Fuzzy Analysis of Vaccine Efficacy against Covid-19
Creators
- 1. Department of Epidemiology, Faculty of Medicine, Constantine University, Algeria
- 2. Faculty of Medicine, Paris Sorbonne University, France
- 3. Faculty of Medicine, Setif University Hospital, UFAS Setif1 University, Setif, Algeria.
Description
The spread of variants of the COVID-19, the ability of vaccines to resist the evolution of the original strain is a major issue in pandemic study. Hypotheses report that the efficiency drops after six months. Other studies report that these vaccines are six times less effective against the Delta variant than Alpha variant. The type of vaccine (Pfizer Biontech, Moderna, AstraZeneca, Jonson & Jonson, SputnikV or Sinopharm and even the mixing of vaccines) and the type of variant (Alpha, Beta, Gamma, Delta and recently Omicron. others are less influential such as Lambda or Mu) and the duration efficiency. Methods: It seems clear that the system is very complex to analyze. Several uncertain factors are involved in the process. This study proposes the analysis of these parameters by fuzzy reasoning. One of the techniques of artificial intelligence is analysis by the principles of fuzzy inference. Conclusion: When the base of the rules contains all the possible combinations starting from the real cases, it becomes possible to assign random values to the input variables to instantly read the result at the output in numerical and symbolic terms. This helps predict the impact of each input parameter on the vaccine efficacy
Files
SRJBMS-9-30-35.pdf
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