Modeling environmental factors that describe the number of active off-host larval Amblyomma americanum
Eric M. Volstromer* and Sheri He
Dr. Hyun-Joo Kim and Dr. Stephanie Fore, Faculty Mentors
Amblyomma americanum, the lone star tick, has become an important vector of several pathogens. Our study determined the best model to describe larval A. americanum activity through a model averaging technique. Zero inflated negative binomial models were fit with seven environmental variables; saturation deficit, average degree days 60 days prior to sampling, precipitation total, day length, average wind speed, site, and average number of adult ticks found between 12-20 weeks prior to sampling (adult lag). Various model selection criteria were calculated for all possible models and the coefficients were averaged from their weights to build a predictive model of A. americanum larval tick count. Results indicate average degree days, day length, and adult lag to be the most important variables to determine larval tick count while site, precipitation total, wind speed, and saturation deficit were least important. These data are consistent with the literature describing seasonal patterns of activity.
Keywords: Ticks, Model Averaging, Amblyomma americanum
Topic(s):Biology
Mathematics
Presentation Type: Poster
Session: 2-8
Location: GEO
Time: 3:30