Our project has extensive field-work, epidemiological surveying, and computational modeling components. We interview humans who have experienced a leishmaniasis infection and then sample rodents and arthropods via field surveys to inform ecological and evolutionary models.
Our immediate needs are for students to help us with the epidemiological interviews, rodent and insect trapping in the field, insect identification, pathogen screening of specimens, and GIS modeling. Student volunteers will gain experience in a variety of areas, including rodent trapping, handling, and specimen sampling; sand-fly trapping, identification, and pathogen screening; GIS and species distribution modeling; epidemiological interviews and case studies. Exceptional volunteers may be offered stipends.
Students interested in the epidemiological component of the project should be highly organized, professional, and enjoy working with people. They will also need to be comfortable conducting telephone and in-person interviews and field surveys of rodents/insects (training in these areas will be provided). Preferred qualifications include speaking/writing Spanish and public health and/or epidemiology coursework.
Students interested in the field component should be self-motivated, demonstrate a willingness to learn new skills, and work both independently and cooperatively. They should enjoy the outdoors and understand that a certain amount of discomfort is associated with field work. Preferred qualifications include coursework in entomology, field ecology, mammalogy, and/or vertebrate anatomy.
Students interested in the lab component of sand-fly sample preparation and pathogen screening should be detail oriented, extremely organized, clean, and have basic microscopy skills. Preferred qualifications include entomology, public health, microbiology, and/or immunology laboratory course work.
Students interested in the geographic information systems component of the research should be familiar one of the following software packages or programming languages: ArcMAP, DivaGIS, R, Matlab, and/or Python. Preferred qualifications include GIS, geography, programming, and/or spatial statistics course work.