A Dominance‐Based Rough Set Approach for an Enhanced Assessment of Seasonal Influenza Risk
| Autor: | Fatima-Zohra Younsi, Alessio Ishizaka, Salem Chakhar, Omar Boussaid, Djamila Hamdadou |
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| Rok vydání: | 2020 |
| Předmět: |
Decision support system
Operations research Computer science 0211 other engineering and technologies Pilot Projects 02 engineering and technology 010501 environmental sciences Multicriteria classification Risk Assessment 01 natural sciences Decision Support Techniques Machine Learning Physiology (medical) Influenza Human Humans Computer Simulation Safety Risk Reliability and Quality Spatial analysis 0105 earth and related environmental sciences 021110 strategic defence & security studies Dominance-based rough set approach Decision problem Data warehouse Algeria Data Interpretation Statistical Epidemiological Monitoring Seasons Rough set Risk assessment |
| Zdroj: | Risk Analysis. 40:1323-1341 |
| ISSN: | 1539-6924 0272-4332 |
| DOI: | 10.1111/risa.13478 |
| Popis: | Accounting for about 290,000-650,000 deaths across the globe, seasonal influenza is estimated by the World Health Organization to be a major cause of mortality. Hence, there is a need for a reliable and robust epidemiological surveillance decision-making system to understand and combat this epidemic disease. In a previous study, the authors proposed a decision support system to fight against seasonal influenza. This system is composed of three subsystems: (i) modeling and simulation, (ii) data warehousing, and (iii) analysis. The analysis subsystem relies on spatial online analytical processing (S-OLAP) technology. Although the S-OLAP technology is useful in analyzing multidimensional spatial data sets, it cannot take into account the inherent multicriteria nature of seasonal influenza risk assessment by itself. Therefore, the objective of this article is to extend the existing decision support system by adding advanced multicriteria analysis capabilities for enhanced seasonal influenza risk assessment and monitoring. Bearing in mind the characteristics of the decision problem considered in this article, a well-known multicriteria classification method, the dominance-based rough set approach (DRSA), was selected to boost the existing decision support system. Combining the S-OLAP technology and the multicriteria classification method DRSA in the same decision support system will largely improve and extend the scope of analysis capabilities. The extended decision support system has been validated by its application to assess seasonal influenza risk in the northwest region of Algeria. |
| Databáze: | OpenAIRE |
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