Attention students! Registration for GPH Summer Courses is now available!
This year's multi-disciplinary offering of summer courses will have a unique focus on COVID-19, encouraging students to open their mind and learn how to apply their skills to benefit the well-being of various populations around the world.
Select courses are open to undergraduate students by permission of instructor.
GPH-GU 2501 Special Topics: Data Science and Machine Learning in Public Health Practice and Research (1 credit)
Prof. Rumi Chunara
Meets August 10th - August 14th; Monday - Friday 3:30 - 5:30pm
Open to all GPH and non-GPH undergraduate and graduate students.
This 5-session (2 hours each session), 1 credit course will introduce and encourage thinking around new datasets and methods in epidemiology and public health. The entire data science pipeline, from data gathering, processing, analysis and communication will be considered. Content along each part of the pipeline will include summaries of current and best practices from the literature, discussion of select exemplar research papers and methods in terms of their appropriateness in public health, and approaches to address methodological challenges. Content will be related to both infectious diseases such as COVID-19 as well as non-communicable diseases. The workshop format will be highly interactive with significant time devoted to discussion. Students will be encouraged to spend time before sessions reading identified papers. Students will also be encouraged to bring their own dataset to the course or use publicly available ones to develop their own data science project, and time in the course will be allotted for discussing specific challenges they face in their project. The main outcomes will be exposure to current research and practice in data science and health, an understanding of tradeoffs, challenges and possible approaches. We will spend the last module on discussion and potential design of future research regarding ethics in artificial intelligence (AI) specific to the public health context.
PRE-REQUISITES: This course will be a good introduction for anyone interested in learning how data science can be used in public health and biomedicine, and what kinds of skills and problems are involved. Previous exposure and experience in epidemiology, biostatistics research and/or practice will be assumed. Students should also have some experience working with data and a working knowledge of the principles of linear regression and statistics. Course examples will be in R so a working knowledge will also be required, or students should go through an online introduction prior to enrolling.
GPH-GU 2503 Special Topics: Through the COVID-19 Magnifying Glass: An Examination of Racial and SES Disparities in the U.S. (1 credit)
Prof. Melody Goodman and Prof. Danielle Ompad
Meets July 27th - July 31st; Monday - Friday 3:30 - 5:30pm
Open to all GPH and non-GPH undergraduate and graduate students.
This 5-session (2 hours each session), 1 credit, course will examine the racial, ethnic, and socioeconomic health disparities in COVID-19 infections, hospitalizations, and mortality. Session 1 will provide an overview of our current understanding of the biology, clinical manifestations, and epidemiology of COVID-19. Students’ understanding of COVID-19 health disparities will be centered in the pre-existing and entrenched health disparities in Session 2 with Session 3 specifically examining COVID-19 infections, hospitalizations, and mortality disparities. Session 4 will explore disparities in the impact of COVID-19 mitigation strategies. Finally, Session 5 will end the course with a discussion of best practices to addressing COVID-19 health disparities in the US. Using what they have learned in the course, students will write a report or op-ed type article or develop a video presentation that describes COVID-19 related health disparities in the US.
GPH-GU 2504 Special Topics: Introduction to Clinical Trials: COVID-19 as a Case Study (1 credit)
Prof. Rebecca Betensky
Meets July 6th, 8th, 15th, 22nd, and August 5th; 3:30 - 5:30pm
Open to all GPH and non-GPH undergraduate and graduate students.
This 5-session (2 hours each session), 1 credit, course will introduce students to the many facets of clinical trials, including their justification and structure, along with many real examples drawn from the over 800 COVID-19 clinical trials worldwide that have been registered as of May 5, 2020 (https://www.covid19-trials.com/). The course will cover designs and methods for the various phases of clinical trials. For each class, students will read reports on clinical trials from the medical literature that exemplify designs and issues discussed in class. Students will develop a full clinical trial design during the course.
GPH-GU 2505 Special Topics: Social Network Data Analysis with R, with Application to COVID-19 (1 credit)
Prof. Yang Feng
Meets July 26th - July 31st; Monday-Friday 9:30 - 11:30am
Open to all GPH and non-GPH undergraduate and graduate students.
