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Primary Submission Category: Infectious or Microbial
High resolution climate data associated characterization of medically relevant mosquito populations from urban to rural settings in Puerto Rico
Authors: Heriberto Martir Vargas,
Presenting Author: Heriberto Martir Vargas*
Mosquito borne diseases remain a public health threat in the tropical islands like Puerto Rico, an island consistently facing growing numbers of diseases carrying mosquito activity. Disease carrying mosquito species found in the Island include various genus such as Aedes (vectors for Dengue, Zika, Chikungunya and Yellow fever), Culex (vectors for West Nile Virus) and Anopheles (vectors for Malaria). Mosquito activity and population dynamics are known to be influenced by environmental conditions which vary throughout the diversity of microclimates across various rural and urban settings in the island. Therefore, this work aims to gather and link fine scale data on mosquito population dynamics to microclimate conditions. This will be achieved by using trusted mosquito collection techniques and sourcing these collections at higher temporal resolution while continuously tracking microclimate conditions at collection sites. Mosquito collection techniques include the use of human landing catches (HLCs) and BG Sentinel Pro automated mosquito traps (AMTs) assisted by lures and CO2. Environmental data such as relative humidity and temperature at capture sites will be recorded using continuous data loggers; additional data for location, elevation, atmospheric pressure, wind speed, cloud coverage and precipitation will be obtained from weather data sources. The batches collected from AMTs will be collected at least twice daily and HLCs at least three times a day. These would account for diurnal and crepuscular activity. Batches will be sorted and counted to obtain proportions of each species per collection period. This approach allows for higher data granularity when trying to understand species specific activity dependent on local climate conditions. The resulting data will significantly inform predictive outbreak modeling strategies which, in turn, impact preparedness efforts from both a vector control lens and an outbreak response lens.