2011 Annual Report
1a.Objectives (from AD-416)
Objective 1: Assess the risk of endemic arthropod vectors to transmit introduced exotic arboviruses in North America.
• Sub-objective 1.A. Determine the vector competence of the primary U.S. bluetongue virus (BTV) vector, Culicoides sonorensis, for EU-BTV-8.
• Sub-objective 1.B. Create models to assess potential population densities for biting insects that might be involved if Rift Valley fever virus was introduced to North America using ecologic and climatic factors.
Objective 2: Identify targets and evaluate tools for vector control and interruption of transmission cycles to protect livestock and humans from vector-borne pathogens.
• Sub-objective 2.A. Identify molecular components in insects that can be targeted to interrupt orbivirus transmission cycles.
• Sub-objective 2.B. Evaluate insecticide resistance of Culicoides sonorensis to common pesticides used in livestock and agricultural operations.
• Sub-objective 2.C. Provide livestock entomologists improved identification tools for North American Culex tarsalis and Aedes vexans.
1b.Approach (from AD-416)
Livestock are often heavily exposed to biting arthropods, causing a number of animal health issues and making them vulnerable to infection with a wide range of insect-borne pathogens. This research program will focus on:.
1)improving risk assessments of the potential for introduction of foreign disease agents into the U.S.,.
2)interrupting transmission cycles at the vector level,.
3)identifying viable pesticides for control of vectors, and.
4)improving vector identification and understanding of population dynamics to enable more efficient vector control. Determining the vector competence of Culicoides sonorensis for an exotic bluetongue virus (BTV-8) will give an indication of the potential risk for the spread of exotic BTV should it be introduced into North America. Targets for controlling C. sonorensis infection with orbiviruses will come through identification of insect cell receptor(s) for BTV and verification of specific genes associated with orbivirus infection in the insect using RNA interference. Determining the susceptibility of C. sonorensis to common insecticides will identify effective treatments for control of this important livestock pest. Development of predictive models to determine risk of arbovirus transmission, such as Rift Valley fever virus, based on predicted mosquito population densities and distributions will give weeks or months advance notice, allowing preventive measures to reduce or prevent animal and human disease. Understanding the population structures of Aedes vexans and Culex tarsalis through molecular data will provide useful information for field entomologists and agencies developing control strategies and for use in developing models to predict risk of arbovirus transmission.
The Netherlands strain of bluetongue serotype 8 was imported as a washed blood cell inoculum in collaboration with R. Bowen at Colorado State University. A domestic origin washed blood cell inoculum was produced by inoculating two sheep in containment laboratories at CSU. This domestic origin BTV-8 preparation will be transferred to the Biosecurity Research Institute at Kansas State University for use in vector competence studies.
In collaboration with faculty at Kansas State University, the research to identify targets for interruption of vector-borne pathogens using RNA inhibition (RNAi) has been restarted. Preliminary experiments with a potential target have been conducted but the analysis is ongoing.
In collaboration with CMAVE: (a) acquired from NASA, (b), formatted, and (c) analyzed monthly normalized difference vegetation index data North America. These data are being used (1) in the analysis of historical eco-climatic variability patterns and linkages with mosquito population dynamics drawn from mosquito trap-data and other collections, (2) characterize the potential near-real time temporal and spatial distribution of mosquito vectors, and (3) create a baseline of potential areas of risk to Rift Valley fever and other arboviruses.
In collaboration with faculty at the University of Wyoming, a degree day model for predicting when and where Rift Valley Fever virus may be transmitted in the United States in the event of an introduction. The model spatially explicit GIS-based model identifies temporal and spatial patterns that determine risk of establishment of RVFV. A web portal for information dissemination has also been created.
In collaboration with faculty at Kansas State University, a hierarchical network modeling approach was used to predict the livestock and human Rift Valley Fever virus infections. The model combined GIS, environmental, and livestock and human census data to predict the number of infections based on stochastic weather fluctuations and population densities of cattle, humans and mosquitoes.
Collected Culex tarsalis and Aedes vexans from around the United States and Canada for population genetics experiment. Used new surveillance methods including:.
1)Organic carbon dioxide production instead of dry ice and gas canisters to attract mosquitoes..
2)Light emitting diode and incandescent light traps with optimized light spectra to enhance mosquito attraction.
Predicted and monitored Rift Valley Fever outbreaks in Africa. Rift Valley Fever epidemics can cause high animal mortality and morbidity in addition to infecting humans. ARS researchers in Manhattan, Kansas and Gainesville, Florida predicted outbreaks of Rift Valley fever for 4 years running in December 2010 for Southern Africa. The outbreak was more wide spread than in the previous outbreaks of 2008, 2009 and 2010 including the Cape region of South Africa and parts of Namibia. There were also reported outbreaks of Rift Valley fever in October 2010 in Mauritania. Detecting and monitoring outbreaks in Africa helps tune models to be more precise and accurate in the event of an introduction of Rift Valley Fever into the United States.
Early warning system for Rift Valley Fever outbreak detection. Rift Valley Fever epidemics affecting animals and humans can be more easily contained if environmental conditions leading to epidemics are identified early. ARS researchers in Manhattan, KS and Gainesville, FL produced up-to-date detailed monthly reports and early warning of Rift Valley fever outbreak risk in endemic areas of sub-Saharan Africa and the Arabian Peninsula. Data and products they produced included Southern Oscillation Index, global sea surface temperature and outgoing longwave radiation, normalized difference vegetation index anomalies (for Africa and North America), and Rift Valley fever risk maps (for Africa). Early warnings helped countries prepare for outbreak conditions. These findings will help scientists detect favorable environmental conditions in the event Rift Valley Fever Virus is identified in the United States.