Literature DB >> 23617766

Spatiotemporal patterns of Aedes aegypti populations in Cairns, Australia: assessing drivers of dengue transmission.

Jennifer Duncombe1, Archie Clements, Joe Davis, Wenbiao Hu, Philip Weinstein, Scott Ritchie.   

Abstract

OBJECTIVES: To identify the meteorological drivers of dengue vector density and determine high- and low-risk transmission zones for dengue prevention and control in Cairns, Australia.
METHODS: Weekly adult female Ae. aegypti data were obtained from 79 double sticky ovitraps (SOs) located in Cairns for the period September 2007-May 2012. Maximum temperature, total rainfall and average relative humidity data were obtained from the Australian Bureau of Meteorology for the study period. Time series-distributed lag nonlinear models were used to assess the relationship between meteorological variables and vector density. Spatial autocorrelation was assessed via semivariography, and ordinary kriging was undertaken to predict vector density in Cairns.
RESULTS: Ae. aegypti density was associated with temperature and rainfall. However, these relationships differed between short (0-6 weeks) and long (0-30 weeks) lag periods. Semivariograms showed that vector distributions were spatially autocorrelated in September 2007-May 2008 and January 2009-May 2009, and vector density maps identified high transmission zones in the most populated parts of Cairns city, as well as Machans Beach.
CONCLUSION: Spatiotemporal patterns of Ae. aegypti in Cairns are complex, showing spatial autocorrelation and associations with temperature and rainfall. Sticky ovitraps should be placed no more than 1.2 km apart to ensure entomological coverage and efficient use of resources. Vector density maps provide evidence for the targeting of prevention and control activities. Further research is needed to explore the possibility of developing an early warning system of dengue based on meteorological and environmental factors.
© 2013 Blackwell Publishing Ltd.

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Year:  2013        PMID: 23617766     DOI: 10.1111/tmi.12115

Source DB:  PubMed          Journal:  Trop Med Int Health        ISSN: 1360-2276            Impact factor:   2.622


  17 in total

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2.  Predicting arboviral disease emergence using Bayesian networks: a case study of dengue virus in Western Australia.

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3.  Spatio-temporal distribution of malaria and its association with climatic factors and vector-control interventions in two high-risk districts of Nepal.

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4.  A spatial simulation model for dengue virus infection in urban areas.

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5.  Risk factors for the presence of chikungunya and dengue vectors (Aedes aegypti and Aedes albopictus), their altitudinal distribution and climatic determinants of their abundance in central Nepal.

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6.  Malaria incidence from 2005-2013 and its associations with meteorological factors in Guangdong, China.

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7.  Surveillance of dengue vectors using spatio-temporal Bayesian modeling.

Authors:  Ana Carolina C Costa; Cláudia T Codeço; Nildimar A Honório; Gláucio R Pereira; Carmen Fátima N Pinheiro; Aline A Nobre
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Review 8.  Assessing the relationship between vector indices and dengue transmission: a systematic review of the evidence.

Authors:  Leigh R Bowman; Silvia Runge-Ranzinger; P J McCall
Journal:  PLoS Negl Trop Dis       Date:  2014-05-08

9.  Spatio-temporal distribution of dengue and lymphatic filariasis vectors along an altitudinal transect in Central Nepal.

Authors:  Meghnath Dhimal; Ishan Gautam; Aljoscha Kreß; Ruth Müller; Ulrich Kuch
Journal:  PLoS Negl Trop Dis       Date:  2014-07-31

10.  A model for a chikungunya outbreak in a rural Cambodian setting: implications for disease control in uninfected areas.

Authors:  Marguerite Robinson; Anne Conan; Veasna Duong; Sowath Ly; Chantha Ngan; Philippe Buchy; Arnaud Tarantola; Xavier Rodó
Journal:  PLoS Negl Trop Dis       Date:  2014-09-11
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