This 5-session (2 hours each session), 1 credit, course will introduce students to social network data analysis with demonstrations in R. The past decade has witnessed a surge of the network data generation in the areas of technological, biological, social, and informational. This course will provide an introduction to networks. It will cover the descriptive analysis of network, network visualization, network models, and community detection. Various concepts and visualizations will be demonstrated using the R language. As a final project, the student will analyze a real network dataset from the COVID-19 pandemic and write a report.
GPH-GU 2506 Special Topics: Statistical and Epidemiological Evaluation of COVID-19 Studies (1 credit)
Profs. Rebecca Betensky, Yang Feng, Melody Goodman, Erez Hatna, Danielle Ompad
Meets July 7th - July 21st; Tuesdays and Thursdays 3:00 - 5:00pm
Open to all GPH and non-GPH undergraduate and graduate students.
This 5-session (2 hours each session), 1 credit, course will examine the rapidly evolving research on COVID-19 and engage students in its critical evaluation. An introduction to infectious disease epidemiology and modeling will be provided, as well as to the wide array of publicly available data sources for COVID-19, including databases and social media, and their use in COVID-19 research. Students will discuss research reports in the media and scientific publications and their interpretations in light of the design and data analysis of the underlying studies. Using what they have learned in the course, students will write a report or op-ed type article or develop a video presentation incorporating an infographic or data visualization that critically evaluates a particular COVID-19 topic.
GPH-GU 2507 Special Topics: The Impact of COVID-19 in Global and Environmental Health (1 credit)
Prof. Chris Dickey
Meets May 26th - July 5th; Tuesdays and Thursdays 4:55 - 5:55pm
Open to all GPH and non-GPH undergraduate and graduate students.
This course is designed to introduce students to the breadth and depth of expertise of the faculty in the Global and Environmental Public Health Program. It will not only provide students with an overview of the ongoing research and projects faculty are engaged in but will also highlight how COVID-19 has impacted their work. It will explore the implications of the pandemic on the future global health and what it means for the next generation of public health practitioners. The course will touch on a diverse set of topics, including urban health, climate change, community engagement, and health disparities in the context of COVID-19.
GPH-GU 2508 Special Topics: SAS Bootcamp for Beginners: Manage and Explore COVID-19 Data (1 credit)
Prof. Emily Goldmann and Prof. Shu (Violet) Xu
Meets July 6th - July 20th; Mondays and Thursdays 12:30 - 2:30pm
Open to all GPH and non-GPH undergraduate and graduate students.
This 5-session (2 hours per session), 1-credit course will introduce students to Statistical Analysis System (SAS®) software and provide an opportunity to gain basic knowledge of this commonly-used software by working with data related to the COVID-19 outbreak. The course will cover data management, descriptive analysis, and data visualization. Students will complete problem sets after each class to reinforce skills introduced during that class, as well as a detailed COVID-19 fact sheet as a culminating assignment that requires students to analyze COVID-19 data and present their findings. All the learning materials will be taught and performed using SAS standard version (version 9.4) and SAS University Edition. (This is a week-long course with one session every day.)
GPH-GU 1230 Advanced Introduction to Public Health Ethics (3 credits)
Prof. Michelle Dyke
Meets July 6th - August 16th; Tuesdays and Thursdays 6:00 - 8:30pm
Pre-requisites: None
This course examines the ethical foundations of public health and ethical issues that arise in the context of public health work. Topics will include, for example, balancing individual autonomy and community health, rights to health and healthcare, culturally respectful global health interventions, and the risk of generating stigma through public health campaigns. We will also discuss the ethics of public health research, exploring topics such as privacy considerations in data gathering and informed consent in a community health context.
GPH-GU 2405 Health Communications: Changing Social Norms in Theory and Practice (3 credits)
Prof. Carlos Chirinos
Meets July 6th - August 14th; Tuesdays and Thursdays 4:55 - 6:35pm
Pre-requisites: None
Open to all graduate and doctoral students; undergraduates by permission of instructor. This course provides an introduction to the theory, design, implementation, and evaluation of health communication programs.Several resources are used to allow students to acquire practical knowledge and skills in health communications planning and implementation. Case studies, resources, research tools and examples of different media channels are reviewed and analyzed to explore how to reach different target audiences with the most effective health communication interventions.