Date of Award




Document Type

Master's Thesis

Degree Name

Master of Science (MS)


Department of Epidemiology and Biostatistics



Content Description

1 online resource (ii, pages) : illustrations, color maps.

Dissertation/Thesis Chair

Bryon Backenson

Committee Members

Melissa Prusinski, Shiguo Jiang


Anaplasmosis, Babesiosis, Climate, Ixodes scapularis, Landscape, Zero-inflated negative binomial regression, Tick-borne diseases

Subject Categories

Biostatistics | Ecology and Evolutionary Biology | Epidemiology


Human granulocytic anaplasmosis (HGA) and human babesiosis are tick-borne diseases spread by Ixodes scapularis (the blacklegged or deer tick) and are the result of infection with Anaplasma phagocytophilum and Babesia microti, respectively. In New York State (NYS), incidence rates of these diseases increased concordantly until around 2013, when rates of HGA began to increase more rapidly than human babesiosis, and the spatial extent of the diseases diverged. Surveillance data of tick-borne pathogens (2007 to 2018) and reported human cases of HGA (n=4,297) and human babesiosis (n=2,986) (2013 to 2018) from the New York State Department of Health (NYSDOH) showed a positive association between the presence/temporal emergence of each pathogen and rates of disease in surrounding areas. Comparing incidence rates among demographic groups showed higher rates of HGA among all age and sex groups, in addition to white (p<0.0001), and non-Hispanic/non-Latino individuals (p<0.0001). Human babesiosis exhibited higher rates among Black (p=0.0001), Asian (p=0.0106), Other (p<0.0001) and Hispanic/Latino (p<0.0001) individuals. Open-source climate, weather and landscape data were used to build a spatially weighted zero-inflated negative binomial (ZINB) model to examine and compare associations between the environment and rates of HGA and human babesiosis. HGA and human babesiosis ZINB models indicated similar associations with forest cover, forest land cover change, and winter minimum temperature, and differing associations with elevation, urban land cover change and winter precipitation. These results indicate that tick-borne disease ecology varies between pathogens spread by Ixodes scapularis.