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

Santos, Celso Augusto Guimarães; Guerra-Gomes, Isabel Cristina; Gois, Bruna Macêdo; Peixoto, Rephany Fonseca; Keesen, Tatjana Souza Lima; Silva, Richarde Marques da

doi:10.1016/j.scitotenv.2018.08.019

Cited by 36 publications

(30 citation statements)

References 29 publications

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“…In agreement with our findings, in Paraíba state, also in the Northeast region of Brazil, a significant association was observed between rainfall and dengue cases whereas temperature was not found to be a useful predictor [58]. The influence of rainfall on the density of Ae.…”

Section: Discussionsupporting

confidence: 89%

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

et al. 2020

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Background: The spread of Dengue virus (DENV) infections, as well as their signs and symptoms, are the result of a complex interaction between several factors. In Brazil, especially in the Northeastern, dengue is an important public health problem. Here, we report an epidemiological analysis of dengue cases in Pernambuco state, Northeastern Brazil, during 2015-2017. Methods: This work is a retrospective cross-sectional observational study on the epidemiological profile of all dengue cases confirmed and reported to the Health Secretary of Pernambuco between 2015 and 2017. These data cover all municipalities of Pernambuco, except Fernando de Noronha. DENV-positive individuals were classified according to the dengue type (without and with warning signs, or severe dengue), age, gender, ethnicity and intermediate geographic region of residence (Recife, Caruaru, Serra Talhada or Petrolina). The distribution of cases over the years was assessed by χ2 test. Temperature and rainfall data were evaluated by Unpaired t-test. p-value < 0.05 and CI 95% were considered in all analyses. Results: Most dengue cases was without warning signs. The most observed characteristics in the less severe dengue phenotypes were: female, mulatto ethnicity and age between 20 and 39 years old; this profile was more clearly observed in 2015. In 2016 and 2017, however, the numbers of dengue without and with warning signs were more evenly distributed and the difference in cases within groups decreased significantly. Regarding severe dengue, mulattoes were the most affected, but it is possible to note a trend towards a more uniform distribution between the genders and ages. Recife was the region with the highest numbers of both total cases and incidence rates and the highest rainfall levels. Overall, over the years, there has been a decrease in dengue cases in all regions of Pernambuco.

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Section: Discussionsupporting

confidence: 89%

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

et al. 2020

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“…In the municipality of Santo André, there was no significance of the studied parameters with dengue cases, except for the RI, inversely correlated with dengue cases. Contrary to our results, a study in other Brazilian metropolitan area showed the total amount of rainfall was significantly associated with the number of dengue incidences according Santos et al 29 . Focks & Barrera 30 and Patz et al 31 stated that vector density increases due to rain, causing an increase in dengue cases, because the higher humidity during the rainy season provides an ideal environment for growth and survival of dengue fever mosquitoes.…”

Section: Discussioncontrasting

confidence: 99%

Fatores associados a casos de Dengue na área industrial brasileira: um estudo ecológico

Cordeiro

Fonseca

Arab

et al. 2020

jhgd

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Introdução: A dengue é uma doença infecciosa viral sistêmica aguda, estabelecida mundialmente em ciclos de transmissão epidêmica e endêmica. Altos níveis de precipitação, temperaturas adequadas, proximidade entre centros urbanos e peri-urbanos, movimento humano entre centros populacionais e produção de resíduos sólidos urbanos (RSU) podem facilitar a transmissão e a disseminação da dengue. Objetivo: Identificar a relação entre casos diagnosticados de dengue e fatores socioeconômicos, geração de massa de RSU e índice pluviométrico. Método: Estudo ecológico, com coleta secundária de dados de 2010 a 2016 para cada município da Região do Grande do ABC, em São Paulo, Brasil. Foram investigados a população total, o produto interno bruto (PIB) per capita, RSU, número de casos de dengue e índice pluviométrico. Os dados foram coletados nos sites do Instituto Brasileiro de Geografia e Estatística (IBGE), os municípios da Região do Grande ABC, o Consórcio Intermunicipal do Grande ABC, a Agência de Desenvolvimento Econômico do Grande ABC, o Sistema Nacional de Informação sobre Saneamento, Centro de Vigilância Epidemiológica do Estado de São Paulo e o Departamento de Água e Energia Elétrica do Estado de São Paulo. As relações entre variáveis foram testadas pela correlação de Spearman. Resultados: A análise dos dados de todos os municípios mostrou correlação positiva entre casos de dengue com população total (r = 0,675, p <0,01), produto interno bruto per capita (r = 0,539, p <0,01) e RSU por habitante por ano (r = 0,492, p <0,01). Também foram observadas correlações positivas entre população total e produto interno bruto per capita (r = 0,583, p <0,01), RSU / dia (r = 0,302, p <0,05) e RSU / ano (r = 0,961, p <0,01); produto interno bruto per capita e RSU / dia (r = 0,849, p <0,01), RSU / ano (r = 0,410, p <0,05) e índice de precipitação (IR) (r = 0,416, p <0,05); RSU / dia e RSU /ano (r = 0,389, p <0,01) e IR (r = 0,388, p <0,05). Conclusão: Quanto maior a população total, poder de compra ou condição socioeconômica (PIB per capita) e a geração de RSU, maior o número de casos de dengue. O descarte adequada dos RSU parece ser uma maneira de ajudar no controle dos casos de dengue.

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“…Patients suspected of having DF included those who lived or traveled to DF endemic areas (over 14 days) and subsequently exhibited clinical symptoms such as fever, with two or more of these manifestations: nausea, vomiting and skin erythema. Medical professionals were responsible for the clinical classification of the disease, along with laboratory confirmation through serology, NS1 (non-structural protein 1) test or polymerase chain reaction (PCR) tests [21]. Acute phase sera were tested by enzyme linked immunoassay (ELISA) for the detection of dengue NS1 antigen and dengue IgM antibodies.…”

Section: Methodsmentioning

confidence: 99%

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

Chen

Zhao

et al. 2019

IJERPH

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Dengue fever is one of the most common vector-borne diseases in the world and is mainly affected by the interaction of meteorological, human and land-use factors. This study aims to identify the impact of meteorological, human and land-use factors on dengue fever cases, involving the interplay between multiple factors. The analyses identified the statistically significant determinants affecting the transmission of dengue fever, employing cross-correlation analysis and the geo-detector model. This study was conducted in Guangzhou, China, using the data of confirmed cases of dengue fever, daily meteorological records, population density distribution and land-use distribution. The findings highlighted that the dengue fever hotspots were mainly distributed in the old city center of Guangzhou and were significantly shaped by meteorological, land-use and human factors. Meteorological factors including minimum temperature, maximum temperature, atmospheric pressure and relative humidity were correlated with the transmission of dengue fever. Minimum temperature, maximum temperature and relative humidity presented a statistically significant positive correlation with dengue fever cases, while atmospheric pressure presented statistically significant negative correlation. Minimum temperature, maximum temperature, atmospheric pressure and humidity have lag effects on the transmission of dengue fever. The population, community age, subway network density, road network density and ponds presented a statistically significant positive correlation with the number of dengue fever cases, and the interaction among land-use and human factors could enhance dengue fever transmission. The ponds were the most important interaction factors, which might strengthen the influence of other factors on dengue fever transmission. Our findings have implications for pre-emptive dengue fever control.

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

Cited by 36 publications

References 29 publications

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

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

Fatores associados a casos de Dengue na área industrial brasileira: um estudo ecológico

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

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