Yale University EliScholar – A Digital Platform for Scholarly Publishing at Yale Public Health Theses School of Public Health 1-1-2019 Analysis Of Entomological Surveillance Data To Predict West Nile Virus Cases In Connecticut Lena Marie Tayo
[email protected] Follow this and additional works at: https://elischolar.library.yale.edu/ysphtdl Part of the Public Health Commons Recommended Citation Tayo, Lena Marie, "Analysis Of Entomological Surveillance Data To Predict West Nile Virus Cases In Connecticut" (2019). Public Health Theses. 1897. https://elischolar.library.yale.edu/ysphtdl/1897 This Open Access Thesis is brought to you for free and open access by the School of Public Health at EliScholar – A Digital Platform for Scholarly Publishing at Yale. It has been accepted for inclusion in Public Health Theses by an authorized administrator of EliScholar – A Digital Platform for Scholarly Publishing at Yale. For more information, please contact
[email protected]. Analysis of Entomological Surveillance Data to Predict West Nile Virus Cases in Connecticut Lena Marie Tayo Yale School of Public Health, Epidemiology of Microbial Diseases Master of Public Health, 2019 Advisors Leonard Munstermann, PhD Philip Armstrong, PhD ACKNOWLEDGEMENTS I gratefully acknowledge the Connecticut Agricultural Experiment Station (CAES) and Dr. Philip Armstrong for providing all mosquito surveillance and human cases data. Thanks to my thesis advisors Dr. Philip Armstrong and Dr. Leonard Munstermann for providing expert guidance and collaborating with me on this project. I also acknowledge the Statistics Lab (StatLab) at the Yale School of Public Health and Maile Phillips for her statistics advice and guidance. Thanks to my friends and family who supported me during the writing of this thesis and over the last two years.