Courses Taught by Peter Larson

EPID521: Introduction to Geographic Information Systems for Public Health Research

• Graduate level
• Residential
• Winter term(s) for residential students;
• 1 credit hour(s) for residential students;
• Instructor(s): Peter Larson (Residential);
• Offered Every Winter
• Prerequisites: EPID600
• Description: This course is a practical guide for how to use GIS in your work as a public health professional and will provide an understanding for why incorporating geography into study design is critical to the translation of research findings into effective health policy.
• Learning Objectives: Foundational Learning Objective: Explain the critical importance of evidence in advancing public health knowledge.

EPID592: Introduction to Spatial Epidemiology and GIS for Public Health

• Graduate level
• Online MPH only
• This is a second year course for Online students
• Fall term(s) for online MPH students;
• 4 credit hour(s) for online MPH students;
• Instructor(s): Peter Larson, Jonathan Zelner, (Online MPH);
• Offered Every Fall
• Prerequisites: None
• Advisory Prerequisites: None
• Description: In this class, students will be exposed to the conceptual foundations of spatial analysis in public health and will develop familiarity with spatial data manipulation and visualization using GIS software.’
• Learning Objectives: 1. Develop familiarity with the historical and conceptual foundations of modern spatial epidemiology. 2. Learn about the different types of spatial data used in epidemiology and public health. 3. Obtain, load, and visualize spatial datasets using ArcGIS Online.

Concentration Competencies that EPID592 Allows Assessment On

Department	Program	Degree	Competency	Specific course(s) that allow assessment
Population and Health Sciences		MPH	Compare population health indicators across subpopulations, time, and data sources	PUBHLTH515, BIOSTAT592, EPID590, EPID592, EPID643, BIOSTAT595, BIOSTAT501

EPID594: Key Concepts in Spatial Analysis

• Graduate level
• Online MPH only
• This is a second year course for Online students
• Winter term(s) for online MPH students;
• 2 credit hour(s) for online MPH students;
• Instructor(s): Peter Larson, Jonathan Zelner, (Online MPH);
• Prerequisites: EPID592
• Description: In this course, students will gain familiarity with the key issues and statistical and theoretical tools for asking and answering epidemiological questions using spatial data.
• Learning Objectives: 1. Identify challenges to causal inference using spatial data. 2. Evaluate and employ appropriate analytic methods for diverse public health questions. 3. Fit basic regression models to spatial data and evaluate model fit.

EPID595: Applied Spatial Modeling

• Graduate level
• Online MPH only
• This is a second year course for Online students
• Winter term(s) for online MPH students;
• 3 credit hour(s) for online MPH students;
• Instructor(s):
• Prerequisites: EPID 592 and EPID 594
• Description: The large availability of geographically indexed health data, along with advances in computing, have enabled the development of statistical methods for the analysis of spatial epidemiological data. This course will introduce students to the most commonly used statistical models used to understand spatial variation in disease risk.
• Learning Objectives: By the end of the course students will be able to: (i) Recognize different types of spatial data. (ii) Formulate research questions and determine the appropriate spatial statistical model to analyze the data. (iii) Understand the concept of spatial correlation and how to estimate it in point-level spatial data. (iv) Include spatial random effect in generalized linear models for the analysis of spatial data. (v) Interpret the results of a spatial generalized linear model. (vi) Perform spatial interpolation of point-referenced data over space to predict missing data at unsampled locations. (vii) Smooth disease rates and disease counts over space using multilevel hierarchical models. (viii) Understand the definition of a (disease) cluster. (ix) Obtain a kernel density estimate of the intensity function representing the likelihood of observing a disease case at a given location. (x) Identify clusters of disease cases via appropriate statistical methods. (xi) Formulate statistical models to characterize spatial variation in the distribution of disease cases.

