Literature DB >> 30096669

Correlation of dengue incidence and rainfall occurrence using wavelet transform for João Pessoa city.

Celso Augusto Guimarães Santos1, Isabel Cristina Guerra-Gomes2, Bruna Macêdo Gois2, Rephany Fonseca Peixoto2, Tatjana Souza Lima Keesen2, Richarde Marques da Silva3.   

Abstract

Dengue, a reemerging disease, is one of the most important viral diseases transmitted by mosquitoes. In this study, 55,680 cases of dengue between 2007 and 2015 were reported in Paraíba State, among which, 30% were reported in João Pessoa city, with peaks in 2015, 2011 and 2013. Weather is considered to be a key factor in the temporal and spatial distribution of vector-transmitted diseases. Thus, the relationship between rainfall occurrence and dengue incidences reported from 2007 to 2015 in João Pessoa city, Paraíba State, Brazil, was analyzed by means of wavelet transform, when a frequency analysis of both rainfall and dengue incidence signals was performed. To determine the relationship between rainfall and the incidence of dengue cases, a sample cross correlation function was performed to identify lags in the rainfall and temperature variables that might be useful predictors of dengue incidence. The total rainfall within 90 days presented the most significant association with the number of dengue cases, whereas temperature was not found to be a useful predictor. The correlation between rainfall and the occurrence of dengue cases showed that the number of cases increased in the first few months after the rainy season. Wavelet analysis showed that in addition to the annual frequency presented in both time series, the dengue time series also presented the 3-year frequency from 2010. Cross wavelet analysis revealed that such an annual frequency of both time series was in phase; however, after 2010, it was also possible to observe 45° up phase arrows, which indicated that rainfall in the present year led to an increased dengue incidence the following year. Thus, this approach to analyze surveillance data might be useful for developing public health policies for dengue prevention and control.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Brazil; Dengue; GIS; Rainfall; TRMM; Wavelet

Mesh:

Year:  2018        PMID: 30096669     DOI: 10.1016/j.scitotenv.2018.08.019

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  6 in total

1.  Drought impacts, social organization, and public policies in northeastern Brazil: a case study of the upper Paraíba River basin.

Authors:  José Carlos Dantas; Richarde Marques da Silva; Celso Augusto Guimarães Santos
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2.  Impacts of El Niño Southern Oscillation on the dengue transmission dynamics in the Metropolitan Region of Recife, Brazil.

Authors:  Henrique Dos Santos Ferreira; Ranyére Silva Nóbrega; Pedro Vinícius da Silva Brito; Jéssica Pires Farias; Jaime Henrique Amorim; Elvis Bergue Mariz Moreira; Érick Carvalho Mendez; Wilson Barros Luiz
Journal:  Rev Soc Bras Med Trop       Date:  2022-06-06       Impact factor: 2.141

3.  Spatiotemporal Transmission Patterns and Determinants of Dengue Fever: A Case Study of Guangzhou, China.

Authors:  Yebin Chen; Zhigang Zhao; Zhichao Li; Weihong Li; Zhipeng Li; Renzhong Guo; Zhilu Yuan
Journal:  Int J Environ Res Public Health       Date:  2019-07-12       Impact factor: 3.390

4.  The application of geographic information system for dengue epidemic in Southeast Asia: A review on trends and opportunity.

Authors:  Cipta Estri Sekarrini; Syamsul Bachri; Didik Taryana; Eggy Arya Giofandi
Journal:  J Public Health Res       Date:  2022-07-18

5.  Retrospective cross-sectional observational study on the epidemiological profile of dengue cases in Pernambuco state, Brazil, between 2015 and 2017.

Authors:  Iasmyn Dayanne Santos do Nascimento; André Filipe Pastor; Thaísa Regina Rocha Lopes; Pablo Cantalice Santos Farias; Juliana Prado Gonçales; Rodrigo Feliciano do Carmo; Ricardo Durães-Carvalho; Caroline Simões da Silva; José Valter Joaquim Silva Júnior
Journal:  BMC Public Health       Date:  2020-06-12       Impact factor: 3.295

6.  Multi-cluster and environmental dependant vector born disease models.

Authors:  Eduardo Vyhmeister; Gregory Provan; Blaine Doyle; Brian Bourke
Journal:  Heliyon       Date:  2020-09-01
  6 in total

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