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FutureBites: Predicting associations among hosts, parasites, and vectors MEMBERS Barbara Han, Jenny Dunn, Ana Rivero, Christina Faust, Stephanie Cinkovich, Michael Robert, Mathieu Legros, Duverney Chaverra Rodriguez, Marm Kilpatrick GOAL Explore the degree to which host-pathogen-vector associations are predictable on the basis of traits. Utilize this exploration to develop a better understanding of the future risk of emergence and expansion of vector- borne disease. We aim to address this broad goal via specific questions at multiple scales. PATHOGEN TRAITS What traits distinguish specialist from generalist pathogens (host and vector)? Are those traits predictable? PATHOGEN-VECTOR ASSOCIATIONS 1) What traits of genotype x genotype interactions predict transmission efficiency in vector-borne disease systems? 2) What are the outcomes of genotype x genotype interactions for multiple pathogens and a vector when there is competition at the population level and coinfection in the vector? 3) What traits distinguish vectors from non-vectors? (associations vs. competency) HOST-PATHOGEN ASSOCIATIONS What predicts the variable outcomes across multiple host species that are infected by a single pathogen? VECTOR-HOST ASSOCIATIONS What predicts associations between vector and host (such as vector preferences, selection preferences)? MODEL INTEGRATION. 1) How can we utilize models to develop testable hypotheses based on proposed analyses? 2) What are the population level consequences of adaptations? 3) How do potential adaptations alter the risk of disease emergence/expansion? 4) How will environmental changes interact with adaptations to influence expansion/emergence? Wish-list for database: Vector competence by parasite strain/species (binary associations, transmission efficacy) Existing Experience and Skills: Machine learning, phylogenetic methods, experimental design, statistical analysis, experimental infections, mathematical modelling, inference, field data collection, life table analysis, genome editing, vector genetics, stochastic modeling, genetic pest management, R, C++, Matlab, BEAST, primate malaria, avian malaria, arboviruses, mosquitoes, ticks, kissing bugs, bacteria, rodents, primates, microbats, livestock, birds, humans.
