Pest Management Professional, May 2017

2017 Mosquito ManageMent suppleMent what it does and does not measure visit CDC gov chikungunya modeling index html What about the accuracy of the models predictions In one study of the Americas Caribbean The model predicted the likely introduction of chikungunya virus transmission to most locations either before or at the time when the first cases were reported according to the CDC Out of the 10 locations with the highest probability of having cases after St Martin nine had reported cases by the end of April For a highly unpredictable area of scientific study 90 percent is a pretty good number It will be interesting to see this model work again on the U S mainland as it may have great potential with similar programs for other arboviral diseases such as dengue and Zika Not only can healthcare organizations use these data for treatment planning and outreach so can the pest management industry in partnering with their lead in the science Other focus areas of mosquito management innovations seem to be occurring in adult surveillance equipment such as Microsofts Project Premonition lethal oviposition traps and selflimiting genetic modification of mosquitoes Soon research data will unfold on how when and where PMPs can use them in their business models Stay tuned and happy hunting pmp White is technical director Rentokil Steritech You can reach him at gwhite@ rentokil com The past sometimes is a good indication of what the future will bring These maps show where the Aedes aegypti and A albopictus mosquitoes are or have been found in the U S and estimate their range in 2016 Source u S centerS for DiSeaSe control anD Prevention Continued From page mm7 Predicting mosquito abundance Is it possible M osquito prediction would seem to be fairly easy But as any entomologist and mosquito management practitioner understands the complexity of environmental conditions can push even the best pest management professionals PMPs into being a soothsayer the last label any of us wants to be tagged with However our science is progressing at a very fast rate to uncover not only the biology but the abiotic influences that drive mosquito abundance Meteorological data such as precipitation temperature soils vegetation topography and hydrological cycles to name a few all play a major role in the rise and fall of the mosquito biological cycles One factor our science has a good grip on is species range Monitoring of species and abundance has become a critical part of mosquito management and one need only look at species range charts to see native expanding receding or invasive ranges of studied organisms The U S Centers for Disease Control and Prevention CDC has these charts for those mosquitoes relative to vectoring human disease as well as research papers that help them predict mosquito abundance One such paper describes Using a Dynamic Hydrology Model to Predict Mosquito Abundances in Flood and Swamp Water visit TinyURL com m6mnap3 Its a comprehensive look at predicting mosquito abundance in flood plain and swamp conditions While it does not account for the human factor for the container breeding mosquitos we encounter it is a head start for the design of future models that may help us manage those species too Obviously pulling together all the abiotic biological and disease prevalence data is necessary to make good decisions for predicting management needs For now we must rely on the methodology we currently have but a new future based on solid science is just around the corner GW mm10 may 2017 pest management professional mypmp net