Aplicação de gráficos de recorrência na análise de casos notificados de dengue, atendimento antirrábico humano e leishmaniose visceral

• Autor(a) principal: Bocchi, Mônica Regina
• Data de Publicação: 2018
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da FAMERP
• Texto Completo: http://bdtd.famerp.br/handle/tede/539
• topic: Estudos de Séries Temporais; Dengue; Leishmaniose Visceral; Vacinas Antirrábicas; Time Series Studies; Dengue; Leishmaniasis, Visceral; Rabies Vaccines; CIENCIAS DA SAUDE

Diseases of public health concerns compose the list of notifiablediseases. These include zoonoses, which are complex problems since it is related to multiplicity of factors interlacing and in dynamic interaction. The most frequent in São José do Rio Preto region are: dengue, human rabies service (HRT) and visceral leishmaniasis (VL). Objectives: To evaluate the behavior pattern of dengue, HRT and VL, through nonlinear analysis, such as random, chaotic, periodic or linear, to better measure prevention and control actions, as well as to improve the management of health services. Material and Method: We used the Cynefin structure and the recurrence graphics analysis. A historical series of 13 years of confirmed cases of dengue and HRT in the city of São José do Rio Preto were analyzed, in addition to a series of seven years of confirmed cases of VL reported in the region. Results: By the recurrence analysis and the quantitative analysis we could ascertain that dengue has a behavior similar to linear, and both HRT and VL, have behavior similar to chaotic. By the Cynefin structure, the dengue situation can be classified from simple to complicated; AARH, complicated to complex and LV, from complex to chaotic. Conclusions: Non - linear analysis can clearly define the behavior of each disease, as well as the complexity of the problems to be faced. The use of two simultaneous methods of analysis strengthens the reliability of the study. Epidemiological methods and recurrence charts are important tools for the analysis and are complementary in predicting future pictures.