EPID604: Applications Of Epidemiology

• Graduate level
• Residential
• Fall, Winter, Spring, Spring-Summer, Summer term(s) for residential students;
• 1-6 credit hour(s) for residential students;
• Instructor(s): Ella August, James Buskiewicz, Sara Adar, Matthew Boulton, Andrew Brouwer, Melissa Beck, Kelly Bakulski, Miatta Buxton, Joseph Eisenberg, Marisa Eisenberg, Nancy Fleischer, Betsy Foxman, Aubree Gordon, Alexis Handal, Jennifer Head, Jihyoun Jeon, Spruha Joshi, Sharon Kardia, Carrie Karvonen-Gutierrez, Lindsay Kobayashi, Peter Larson, Aleda Leis, Elizabeth Levin-Sparenberg, Lynda Lisabeth, Juan Marquez, Emily Martin, Briana Mezuk, Alison Mondul, Lewis Morgenstern, Belinda Needham, Marie O'Neill, Sung Kyun Park, C. Leigh Pearce, Laura Power, Alex Rickard, Jennifer Smith, Eduardo Villamor, Abram Wagner, Xin Wang, Douglas Wiebe, Zhenhua Yang, Jonathan Zelner, (Residential);
• Prerequisites: Instructor Permission
• Description: Application of epidemiological methods and concepts to analysis of data from epidemiological, clinical or laboratory studies. Introduction to independent research and scientific writing under faculty guidance.
• This course is cross-listed with .
• Syllabus for EPID604

EPID698: Ms Capstone In Epidemiology

• Graduate level
• Residential
• Fall, Winter term(s) for residential students;
• 3 credit hour(s) for residential students;
• Instructor(s): Staff, Sara Adar, Ella August, Kelly Bakulski, Melissa Beck, Matthew Boulton, Andrew Brouwer, James Buskiewicz, Miatta Buxton, Carol Chenoweth, Philippa Clarke, Marisa Eisenberg, Joseph Eisenberg, Nancy Fleischer, Betsy Foxman, Aubree Gordon, Alexis Handal, Sioban Harlow, Michael Hayashi, Jennifer Head, William Herman, Kirsten Herold, Tyler James, Jihyoun Jeon, Spruha Joshi, Sharon Kardia, Carrie Karvonen-Gutierrez, Mark Katz, Devon Keen, Lindsay Kobayashi, Peter Larson, Aleda Leis, Paul Lephart, Elizabeth Levin-Sparenberg, Lynda Lisabeth, Juan Marquez, Emily Martin, Dan McConnell, Briana Mezuk, Eve Mokotoff, Alison Mondul, Arnold S Monto, Hal Morgenstern, Lewis Morgenstern, Belinda Needham, Duane Newton, Gilbert Omenn, C. Leigh Pearce, Patricia A Peyser, Laura Power, Meza Rafael, Sarah Reeves, Paul Resnick, Julia Richards, Alex Rickard, Aruna Sarma, Jennifer Smith, Evan Snitkin, Howard Stein, Michael Swain, Eduardo Villamor, Abram Wagner, Xin Wang, Douglas Wiebe, Mark L Wilson, Zhenhua Yang, Jonathan Zelner, (Residential);
• Prerequisites: Enrolled in Epidemiology MS programs
• Description: This capstone research project course is designed for Epidemiology MS students (30-credit or 48-credit CESM programs). Working with their mentor, students are expected to develop an original research project to address public health problems using epidemiologic methods. Students will have the opportunity to apply what they learned in their coursework to important public health questions. Students will work with a faculty mentor to conduct a literature review, develop a research project, develop and implement an analysis plan, write up the results and discuss the implications of the findings, and present their work in the annual Epidemiology Poster Day. Students are expected to begin their capstone project in their first term and complete it in the second term of their final year (or only, for one-year programs) of training (three credits per term, for a total of six credits). The Epidemiology Master’s committee will help students find an appropriate mentor. Details regarding the structure of capstone writing products and evaluation guidelines will be provided in the MS Student Handbook.
• Learning Objectives: The learning objectives of and skills employed in this course are determined by the specific research project. The list below (which is not exhaustive) provides examples of learning objectives for this course: 1. Assess knowledge gaps in the scientific literature; 2. Develop a scientific research question designed to address a gap in the scientific literature 3. Identify appropriate data sources to address a research question; 4. Better understand the role of data in understanding public health problems; 5. Create a data collection instrument and/or collect data; 6. Analyze data (quantitative or mixed data – including both quantitative and qualitative) to test research hypotheses relevant to public health in a manner that reflects principles of epidemiology (e.g., study design, measurement, confounding, etc); 7. Generate appropriate data visualizations and/or presentations; 8. Communicate the significance, approach, and implications of epidemiological research in a written format appropriate for the target audience; 9. Complete research ethics training through the Program for the Education and Evaluation of Responsible Research and Scholarship (PEERRS). Two modules are required: Human Subjects Research Protections and Responsible Conduct of Research and Scholarship (RCRS).
• Syllabus for EPID698