Non-parametric tests applied to reported cases of dengue in the southeast region of Brazil

Abstract

Dengue is one of the biggest problems of global public health in developing and underdeveloped countries. Nowadays, researchers in climate changes are concerned about the impact of these changes on human health, particularly with increased this epidemic. Dengue is among the largest public health problems in Brazil and is higher in the months with high temperatures, which is the Aedes aegypti's reproductive period climax. Reported dengue cases via DATASUS from 1994 to 2014 were analyzed. Mann-Kendall (MK), Run and Pettit nonparametric tests; were applied to time series. The run test indicated that the time series is homogenous and persistence free. There is a non-significant trend of increase of a number of reported dengue cases only in Rio de Janeiro. Based on the test, three positive trends were identified in the time series of São Paulo, Minas Gerais and the Espírito Santo States of dengue cases reported in Southeast of Brazil. Pettitt test was able to identify the years classified as El Niño events and that had a significant impact on the increase of dengue cases in the southeastern region of Brazil.