Spatial autocorrelation of West Nile virus vector mosquito abundance in a seasonally wet suburban environment

2008 ◽  
Vol 11 (1) ◽  
pp. 67-87 ◽  
Author(s):  
P. R. Trawinski ◽  
D. S. Mackay
EcoHealth ◽  
2013 ◽  
Vol 11 (1) ◽  
pp. 120-132 ◽  
Author(s):  
Lapo Mughini-Gras ◽  
Paolo Mulatti ◽  
Francesco Severini ◽  
Daniela Boccolini ◽  
Roberto Romi ◽  
...  

2010 ◽  
Vol 10 (110) ◽  
pp. 1-17 ◽  
Author(s):  
Scott R. Larson ◽  
John P. DeGroote ◽  
Lyric C. Bartholomay ◽  
Ramanathan Sugumaran

2006 ◽  
Vol 6 (3) ◽  
pp. 680-682 ◽  
Author(s):  
JASON L. RASGON ◽  
MEERA VENKATESAN ◽  
CATHERINE J. WESTBROOK ◽  
MARY CLAIRE HAUER

2019 ◽  
Vol 34 (6) ◽  
pp. 514-520
Author(s):  
Davoud Adham ◽  
Eslam Moradi-Asl ◽  
Hassan Vatandoost ◽  
Abedin Saghafipour

2008 ◽  
Vol 104 (5) ◽  
pp. 1005-1009 ◽  
Author(s):  
Antonios Michaelakis ◽  
Anastasia. P. Mihou ◽  
George Koliopoulos ◽  
Elias. A. Couladouros

Author(s):  
Hiroko Mori ◽  
Joshua Wu ◽  
Motomu Ibaraki ◽  
Franklin Schwartz

The city of Bismarck, North Dakota has one of the highest numbers of West Nile Virus (WNV) cases per population in the U.S. Although the city conducts extensive mosquito surveillance, the mosquito abundance alone may not fully explain the occurrence of WNV. Here, we developed models to predict mosquito abundance and the number of WNV cases, independently, by statistically analyzing the most important climate and virus transmission factors. An analysis with the mosquito model indicated that the mosquito numbers increase during a warm and humid summer or after a severely cold winter. In addition, river flooding decreased the mosquito numbers. The number of WNV cases was best predicted by including the virus transmission rate, the mosquito numbers, and the mosquito feeding pattern. This virus transmission rate is a function of temperature and increases significantly above 20 °C. The correlation coefficients (r) were 0.910 with the mosquito-population model and 0.620 with the disease case model. Our findings confirmed the conclusions of other work on the importance of climatic variables in controlling the mosquito numbers and contributed new insights into disease dynamics, especially in relation to extreme flooding. It also suggested a new prevention strategy of initiating insecticides not only based on mosquito numbers but also 10-day forecasts of unusually hot weather.


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