A Data-Driven Digital Application to Enhance the Capacity Planning of the COVID-19 Vaccination Process

Dijkstra's algorithm to find the nearest vaccine location

Since the start of Covid-19 pandemic has made many people look for vaccine locations. In general, Dijkstra algorithm is used to find the shortest path. The shortest path problem concentrates on finding the path with the minimum distance. The Dijkstra algorithm was chosen because it has several advantages other than advantageous in terms of running time to find the shortest path. This research focuses on calculation and implementation of Dijkstra algorithm that will result the shortest path with visual by Google Maps API. The project is tested with manual calculation first by using graph explanation. The graph is obtained based on route data obtained with the help of google maps then it is tested by implementing the Dijkstra algorithm using HTML, JavaScript and also Google Maps API to visualize the nearest vaccine location. From the research founded that there were shortcomings problem where program had to enter each road turn as a vertex and an edge, If not including the entire path that was formed, it would pass through buildings or structures that should not be passed. The results that will be displayed on the website based on the purpose of the research.

Logistics Trends and Innovations in Response to COVID-19 Pandemic: An Analysis Using Text Mining

The disruptions caused by the COVID-19 pandemic have forced many companies in the logistics sector to innovate, or even transform their business and underlying processes. Closing borders, limited supply and manpower, and continuous changes in regulations challenged many logistics firms to innovate. This study analyzes 5098 abstracts of logistics articles using text mining to identify and to quantify the changes in logistics trends and innovations before and during the COVID-19 pandemic, and if these trends and innovations were accelerated by the COVID-19 pandemic. Results indicate that (1) resiliency is an ongoing trend in logistics and has shown increasing importance during the COVID-19 pandemic; (2) there appears to be acceleration in digitalization trend in logistics based on emerging focus on blockchain, Internet of Things, data, drones, robots, and unmanned vehicles during COVID-19 pandemic, and (3) there seems to be no evidence of acceleration in sustainability due to COVID-19 despite an observed shift in sustainability trends in terms of bioenergy and biofuel before COVID-19 pandemic to low-carbon, hydrogen and electric vehicles during COVID-19 pandemic. This paper recommends logistics firms, especially Small and Medium Enterprises (SMEs), to analyze their readiness to adopt digitalization in terms of data, resources, and technology via, e.g., the use of a maturity scan, to contribute to sustainable and resilient logistics and to make sure that they remain competitive and future-proof. Policy makers can provide support to these SMEs by providing information, funding, and template solutions.

Bi-objective optimization of a stochastic resilient vaccine distribution network in the context of the COVID-19 pandemic

This paper develops an approach to optimize a vaccine distribution network design through a mixed-integer nonlinear programming model with two objectives: minimizing the total expected number of deaths among the population and minimizing the total distribution cost of the vaccination campaign. Additionally, we assume that a set of input parameters (e.g., death rate, social contacts, vaccine supply, etc.) is uncertain, and the distribution network is exposed to disruptions. We then investigate the resilience of the distribution network through a scenario-based robust-stochastic optimization approach. The proposed model is linearized and finally validated through a real case study of the COVID-19 vaccination campaign in France. We show that the current vaccination strategies are not optimal, and vaccination prioritization among the population and the equity of vaccine distribution depend on other factors than those conceived by health policymakers. Furthermore, we demonstrate that a vaccination strategy mixing the population prioritization and the quarantine restrictions leads to an 8.5% decrease in the total number of deaths.