Banca de DEFESA: JUCARLOS RUFINO DE FREITAS

Uma banca de DEFESA de DOUTORADO foi cadastrada pelo programa.
STUDENT : JUCARLOS RUFINO DE FREITAS
DATE: 18/02/2022
TIME: 10:00
LOCAL: https://meet.google.com/fjg-toyn-zxw
TITLE:

SPACE-TEMPORAL ANALYSIS OF THE DENGUE CASES NUMBER IN PERNAMBUCO, BRAZIL

KEY WORDS:

Dengue; Epidemiology; Statistical tests; Models; Spatial analysis.

PAGES: 73
BIG AREA: Ciências Agrárias
AREA: Agronomia
SUMMARY:

The dengue is compulsorily notifiable disease and are present on National Compulsory Notification List of Diseases, Aggravation and Public Health Events. In Brazilian Northeast, Pernambuco is the fourth state with the highest detection rate (per 100,000 inhab.) and lethality. With that, the present research aimed to analyze the number of weekly cases of dengue in the state of Pernambuco through georeferencing analysis. The research it's about epidemiological study of the ecological type, carried out with data from the Citizen Information Service and the Pernambuco Agency for Water and Climate, in the period 2000 to 2018. Used the TerraView 4.2.2 and Qgis 3.4.11 software for spatial analysis and the free software R version 3.6.1 and IBM SPSS Statistics 20, in which statistical tests were applied. To assess the correlation between the variables, the Pearson correlation coefficient was calculated and the generalized linear models were proceeded. Have been confirmed 508,948 cases of dengue in the state of Pernambuco, in the period 2000 and 2018. The spatial distribution of cases showed a high concentration in the Metropolitan Mesoregion of Recife, with greater frequency from Recife municipality. The results indicate the formation of clusters with positive spatial autocorrelation between municipalities in the Metropolitan Mesoregion of Recife. Regarding the Pearson correlation coefficient, positive correlations were observed in 75.54% of the municipalities. From the estimates of the models, it was verified that the Negative Binomial model proved to be more satisfactory to analyze the distribution of dengue cases. Therefore, the computerized processing of georeferenced data allowed the identification of municipalities with greater vulnerabilities, providing subsidies for the regulatory agencies of epidemics and endemics in the state of Pernambuco to plan their actions.

BANKING MEMBERS:
Interno - 1950420 - GUILHERME ROCHA MOREIRA
Interno - 2718900 - JOSIMAR MENDES DE VASCONCELOS
Externo à Instituição - MANOEL RIVELINO GOMES DE OLIVEIRA - UFBA
Presidente - 6383609 - MOACYR CUNHA FILHO
Externo à Instituição - RENISSON NEPONUCENO DE ARAUJO FILHO - UFT