Methodology to determine the evolution of asymptomatic HIV population using fuzzy set theory

dc.creatorJafelice, RM
dc.creatorDe Barros, LC
dc.creatorBassanezi, RC
dc.creatorGomide, F
dc.date2005
dc.dateFEB
dc.date2014-11-17T03:32:54Z
dc.date2015-11-26T16:36:57Z
dc.date2014-11-17T03:32:54Z
dc.date2015-11-26T16:36:57Z
dc.date.accessioned2018-03-28T23:19:52Z
dc.date.available2018-03-28T23:19:52Z
dc.identifierInternational Journal Of Uncertainty Fuzziness And Knowledge-based Systems. World Scientific Publ Co Pte Ltd, v. 13, n. 1, n. 39, n. 58, 2005.
dc.identifier0218-4885
dc.identifierWOS:000228311900004
dc.identifier10.1142/S0218488505003308
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/56633
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/56633
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/56633
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1271934
dc.descriptionThe aim of this paper is to o study the evolution of positive HIV population for manifestation of AIDS, the Acquired Immunodeficiency Syndrome. For this purpose, we suggest a methodology to combine a macroscopic HIV positive population model with an individual microscopic model. The first describes the evolution of the population whereas the second the evolution of HIV in each individual of the population. This methodology is suggested by the way that experts use to conduct public policies, namely, to act at the individual level to observe and verify the manifest population. The population model we address is a differential equation system whose transference rate from asymptomatic to symptomatic population is found through a fuzzy rule-based system. The transference rate depends on the CD4+ level, the main T lymphocyte attacked by the HIV retrovirus when it reaches the bloodstream. The microscopic model for a characteristic individual in a population is used to obtain the CD4+ level at each time instant. From the CD4+ level, its fuzzy initial value, and the macroscopic population model, we compute the fuzzy values of the proportion of asymptomatic population at each time instant t using the extension principle. Next, centroid defuzzification is used to obtain a solution that represents the number of infected individuals. This approach provides a method to find a solution of a non-autonomous differential equation from an autonomous equation, a fuzzy initial value, the extension principle, and center of gravity defuzzification. Simulation experiments show that the solution given by the method suggested in this paper fits well to AIDS population data reported in the literature.
dc.description13
dc.description1
dc.description39
dc.description58
dc.languageen
dc.publisherWorld Scientific Publ Co Pte Ltd
dc.publisherSingapore
dc.publisherSingapura
dc.relationInternational Journal Of Uncertainty Fuzziness And Knowledge-based Systems
dc.relationInt. J. Uncertainty Fuzziness Knowl.-Based Syst.
dc.rightsfechado
dc.sourceWeb of Science
dc.subjectepidemiological modeling
dc.subjectHIV population model
dc.subjectdynamic fuzzy modeling
dc.subjectfuzzy set theory
dc.subjectIndividuals
dc.titleMethodology to determine the evolution of asymptomatic HIV population using fuzzy set theory
dc.typeArtículos de revistas


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