61 research outputs found

    Green Infrastructure Assessment Tools for Varying Scales in Coastal South Carolina

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    2010 S.C. water Resources Conference - Science and Policy Challenges for a Sustainable Futur

    West Nile virus infection in birds and mosquitoes, New York State, 2000.

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    West Nile (WN) virus was found throughout New York State in 2000, with the epicenter in New York City and surrounding counties. We tested 3,403 dead birds and 9,954 mosquito pools for WN virus during the transmission season. Sixty-three avian species, representing 30 families and 14 orders, tested positive for WN virus. The highest proportion of dead birds that tested positive for WN virus was in American Crows in the epicenter (67% positive, n=907). Eight mosquito species, representing four genera, were positive for WN virus. The minimum infection rate per 1,000 mosquitoes (MIR) was highest for Culex pipiens in the epicenter: 3.53 for the entire season and 7.49 for the peak week of August 13. Staten Island had the highest MIR (11.42 for Cx. pipiens), which was associated with the highest proportion of dead American Crows that tested positive for WN virus (92%, n=48) and the highest number of human cases (n=10)

    Optimal spline solutions of systems of ordinary differential equations

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    Surveillance of dengue fever virus: A review of epidemiological models and early warning systems

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    Dengue fever is one of the world’s most important vector-borne diseases. The transmission area of this disease continues to expand due to many factors including urban sprawl, increased travel and global warming. Current preventative techniques are primarily based on controlling mosquito vectors as other prophylactic measures, such as a tetravalent vaccine are unlikely to be available in the foreseeable future. However, the continually increasing dengue incidence suggests that this strategy alone is not sufficient. Epidemiological models attempt to predict future outbreaks using information on the risk factors of the disease. Through a systematic literature review, this paper aims at analyzing the different modeling methods and their outputs in terms of accurately predicting disease outbreaks. We found that many previous studies have not sufficiently accounted for the spatio-temporal features of the disease in the modeling process. Yet with advances in technology, the ability to incorporate such information as well as the socio-environmental aspect allowed for its use as an early warning system, albeit limited geographically to a local scale
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