Fernando A Inthamoussou, Fernando Valenciaga, Sebastián Núñez, Fabricio Garelli
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引用次数: 3
Abstract
This work presents an extended and age-band compartmentalised SEIR model that allows describing the spread evolution of SARS-CoV-2 and evaluating the effect of different detection rates, vaccination strategies or immunity periods. The model splits up the population into fifteen age groups of 5 years each, linked through a statistical interaction matrix that includes seventeen health states within each age group. An age-dependent transmission rate takes into account infectious between the groups as well the effect of interventions such as quarantines and mobility restrictions. Further, the proposal includes a nonlinear switched controller for model tuning purposes guarantying a simple and fast adjusting process. To illustrate the model potentials, the particular case of COVID-19 evolution in Argentina is analysed by simulation of three scenarios: (i) different detection levels combined with mobility restrictions, (ii) vaccination campaigns with re-opening of activities and (iii) vaccination campaigns with possible reinfections. The results exhibit how the model can aid the authorities in the decision making process.
期刊介绍:
Journal of Healthcare Informatics Research serves as a publication venue for the innovative technical contributions highlighting analytics, systems, and human factors research in healthcare informatics.Journal of Healthcare Informatics Research is concerned with the application of computer science principles, information science principles, information technology, and communication technology to address problems in healthcare, and everyday wellness. Journal of Healthcare Informatics Research highlights the most cutting-edge technical contributions in computing-oriented healthcare informatics. The journal covers three major tracks: (1) analytics—focuses on data analytics, knowledge discovery, predictive modeling; (2) systems—focuses on building healthcare informatics systems (e.g., architecture, framework, design, engineering, and application); (3) human factors—focuses on understanding users or context, interface design, health behavior, and user studies of healthcare informatics applications. Topics include but are not limited to: · healthcare software architecture, framework, design, and engineering;· electronic health records· medical data mining· predictive modeling· medical information retrieval· medical natural language processing· healthcare information systems· smart health and connected health· social media analytics· mobile healthcare· medical signal processing· human factors in healthcare· usability studies in healthcare· user-interface design for medical devices and healthcare software· health service delivery· health games· security and privacy in healthcare· medical recommender system· healthcare workflow management· disease profiling and personalized treatment· visualization of medical data· intelligent medical devices and sensors· RFID solutions for healthcare· healthcare decision analytics and support systems· epidemiological surveillance systems and intervention modeling· consumer and clinician health information needs, seeking, sharing, and use· semantic Web, linked data, and ontology· collaboration technologies for healthcare· assistive and adaptive ubiquitous computing technologies· statistics and quality of medical data· healthcare delivery in developing countries· health systems modeling and simulation· computer-aided diagnosis