Surveillance Routing of COVID-19 Infection Spread Using an Intelligent Infectious Diseases Algorithm

Guevara, Cesar; Peñas, Matilde Santos

doi:10.1109/access.2020.3036347

Cited by 12 publications

(10 citation statements)

References 28 publications

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“…In the literature [5], the students proposed a new hybrid genetic algorithm by using connected subgraphs as the crossover operator of the genetic algorithm, which solves the defect that the old crossover operation of the genetic algorithm generates nonsense paths, and combines the small habitat operation, migration algorithm, and local search. Shao et al [6] presents the traveler problem with node service time, and the node service time is a linear or quadratic function based on the start service time and proposes the method of additional subloops to eliminate the constraints.…”

Section: Related Jobsmentioning

confidence: 99%

Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

Chen

2022

Mathematical Problems in Engineering

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As an important historical and cultural heritage, rural red tourism sites have high historical, cultural, and social values. Moreover, rural red tourism sites are suitable for development and protection as tourism resources due to their unique landscape, architecture, culture, and art. In this paper, we propose a path generation model based on an ant colony algorithm to recommend the best path for tourists to visit rural red tourism sites. First, this paper investigates the modeling methods of path planning and multiobjective planning and their related solution algorithms to prepare for the establishment and solution of the tour path generation model for rural red tourism sites. By analyzing the problem description, this paper proposes the two model objectives of the shortest tour path and the highest total rating of the tourist attraction, and the model limitation of the total tour usage time, to model the model with a multiobjective planning approach. Then, by modifying the calculation of visibility and pheromone increments of the ant colony algorithm, the modified ant colony algorithm can take into account the two objectives of shortest path and highest total rating when constructing the path. Finally, this paper proposes to update the optimal path by using the number of ratings per unit path length as the update criterion of the optimal path.

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Section: Related Jobsmentioning

confidence: 99%

Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

Chen

2022

Mathematical Problems in Engineering

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“… Guevara & Penas (2020) developed the intelligent infectious diseases algorithm (IIDA), which could locate the sources of contagion and determine the survival rate of the COVID-19 virus using kernel density (KDE), ant colony optimization algorithms, and the TSP. The main goal of this study was to reduce the spread of the virus and decrease the number of infections.…”

Section: Related Workmentioning

confidence: 99%

COVID-19 spread algorithm in the international airport network-DetArpds

Guevara

Coronel

Maldonado

et al. 2023

PeerJ Computer Science

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Due to COVID-19, the spread of diseases through air transport has become an important issue for public health in countries globally. Moreover, mass transportation (such as air travel) was a fundamental reason why infections spread to all countries within weeks. In the last 2 years in this research area, many studies have applied machine learning methods to predict the spread of COVID-19 in different environments with optimal results. These studies have implemented algorithms, methods, techniques, and other statistical models to analyze the information in accuracy form. Accordingly, this study focuses on analyzing the spread of COVID-19 in the international airport network. Initially, we conducted a review of the technical literature on algorithms, techniques, and theorems for generating routes between two points, comprising an analysis of 80 scientific papers that were published in indexed journals between 2017 and 2021. Subsequently, we analyzed the international airport database and information on the spread of COVID-19 from 2020 to 2022 to develop an algorithm for determining airport routes and the prevention of disease spread (DetARPDS). The main objective of this computational algorithm is to generate the routes taken by people infected with COVID-19 who transited the international airport network. The DetARPDS algorithm uses graph theory to map the international airport network using geographic allocations to position each terminal (vertex), while the distance between terminals was calculated with the Euclidian distance. Additionally, the proposed algorithm employs the Dijkstra algorithm to generate route simulations from a starting point to a destination air terminal. The generated routes are then compared with chronological contagion information to determine whether they meet the temporality in the spread of the virus. Finally, the obtained results are presented achieving a high probability of 93.46% accuracy for determining the entire route of how the disease spreads. Above all, the results of the algorithm proposed improved different computational aspects, such as time processing and detection of airports with a high rate of infection concentration, in comparison with other similar studies shown in the literature review.

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“…The inclusion criteria were (i) articles focused on VRPs in a pandemic or epidemic setting, and (ii) both the terms "vehicle routing" and "pandemic", or other similar words (as mentioned in Table 3), appearing in the body text. Hereby, VRP applications on animal disease control [53], agricultural route planning [54,55], home health care (HHC) [56][57][58][59][60], supply chain management [61,62], and production management [63] were excluded from consideration, since this review aims to focus on humanitarian delivery optimization and pandemic control. For a holistic review of the HHC routing problem and production routing problem, interested readers can refer to the surveys provided by Fikar and Hirsch [64] and Adulyasak et al [65], respectively.…”

Section: Scopusmentioning

confidence: 99%

Vehicle Routing Optimization for Pandemic Containment: A Systematic Review on Applications and Solution Approaches

2022

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The global spread of the novel coronavirus (COVID-19) has accounted for many deaths. The effective containment of the current COVID-19 epidemic calls for a fast and sustainable delivery strategy to minimize the impact of this crisis. As such, this study aimed to conduct a comprehensive review of research on the vehicle routing problem (VRP) from a sustainable viewpoint during the pandemic and explore viable delivery solutions that may aid in the containment of the COVID-19 pandemic. Through a systematic review of the selected articles, four broad themes of pandemic containment measures from the delivery aspect were identified: efficient pharmaceutical delivery strategy, contactless distribution, sustainable waste transportation strategy, and isolated and quarantine vehicle scheduling. Following that, the methodology utilized to execute the containment measures were analyzed, research gaps were hightlighted, and possibilities for future studies were suggested. In summary, the goal of this research is to provide an overview of the literature on the application of VRPs in pandemic control and to assist academics and practitioners in learning more about the performance metrics, models, and solution techniques utilized in pandemic control delivery operations.

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Surveillance Routing of COVID-19 Infection Spread Using an Intelligent Infectious Diseases Algorithm

Cited by 12 publications

References 28 publications

Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

Path Optimization Model of Rural Red Tourist Attractions Based on Ant Colony Algorithm

COVID-19 spread algorithm in the international airport network-DetArpds

Vehicle Routing Optimization for Pandemic Containment: A Systematic Review on Applications and Solution Approaches

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