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Population and Global Health

Graduate work in the Population and Global Health concentration aims to train students in population-based methods applied to animal and human health and their intersection. Population health methods are relevant to several research fields including global and public health, clinical and population medicine, and one health. Our faculty are highly collaborative with expertise in epidemiology, computational biology, infectious diseases, microbiome, global health, and animal welfare and production.

Graduate coursework will include research methods (e.g., epidemiology, computational biology, or bioinformatics) and knowledge-domain courses in the chosen field of study (e.g., animal health, animal welfare, infectious diseases, public health, global health).

Courses required for the population and global health concentration

CBS 650 Seminar: Population Medicine Forum (1 credit; minimum 3 credits total for doctoral students; minimum 2 credits total for master’s students).

CBS 775 Designing Population-based Research; Spring (3 credits)

Elective courses

At least 6 credits in elective courses need to be taken by the student in consultation with the advisor and graduate committee, and must be approved by the student’s graduate advisory committee. Possible elective course include, but are not limited to, the following:

CBS 580 Epidemiology I

CBS 586 One Health: From Philosophy to Practice

CBS 649 Issues in Preventive Medicine and Public Health

CBS 713 Zoonoses and Public Health

CBS 754 Epidemiology II

CBS 776 Infectious Disease Dynamics

BMA 560 Population Ecology

BMA 567 Modeling of Biological Systems

GN 703 Population & Quantitative Genetics

SOC 755 Global Institutions and Markets

SOC 762 Sociology of Food Systems

SOC 761 Contemporary Debates in Food & Environment

PA 511 Public Policy Analysis

PA 715 Quantitative Policy Analysis

BIT 477 Metagenomics

ST 505 Applied Nonparametric Statistics

ST 506 Sampling Animal Populations

ST 512 Experimental Statistics for Biological Sciences II

ST 520 Statistical Principles of Clinical Trials

ST 531 Experimental Design

ST 533 Applied Spatial Statistics

ST 535 Statistical Methods for Quality and Productivity Improvement

ST 537 Applied Multivariate and Longitudinal Data Analysis

ST 540 Applied Bayesian Analysis

ST 544 Applied Categorical Data Analysis

ST 745 Analysis of Survival Data

Name Email Concentration Research Emphasis
Andrew Stringer Population Medicine Antimicrobial Resistance (AMR), Infectious Disease and Community Engagement
Ben Callahan Infectious Diseases, Population Medicine Microbiome methods in health and disease
Cristina Lanzas Population Medicine Epidemiology and ecology of infectious diseases in animal and human populations
Derek Foster  Infectious Diseases, Pharmacology, Population Medicine We use pharmacokinetic modeling to understand antimicrobial resistance in enteric bacteria. 
Glen Almond  Infectious Diseases, Population Medicine Porcine production and infectious diseases.
Gustavo Machado  Population Medicine  Mathematical modeling to examine the impact of practical interventions on the subsequent disease dynamics
Isabel Gimeno Immunology, Infectious Diseases, Population Medicine Tumor viral diseases in poultry and development of the chicken immune system
Jay Levine Population Medicine Aquatic animal epidemiology and ecosystem health, microbial communities, and environmental monitoring
Kara Walker Population Medicine Behavior and health of wild primates
Kevin Anderson  Infectious Diseases, Population Medicine Infectious diseases of ruminants; emphasis on mastitis and the pathogen Staphylococcus aureus
Maria Correa Population Medicine Epidemiology, public health, and public policy
Michael Stoskopf  Pharmacology, Population Medicine Ecological Metabolomics
Monique Pairis-Garcia  Population Medicine Validating objective techniques to assess livestock welfare and behavior
Rocio Crespo Population Medicine Poultry medicine and pathology
Sid Thakur Infectious Diseases, Population Medicine Antimicrobial resistance and One Health