scholarly journals Spatial distribution and infection of West Nile virus lineages 1 and 2 in France from 2015 to 2020

2021 ◽  
Vol 53 (S56) ◽  
pp. 82-82
Pathogens ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 908 ◽  
Author(s):  
Cécile Beck ◽  
Isabelle Leparc Goffart ◽  
Florian Franke ◽  
Gaelle Gonzalez ◽  
Marine Dumarest ◽  
...  

Since 2015, annual West Nile virus (WNV) outbreaks of varying intensities have been reported in France. Recent intensification of enzootic WNV circulation was observed in the South of France with most horse cases detected in 2015 (n = 49), 2018 (n = 13), and 2019 (n = 13). A WNV lineage 1 strain was isolated from a horse suffering from West Nile neuro-invasive disease (WNND) during the 2015 episode in the Camargue area. A breaking point in WNV epidemiology was achieved in 2018, when WNV lineage 2 emerged in Southeastern areas. This virus most probably originated from WNV spread from Northern Italy and caused WNND in humans and the death of diurnal raptors. WNV lineage 2 emergence was associated with the most important human WNV epidemics identified so far in France (n = 26, including seven WNND cases and two infections in blood and organ donors). Two other major findings were the detection of WNV in areas with no or limited history of WNV circulation (Alpes-Maritimes in 2018, Corsica in 2018–2019, and Var in 2019) and distinct spatial distribution of human and horse WNV cases. These new data reinforce the necessity to enhance French WNV surveillance to better anticipate future WNV epidemics and epizootics and to improve the safety of blood and organ donations.


2006 ◽  
Vol 6 (3) ◽  
pp. 283-295 ◽  
Author(s):  
Maria A. Diuk-Wasser ◽  
Heidi E. Brown ◽  
Theodore G. Andreadis ◽  
Durland Fish

2017 ◽  
Vol 64 ◽  
pp. 20-26 ◽  
Author(s):  
Yaniv Lustig ◽  
Zalman Kaufman ◽  
Ella Mendelson ◽  
Laor Orshan ◽  
Emilia Anis ◽  
...  

2018 ◽  
Author(s):  
Sifat A. Moon ◽  
Lee W. Cohnstaedt ◽  
D. Scott McVey ◽  
Caterina M. Scoglio

AbstractWest Nile virus (WNV)—a mosquito-borne arbovirus— entered the USA through New York City in 1999 and spread to the contiguous USA within three years while transitioning from epidemic outbreaks to endemic transmission. The virus is transmitted by vector competent mosquitoes and maintained in the avian populations. WNV spatial distribution is mainly determined by the movement of residential and migratory avian populations. We developed an individual-level heterogeneous network framework across the USA with the goal of understanding the long-range spatial distribution of WNV. To this end, we proposed three distance dispersal kernels model: 1) exponential—short-range dispersal, 2) power-law—long-range dispersal in all directions, and 3) power-law biased by flyway direction—long-range dispersal only along established migratory routes. To select the appropriate dispersal kernel we used the human case data and adopted a model selection framework based on approximate Bayesian computation with sequential Monte Carlo sampling (ABC-SMC). From estimated parameters, we find that the power-law biased by flyway direction kernel is the best kernel to fit WNV human case data, supporting the hypothesis of long-range WNV transmission is mainly along the migratory bird flyways. Through extensive simulation from 2014 to 2016, we proposed and tested hypothetical mitigation strategies and found that mosquito population reduction in the infected states and neighboring states is potentially cost-effective.Author summaryThe underlying pattern of West Nile virus (WNV) geographic spread across the United States is not completely clear, which is a necessary step for continental or state level mitigation strategies to reduce WNV transmission. We report a network model that explains the geographic spread of WNV in the United States. West Nile virus is a mosquito-borne pathogen that infects many avian species with different movement ranges. From our research, we found that migration patterns and routes play an essential role in the WNV spatial distribution. The virus spreads in all directions at short distances because of local birds and short-distance migratory birds. However, the virus also disperses long distances along the avian migratory routes. Our model is designed to be flexible and therefore can be used to explore spreading patterns of other infectious diseases in other geographic locations.


ASHA Leader ◽  
2004 ◽  
Vol 9 (9) ◽  
pp. 10-13
Author(s):  
Susan Brady ◽  
Rhonda Miserendino ◽  
Noel Rao
Keyword(s):  

2005 ◽  
Vol 39 (8) ◽  
pp. 10
Author(s):  
PATRICE WENDLING
Keyword(s):  

2005 ◽  
Vol 38 (8) ◽  
pp. 55
Author(s):  
MICHELE G. SULLIVAN
Keyword(s):  

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