Changes in dengue risk potential in Hawaii, USA, due to climate variability and change

Kolivras, Korine N.

doi:10.3354/cr00861

Cited by 36 publications

(26 citation statements)

References 33 publications

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“…() that climate extremes are more critical for human health than changes in means. Following Aiken et al (), study results suggest that the impact of increased rainfall on dengue/DHF incidence is enhanced following a period of rainfall deficit associated with the El Nino phase, a pattern observed also by Kolivras () in Hawaii.…”

Section: Discussionsupporting

confidence: 77%

The variable impact of ENSO events on regional dengue/DHF in Indonesia

Arcari

Tapper

2017

Singap J Trop Geogr

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Although studies have demonstrated significant associations between ENSO events and dengue fever, few have explored regional impacts on dengue fever of separate events. This study explores the impacts of two ENSO events on regional patterns of dengue/ dengue haemorrhagic fever (DHF) incidence in Indonesia. Data consist of monthly cases of dengue/DHF from 1992 to 2001 for each of Indonesia's 27 provinces, and monthly figures for rainfall, rainfall anomalies, temperature, relative humidity and the Southern Oscillation Index (SOI). We conducted Pearson correlation analyses for each independent variable against dengue/DHF incidence, using a direct month-by-month correlation and applying a lag of between one and six months to each variable with respect to dengue/DHF incidence. Based on the SOI value, we identified two ENSO events between 1992 and 2001. To explore each event, we created two dummy variables and in regression analyses for eight provinces. The variance of between 12.9 per cent and 24.5 per cent in provincial dengue/DHF incidence is explained by two or three climate variables in each of the provinces (p < 0.01 to 0.1). During the 1997/98 event, the explained variance increased by between 7 per cent and 15 per cent in provinces whose climate regimes were most affected by this event. This study demonstrates that indicators of ENSO such as the SOI may assist in the forecast of potential dengue/DHF incidence and distribution in Indonesia.

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Section: Discussionsupporting

confidence: 77%

The variable impact of ENSO events on regional dengue/DHF in Indonesia

Arcari

Tapper

2017

Singap J Trop Geogr

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“…Kolivras (2010) estimated intraannual climate-induced range changes of Ae. albopictus in Hawaii using a geographic information system (GIS), climate data, and the known habitat of the mosquito.…”

Section: Resultsmentioning

confidence: 99%

Climate and Dengue Transmission: Evidence and Implications

Morin¹,

Comrie

Ernst

2013

Environ Health Perspect

456

390

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Background: Climate influences dengue ecology by affecting vector dynamics, agent development, and mosquito/human interactions. Although these relationships are known, the impact climate change will have on transmission is unclear. Climate-driven statistical and process-based models are being used to refine our knowledge of these relationships and predict the effects of projected climate change on dengue fever occurrence, but results have been inconsistent.Objective: We sought to identify major climatic influences on dengue virus ecology and to evaluate the ability of climate-based dengue models to describe associations between climate and dengue, simulate outbreaks, and project the impacts of climate change.Methods: We reviewed the evidence for direct and indirect relationships between climate and dengue generated from laboratory studies, field studies, and statistical analyses of associations between vectors, dengue fever incidence, and climate conditions. We assessed the potential contribution of climate-driven, process-based dengue models and provide suggestions to improve their performance.Results and Discussion: Relationships between climate variables and factors that influence dengue transmission are complex. A climate variable may increase dengue transmission potential through one aspect of the system while simultaneously decreasing transmission potential through another. This complexity may at least partly explain inconsistencies in statistical associations between dengue and climate. Process-based models can account for the complex dynamics but often omit important aspects of dengue ecology, notably virus development and host–species interactions.Conclusion: Synthesizing and applying current knowledge of climatic effects on all aspects of dengue virus ecology will help direct future research and enable better projections of climate change effects on dengue incidence.Citation: Morin CW, Comrie AC, Ernst KC. 2013. Climate and dengue transmission: evidence and implications. Environ Health Perspect 121:1264–1272; http://dx.doi.org/10.1289/ehp.1306556

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“…GIS and climate data analysis done in Hawaii show intra-annual climate variations inducing changes in A . albopictus habitats [17]. High dengue incidence is associated with areas of less rainfall and warmer temperatures as reported by a Caribbean study.…”

Section: Introductionmentioning

confidence: 99%

Effect of Climatic Factors and Population Density on the Distribution of Dengue in Sri Lanka: A GIS Based Evaluation for Prediction of Outbreaks

et al. 2017

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Dengue is one of the major hurdles to the public health in Sri Lanka, causing high morbidity and mortality. The present study focuses on the use of geographical information systems (GIS) to map and evaluate the spatial and temporal distribution of dengue in Sri Lanka from 2009 to 2014 and to elucidate the association of climatic factors with dengue incidence. Epidemiological, population and meteorological data were collected from the Epidemiology Unit, Department of Census and Statistics and the Department of Meteorology of Sri Lanka. Data were analyzed using SPSS (Version 20, 2011) and R studio (2012) and the maps were generated using Arc GIS 10.2. The dengue incidence showed a significant positive correlation with rainfall (p<0.0001). No positive correlation was observed between dengue incidence and temperature (p = 0.107) or humidity (p = 0.084). Rainfall prior to 2 and 5 months and a rise in the temperature prior to 9 months positively correlated with dengue incidence as based on the auto-correlation values. A rise in humidity prior to 1 month had a mild positive correlation with dengue incidence. However, a rise in humidity prior to 9 months had a significant negative correlation with dengue incidence based on the auto-correlation values. Remote sensing and GIS technologies give near real time utility of climatic data together with the past dengue incidence for the prediction of dengue outbreaks. In that regard, GIS will be applicable in outbreak predictions including prompt identification of locations with dengue incidence and forecasting future risks and thus direct control measures to minimize major outbreaks.

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Changes in dengue risk potential in Hawaii, USA, due to climate variability and change

Cited by 36 publications

References 33 publications

The variable impact of ENSO events on regional dengue/DHF in Indonesia

The variable impact of ENSO events on regional dengue/DHF in Indonesia

Climate and Dengue Transmission: Evidence and Implications

Effect of Climatic Factors and Population Density on the Distribution of Dengue in Sri Lanka: A GIS Based Evaluation for Prediction of Outbreaks

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