Spatial Patterns of High Aedes aegypti Oviposition Activity in Northwestern Argentina

被引:13
作者
Lilia Estallo, Elizabet [1 ]
Mas, Guillermo [2 ]
Vergara-Cid, Carolina [3 ]
Alberto Lanfri, Mario [4 ]
Luduena-Almeida, Francisco [1 ]
Marcelo Scavuzzo, Carlos [4 ]
Virginia Introini, Maria
Zaidenberg, Mario
Ricardo Almiron, Walter [1 ]
机构
[1] Univ Nacl Cordoba, Fac Ciencias Exactas Fis & Nat, Ctr Invest Entomol Cordoba, Inst Invest Biol & Tecnol,CONICET, RA-5000 Cordoba, Argentina
[2] INTA EEA San Luis, Villa Mercedes, San Luis, Argentina
[3] Univ Nacl Cordoba, Fac Ciencias Med, Inst Virol Dr JM Vanella, RA-5000 Cordoba, Argentina
[4] Ctr Espacial Teofilo Tabanera, Comis Nacl Actividades Espaciales CONAE, Inst Altos Estudios Espaciales Mario Gulich, Cordoba, Argentina
关键词
BUENOS-AIRES; DENGUE; EPIDEMIOLOGY; DIPTERA;
D O I
10.1371/journal.pone.0054167
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: was to analyze the spatial patterns of high Aedes aegypti oviposition activity in San Ramon de la Nueva Oran, northwestern Argentina. The location of clusters as hot spot areas should help control programs to identify priority areas and allocate their resources more effectively. Methodology: Oviposition activity was detected in Oran City (Salta province) using ovitraps, weekly replaced (October 2005-2007). Spatial autocorrelation was measured with Moran's Index and depicted through cluster maps to identify hot spots. Total egg numbers were spatially interpolated and a classified map with Ae. aegypti high oviposition activity areas was performed. Potential breeding and resting (PBR) sites were geo-referenced. A logistic regression analysis of interpolated egg numbers and PBR location was performed to generate a predictive mapping of mosquito oviposition activity. Principal Findings: Both cluster maps and predictive map were consistent, identifying in central and southern areas of the city high Ae. aegypti oviposition activity. A logistic regression model was successfully developed to predict Ae. aegypti oviposition activity based on distance to PBR sites, with tire dumps having the strongest association with mosquito oviposition activity. A predictive map reflecting probability of oviposition activity was produced. The predictive map delimitated an area of maximum probability of Ae. aegypti oviposition activity in the south of Oran city where tire dumps predominate. The overall fit of the model was acceptable (ROC = 0.77), obtaining 99% of sensitivity and 75.29% of specificity. Conclusions: Distance to tire dumps is inversely associated with high mosquito activity, allowing us to identify hot spots. These methodologies are useful for prevention, surveillance, and control of tropical vector borne diseases and might assist National Health Ministry to focus resources more effectively.
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页数:8
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