Temporal analysis of the relationship between dengue and meteorological variables in the city of Rio de Janeiro, Brazil, 2001-2009

Gomes, Adriana Fagundes; Nobre, Aline Araújo; Cruz, Oswaldo Gonçalves

doi:10.1590/s0102-311x2012001100018

Cited by 62 publications

(67 citation statements)

References 28 publications

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“…aegypti; mosquito populations become largest when temperatures are warm and rainfall is abundant [51,52]. They are also consistent with studies indicating that dengue risk in humans is positively correlated with temperature and rainfall [53], which is likely in part due to the impacts of temperature and rainfall on vector populations [54,55].…”

Section: Discussionsupporting

confidence: 85%

Correlating Remote Sensing Data with the Abundance of Pupae of the Dengue Virus Mosquito Vector, Aedes aegypti, in Central Mexico

Moreno-Madriñán

Crosson

Eisen

et al. 2014

IJGI

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Using a geographic transect in Central Mexico, with an elevation/climate gradient, but uniformity in socio-economic conditions among study sites, this study evaluates the applicability of three widely-used remote sensing (RS) products to link weather conditions with the local abundance of the dengue virus mosquito vector, Aedes aegypti (Ae. aegypti). Field-derived entomological measures included estimates for the percentage of premises with the presence of Ae. aegypti pupae and the abundance of Ae. aegypti pupae per premises. Data on mosquito abundance from field surveys were matched with RS data and analyzed for correlation. Daily daytime and nighttime land surface temperature (LST) values were obtained from Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua cloud-free images within the four weeks preceding the field survey. Tropical Rainfall Measuring Mission (TRMM)-estimated rainfall accumulation was calculated for the four weeks preceding the field survey. Elevation was estimated through a digital elevation model (DEM). Strong correlations were found between mosquito abundance and RS-derived night LST, elevation and rainfall along the elevation/climate gradient. These findings show that RS data can be used to predict Ae. aegypti abundance, but further studies are needed to define the climatic and socio-economic conditions under which the correlations observed herein can be assumed to apply.

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Section: Discussionsupporting

confidence: 85%

Correlating Remote Sensing Data with the Abundance of Pupae of the Dengue Virus Mosquito Vector, Aedes aegypti, in Central Mexico

Moreno-Madriñán

Crosson

Eisen

et al. 2014

IJGI

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“…Typically, the most significant time lags between temperature/precipitation and dengue are found to be around 1-2 months (Arcari et al, 2007;Cheong et al, 2013;Descloux et al, 2012;García et al, 2011;Gharbi et al, 2011;Gomes et al, 2012;Jeefoo et al, 2010;Lowe et al, 2011;Wu et al, 2007) , although some studies report lags of around 3-4 months (Bi et al, 2001;Chen et al, 2012;Depradine and Lovell, 2004;Yu et al, 2011) .…”

Section: Introductionmentioning

confidence: 99%

Quantifying the added value of climate information in a spatio-temporal dengue model

Lowe

Cazelles

Rácz

et al. 2015

Stoch Environ Res Risk Assess

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Dengue is the world's most important vector-borne viral disease. The dengue mosquito and virus are sensitive to climate variability and change. Temperature, humidity and precipitation influence mosquito biology, abundance and habitat, and the virus replication speed. In this study, we develop a modelling procedure to quantify the added value of including climate information in a dengue model for the 76 provinces of Thailand, from 1982-2013. We first developed a seasonal-spatial model, to account for dependency structures from one month to the next and between provinces. We then tested precipitation and temperature variables at varying time lags, using linear and nonlinear functional forms, to determine an optimum combination of time lags to describe dengue relative risk. Model parameters were estimated using Integrated Nested Laplace Approximation (INLA).This approach provides a novel opportunity to perform model selection in a Bayesian framework, while accounting for underlying spatial and temporal dependency structures and linear or nonlinear functional forms. We quantified the additional variation explained by interannual climate variations, above that provided by the seasonal-spatial model. Overall, an additional 8% of the variance in dengue relative risk can be explained by accounting for interannual variations in precipitation and temperature in the previous month. The inclusion of nonlinear functions of climate in the model framework improved the model for 79% of the provinces. Therefore, climate forecast information could significantly contribute to a national dengue early warning system in Thailand.

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“…Porém, não se pode afirmar que estes fatores são totalmente influenciadores dos índices de dengue, embora possam contribuir para o aparecimento da doença. Ressalta-se então, que outros fatores devem ser considerados como os fatores ambientais e meteorológicos como o clima e a temperatura de cada região, conforme afirmado por Gomes;Nobre;Cruz (2012), que podem influenciar na disseminação do patógeno e favorecer a permanência destes vetores. Segundo Soares; Fragoso; Cruz (2017) existem condições favoráveis para a geração de criadouros em regiões ricas e pobres, além da temperatura, que por ser mais elevada no mês de fevereiro, aumenta o número de fêmeas de Aedes aegypti, além de fatores que de forma combinada podem contribuir para que os casos de dengue possam ter um aumento significativo.…”

Section: Resultsunclassified

Dengue e saúde pública na cidade do Rio de Janeiro, Brasil

Miceli

Fonseca

2018

Sustinere

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Dengue and public health in Rio de Janeiro city, BrazilAbstract: This article deals with the issue of sanitation in the city of Rio de Janeiro relating with the incidence of cases of dengue fever. For that, we sought to bring the concept of basic sanitation, according to the World Health Organization (who) and also address the evolution of this concept historically since the early 19TH century, with the absence of that service, until the beginning of the 21st century with the emergence of incentive laws and reports of current scenario especially with the infrastructure of the city during the year 2016 When the Olympic Games, as well as a aims to address disease cited information. The aim of this study was to compare the data provided by the city of Rio de Janeiro in relation to basic sanitation (sewage collection, with data from the years 2000 until 2014 and solid waste as the public garbage for the years 2010 and 2014) with the number of cases of dengue (2010, 2014 and 2016) in order to check how the lack of these resources interferes with the quality of life of the population and in the number of cases that illness. Noting common data 2010 and 2014, it was noted that the issues of basic sanitation does not match the contents of dengue fever cases in these same periods. It appears that you can't relate to such difficulties as causes only

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Temporal analysis of the relationship between dengue and meteorological variables in the city of Rio de Janeiro, Brazil, 2001-2009

Cited by 62 publications

References 28 publications

Correlating Remote Sensing Data with the Abundance of Pupae of the Dengue Virus Mosquito Vector, Aedes aegypti, in Central Mexico

Correlating Remote Sensing Data with the Abundance of Pupae of the Dengue Virus Mosquito Vector, Aedes aegypti, in Central Mexico

Quantifying the added value of climate information in a spatio-temporal dengue model

Dengue e saúde pública na cidade do Rio de Janeiro, Brasil

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