Patrick O. Pithua, BVM, MSc, PhD, DLSHTM
VA-MD College of Veterinary Medicine
205 Duck Pond Drive
Blacksburg, VA 24061
Dr. Pithua is an Associate Professor of Epidemiology in the Department of Population Health Sciences at the Virginia-Maryland College of Veterinary Medicine at Virginia Tech.
In 2016, the J. William Fulbright Foreign Scholarship Board inducted Patrick into the Fulbright Specialist roster as a Veterinary Preventive Medicine, Epidemiology, and Public Health specialist. That same year, he was awarded a Fulbright Specialist Grant for Teaching at the Faculty of Veterinary Medicine, National University of La Pampa, Argentina. Dr. Pithua won a Fulbright award to the Africa Regional Research Program and was named a Fellow of the Carnegie African Diaspora Program for strengthening collaboration in zoonotic disease research, curriculum development in applied veterinary epidemiology, and student advising.
PhD, Veterinary Medicine, Population Medicine Track, Epidemiology Minor, University of Minnesota Twin Cities
MSc, Veterinary Epidemiology, London School of Hygiene & Tropical Medicine and The Royal Veterinary College, University of London
BVM, Veterinary Medicine, Makerere University
- Emerging and endemic bacterial human diseases of animal origin
- Pathogenic human Leptospira epidemiology
- Role of zoonotic pathogens in the epidemiology of undifferentiated febrile illnesses in humans
- Emergence and persistence of antimicrobial resistance
- Acaricides resistance in ticks and their role in promoting antibiotic resistance in livestock and humans
- Ruminant health and well fare
- Colostrum management in relation to calf health and infectious disease transmission in dairy cattle [Mycobacterium avium subsp paratuberculosis, Bovine Leukemia Virus]
- Mycobacterial diseases of ruminants [i.e. Paratuberculosis and Bovine TB]
Epidemiology and Quantitative Methods in Public Health II
- The goal of this course is to introduce students to the systematic approach to data analysis, statistical computing, correct interpretation and presentation of results. The course is designed to improve your research and data-analysis expertise, refine, and maximize your analytical talents. The skills you learn from this course can be applied across the business, education, health, science, governmental, and technology fields. Note that mathematical equations or their derivations forms are not emphasized. However, candidates taking this course are required to have a basic understanding of the epidemiologic and statistical principles and data analysis. The course is not expected to convert you into an expert data analyst within 16 weeks but upon completing the course, you will have acquired skills needed to analyze and interpret cohort, case-control and cross-sectional studies by cross tabulations, stratification, and regression. In addition, you will be able to build and interpret findings from complex multivariable models after controlling for confounding.