scholarly journals Environmental risk factors of West Nile virus infection of horses in the Senegal River basin

2010 ◽  
Vol 138 (11) ◽  
pp. 1601-1609 ◽  
Author(s):  
V. CHEVALIER ◽  
A. DUPRESSOIR ◽  
A. TRAN ◽  
O. M. DIOP ◽  
C. GOTTLAND ◽  
...  

SUMMARYIn 2005, a serological study was carried out on horses in five ecologically contrasted zones of the Senegal River basin (Senegal) to assess West Nile virus (WNV) transmission and investigate underlying environmental risk factors. In each study zone, horses were randomly selected and blood samples taken. A land-cover map of the five study areas was built using two satellite ETM+ images. Blood samples were screened by ELISA for anti-WNV IgM and IgG and positive samples were confirmed by seroneutralization. Environmental data were analysed using a principal components analysis. The overall IgG seroprevalence rate was 85% (n=367; 95% CI 0·81–0·89). The proximity to sea water, flooded banks and salted mudflats were identified as protective factors. These environmental components are unfavourable to the presence of Culex mosquitoes suggesting that in Senegal, the distribution of the vector species is more limiting for WNV transmission than for the hosts' distribution.

2009 ◽  
Vol 23 (4) ◽  
pp. 357-366 ◽  
Author(s):  
L. M. V. RIOS ◽  
J.-J. SHEU ◽  
J. F. DAY ◽  
J. E. MARUNIAK ◽  
K. SEINO ◽  
...  

2008 ◽  
Vol 33 (5) ◽  
pp. 461-471 ◽  
Author(s):  
Michael P. Ward ◽  
Courtney A. Wittich ◽  
Geoffrey Fosgate ◽  
Raghavan Srinivasan

2017 ◽  
Vol 145 (13) ◽  
pp. 2797-2807 ◽  
Author(s):  
J. P. ROCHELEAU ◽  
P. MICHEL ◽  
L. R. LINDSAY ◽  
M. DREBOT ◽  
A. DIBERNARDO ◽  
...  

SUMMARYThe identification of specific environments sustaining emerging arbovirus amplification and transmission to humans is a key component of public health intervention planning. This study aimed at identifying environmental factors associated with West Nile virus (WNV) infections in southern Quebec, Canada, by modelling and jointly interpreting aggregated clinical data in humans and serological data in pet dogs. Environmental risk factors were estimated in humans by negative binomial regression based on a dataset of 191 human WNV clinical cases reported in the study area between 2011 and 2014. Risk factors for infection in dogs were evaluated by logistic and negative binomial models based on a dataset including WNV serological results from 1442 dogs sampled from the same geographical area in 2013. Forested lands were identified as low-risk environments in humans. Agricultural lands represented higher risk environments for dogs. Environments identified as impacting risk in the current study were somewhat different from those identified in other studies conducted in north-eastern USA, which reported higher risk in suburban environments. In the context of the current study, combining human and animal data allowed a more comprehensive and possibly a more accurate view of environmental WNV risk factors to be obtained than by studying aggregated human data alone.


2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Andrea McMahon ◽  
Abere Mihretie ◽  
Adem Agmas Ahmed ◽  
Mastewal Lake ◽  
Worku Awoke ◽  
...  

Abstract Background Despite global intervention efforts, malaria remains a major public health concern in many parts of the world. Understanding geographic variation in malaria patterns and their environmental determinants can support targeting of malaria control and development of elimination strategies. Methods We used remotely sensed environmental data to analyze the influences of environmental risk factors on malaria cases caused by Plasmodium falciparum and Plasmodium vivax from 2014 to 2017 in two geographic settings in Ethiopia. Geospatial datasets were derived from multiple sources and characterized climate, vegetation, land use, topography, and surface water. All data were summarized annually at the sub-district (kebele) level for each of the two study areas. We analyzed the associations between environmental data and malaria cases with Boosted Regression Tree (BRT) models. Results We found considerable spatial variation in malaria occurrence. Spectral indices related to land cover greenness (NDVI) and moisture (NDWI) showed negative associations with malaria, as the highest malaria rates were found in landscapes with low vegetation cover and moisture during the months that follow the rainy season. Climatic factors, including precipitation and land surface temperature, had positive associations with malaria. Settlement structure also played an important role, with different effects in the two study areas. Variables related to surface water, such as irrigated agriculture, wetlands, seasonally flooded waterbodies, and height above nearest drainage did not have strong influences on malaria. Conclusion We found different relationships between malaria and environmental conditions in two geographically distinctive areas. These results emphasize that studies of malaria-environmental relationships and predictive models of malaria occurrence should be context specific to account for such differences.


2021 ◽  
Author(s):  
Andrea McMahon ◽  
Abere Mihretie ◽  
Adem Agmas Ahmed ◽  
Mastewal Lake ◽  
Worku Awoke ◽  
...  

Abstract Background Despite global intervention efforts, malaria remains a major public health concern in many parts of the world. Understanding geographic variation in malaria patterns and their environmental determinants can support targeting of malaria control and development of elimination strategies. We used multiple sources of remotely-sensed environmental data to analyze the influences of environmental risk factors on malaria cases caused by Plasmodium falciparum and Plasmodium vivax in two geographic settings in Ethiopia. Results We found considerable spatial variation in malaria proportion and the distribution of malaria hot spots. Spectral indices were related to land cover greenness (NDVI) and moisture (NDWI) showed an association between malaria and dry landscapes. Climatic factors, including precipitation and land surface temperature, had positive associations with malaria occurrence. Settlement structure also played an important role, with opposing relationships between settlement density and malaria for the two study areas. Variables related to land surface water, such as irrigated agriculture, wetlands, seasonally flooded waterbodies and height above nearest drainage did not influence malaria proportion. Conclusion We found different relationships between malaria and environmental conditions in two geographically distinctive areas. These results emphasize that studies of malaria-environmental relationships and predictive models of malaria occurence should be context specific to account for such differences.


2010 ◽  
Author(s):  
Thomas A. Wills ◽  
Pallav Pokhrel ◽  
Frederick X. Gibbons ◽  
James D. Sargent ◽  
Mike Stoolmiller

2012 ◽  
Author(s):  
M. Pugliatti ◽  
I. Casetta ◽  
J. Drulovic ◽  
E. Granieri ◽  
T. Holmøy ◽  
...  

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