iterations equals to the number of branches (b) in the MST. Typically, b << n where n is the number of nodes. With O-Mopsi and Dots datasets, the algorithm reaches gap of 1.69% and 0.61 %, respectively. The algorithm is suitable especially for educational purposes by showing the connection between MST and TSP, but it can also serve as a quick approximation for more complex metaheuristics whose efficiency relies on quality of the initial solution.

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