Abundancia y distribución de Aedes aegypti (Diptera: Culicidae) y dispersión del dengue en Guasave Sinaloa, México

García, Cipriano; García, Lourdes Serrano; Espinosa-Carreón, T. Leticia; Ley, P César

doi:10.15517/rbt.v59i4.3424

Cited by 12 publications

(9 citation statements)

References 15 publications

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“…This shift in resistance has occurred at scale throughout the country and is not restricted to small areas where selection has been increased, for example by the introduction of pyrethroid-based IRS. Similar shifts have been noted in Aedes aegypti in Mexico (24), which is currently underpinning a major outbreak of dengue hemorrhagic fever (25). The speed at which this resistance has appeared and spread emphasizes the importance of high-quality routine screening if resistance is to be detected at an early stage.…”

Section: Resultsmentioning

confidence: 58%

Impact of pyrethroid resistance on operational malaria control in Malawi

Wondji

Coleman

Kleinschmidt

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

122

131

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The impact of insecticide resistance on insect-borne disease programs is difficult to quantify. The possibility of eliminating malaria in high-transmission settings is heavily dependent on effective vector control reducing disease transmission rates. Pyrethroids are the dominant insecticides used for malaria control, with few options for their replacement. Their failure will adversely affect our ability to control malaria. Pyrethroid resistance has been selected in Malawi over the last 3 y in the two major malaria vectors Anopheles gambiae and Anopheles funestus , with a higher frequency of resistance in the latter. The resistance in An. funestus is metabolically based and involves the up-regulation of two duplicated P450s. The same genes confer resistance in Mozambican An. funestus , although the levels of up-regulation differ. The selection of resistance over 3 y has not increased malaria transmission, as judged by annual point prevalence surveys in 1- to 4-y-old children. This is true in areas with long-lasting insecticide-treated nets (LLINs) alone or LLINs plus pyrethroid-based insecticide residual spraying (IRS). However, in districts where IRS was scaled up, it did not produce the expected decrease in malaria prevalence. As resistance increases in frequency from this low initial level, there is the potential for vector population numbers to increase with a concomitant negative impact on control efficacy. This should be monitored carefully as part of the operational activities in country.

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Section: Resultsmentioning

confidence: 58%

Impact of pyrethroid resistance on operational malaria control in Malawi

Wondji

Coleman

Kleinschmidt

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

122

131

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“…Many studies have identified an overall increased risk of dengue for rainfall and temperature at lag weeks 9–16 [21,61]. A two months lag period for rainfall was documented in other statistical and mathematical modelling studies [22,62,63]. The vectorial capacity of Aedes mosquitoes is highly dependent on temperature.…”

Section: Discussionmentioning

confidence: 99%

A Spatial Hierarchical Analysis of the Temporal Influences of the El Niño-Southern Oscillation and Weather on Dengue in Kalutara District, Sri Lanka

Liyanage

Tissera

Sewe

et al. 2016

IJERPH

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Dengue is the major public health burden in Sri Lanka. Kalutara is one of the highly affected districts. Understanding the drivers of dengue is vital in controlling and preventing the disease spread. This study focuses on quantifying the influence of weather variability on dengue incidence over 10 Medical Officer of Health (MOH) divisions of Kalutara district. Weekly weather variables and data on dengue notifications, measured at 10 MOH divisions in Kalutara from 2009 to 2013, were retrieved and analysed. Distributed lag non-linear model and hierarchical-analysis was used to estimate division specific and overall relationships between weather and dengue. We incorporated lag times up to 12 weeks and evaluated models based on the Akaike Information Criterion. Consistent exposure-response patterns between different geographical locations were observed for rainfall, showing increasing relative risk of dengue with increasing rainfall from 50 mm per week. The strongest association with dengue risk centred around 6 to 10 weeks following rainfalls of more than 300 mm per week. With increasing temperature, the overall relative risk of dengue increased steadily starting from a lag of 4 weeks. We found similarly a strong link between the Oceanic Niño Index to weather patterns in the district in Sri Lanka and to dengue at a longer latency time confirming these relationships. Part of the influences of rainfall and temperature can be seen as mediator in the causal pathway of the Ocean Niño Index, which may allow a longer lead time for early warning signals. Our findings describe a strong association between weather, El Niño-Southern Oscillation and dengue in Sri Lanka.

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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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Abundancia y distribución de Aedes aegypti (Diptera: Culicidae) y dispersión del dengue en Guasave Sinaloa, México

Cited by 12 publications

References 15 publications

Impact of pyrethroid resistance on operational malaria control in Malawi

Impact of pyrethroid resistance on operational malaria control in Malawi

A Spatial Hierarchical Analysis of the Temporal Influences of the El Niño-Southern Oscillation and Weather on Dengue in Kalutara District, Sri Lanka

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

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