ArticleIEEE access : practical innovations, open solutions2020
Surveillance Routing of COVID-19 Infection Spread Using an Intelligent Infectious Diseases Algorithm.
Article in IEEE access : practical innovations, open solutions, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Utilising unsupervised machine learning to predict outbreaks of respiratory tract infections in acute Irish hospitals (2016-2021).Public health in practice (Oxford, England) · 2026Article
- Route Optimization for UVC Disinfection Robot Using Bio-Inspired Metaheuristic Techniques.Biomimetics (Basel, Switzerland) · 2024Article
- COVID-19 spread algorithm in the international airport network-DetArpds.PeerJ. Computer science · 2023Article
- Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.IEEE access : practical innovations, open solutions · 2021Article
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2 authors.
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Abstract
In this study, the Intelligent Infectious Diseases Algorithm (IIDA) has been developed to locate the sources of infection and survival rate of coronavirus disease 2019 (COVID-19), in order to propose health care routes for population affected by COVID-19. The main goal of this computational algorithm is to reduce the spread of the virus and decrease the number of infected people. To do so, health care routes are generated according to the priority of certain population groups. The algorithm was applied to New York state data. Based on infection rates and reported deaths, hot spots were determined by applying the kernel density estimation (KDE) to the groups that have been previously obtained using a clustering algorithm together with the elbow method. For each cluster, the survival rate -the key information to prioritize medical care- was determined using the proportional hazards model. Finally, ant colony optimization (ACO) and the traveling salesman problem (TSP) optimization algorithms were applied to identify the optimal route to the closest hospital. The results obtained efficiently covered the points with the highest concentration of COVID-19 cases. In this way, its spread can be prevented and health resources optimized.
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