Hall-Mendelin, Sonja , Ritchie, Scott A., Johansen , Cheryl A., Zborowski , Paul, Cortis , Giles, Dandridge, Scott, Hall, Roy A., and van den Hurk, Andrew F. (2010) Exploiting mosquito sugar feeding to detect mosquito-borne pathogens. Proceedings of the National Academy of Sciences of the United States of America, 107 (25). pp. 11255-11259.

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Abstract

Arthropod-borne viruses (arboviruses) represent a global public health problem, with dengue viruses causing millions of infections annually, while emerging arboviruses, such as West Nile, Japanese encephalitis, and chikungunya viruses have dramatically expanded their geographical ranges. Surveillance of arboviruses provides vital data regarding their prevalence and distribution that may be utilized for biosecurity measures and the implementation of disease control strategies. However, current surveillance methods that involve detection of virus in mosquito populations or sero-conversion in vertebrate hosts are laborious, expensive, and logistically problematic. We report a unique arbovirus surveillance system to detect arboviruses that exploits the process whereby mosquitoes expectorate virus in their saliva during sugar feeding. In this system, infected mosquitoes captured by CO2-baited updraft box traps are allowed to feed on honey-soaked nucleic acid preservation cards within the trap. The cards are then analyzed for expectorated virus using real-time reverse transcription-PCR. In field trials, this system detected the presence of Ross River and Barmah Forest viruses in multiple traps deployed at two locations in Australia. Viral RNA was preserved for at least seven days on the cards, allowing for long-term placement of traps and continuous collection of data documenting virus presence in mosquito populations. Furthermore no mosquito handling or processing was required and cards were conveniently shipped to the laboratory overnight. The simplicity and efficacy of this approach has the potential to transform current approaches to vector-borne disease surveillance by streamlining the monitoring of pathogens in vector populations.

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