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Course Criteria
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3.00 Credits
Capstone Course for students in Global Health Certificate. Group analysis of a current global health problem/issue. Project involves background research, data acquisition, analysis, writing, and presentation of a substantial research paper/report at an advanced level. Consent of program director required. Instructor: Staff
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3.00 Credits
Substantive findings and policies/policy debates around selected topics in the field of population and health in industrialized and developing societies. Demographic models used to examine selected current population and health topics through framing, defining and evaluating key concepts. Topics include: end of population growth; relations between population, development and environment; health of populations; population aging; potentials for mortality increases; HIV/AIDS epidemic and resurgence of infectious diseases. Readings from disciplines of demography, sociology and public health. Topics Course. Instructor: Merli
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3.00 Credits
Topics vary depending on semester and section. Topics may include: global health ethics, field methods, health technologies, rapid needs assessment, and global health policies. Instructor: Staff
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3.00 Credits
Topics vary depending on semester and section. Topics may include: global health ethics, field methods, health technologies, rapid needs assessment, and global health policies. Instructor: Staff
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3.00 Credits
Overview of choices countries make structuring health care delivery, financing systems, cost effectiveness and cost benefit analysis. Hospitals, physicians and pharmaceuticals in low/middle income countries. Instructor: Sloan
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3.00 Credits
Individual non-research directed study in a field of special interest on a previously approved topic, under the supervision of a faculty member, resulting in a significant academic product. Open only by consent of instructor and director of Global Health Certificate program. Instructor: Staff
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3.00 Credits
Course introduces major global health problems and social, behavioral, economic, biomedical and environmental determinants of health in resource limited settings. Topics include communicable diseases i.e. HIV, malaria, tuberculosis and common childhood diseases; chronic diseases such as cancer, diabetes, cardiovascular disease and mental health; and determinants of health associated with these diseases, such as poverty, gender imbalance, culture, poor environmental sanitation, malnutrition, tobacco use, and climate change. Other topics may include health promotion, reproductive health, maternal and child health, and disaster preparedness. Departmental cosent required. Instructor: Woods
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4.00 Credits
Introduces principles of epidemiology, including disease frequency measures; measures of association; observational, experimental, and quasi-experimental study designs; validity -- confounding, selection bias, measurement error; reliability. The course also will interweave introductory biostatistics for continuous and categorical variables. Lab section in which students walk through guided data analysis on provided data set using STATA. Instructor: Pence
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3.00 Credits
Course introduces wide range of methodologies appropriate for global health research and will cover the advantages and disadvantages of each. Students develop ability to evaluate and use best methodological approach to answer their research question, Team projects and appropriate technologies also examined. Students further refine skills in designing a research project and will be taught how to design qualitative and quantitative surveys, in-depth interviews, and conduct ethnographies. Instructor: Read
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3.00 Credits
Course builds on Epidemiologic Methods I to present advanced topics in epidemiology. Topics include review of study designs including meta-analysis; intensive study of bias, including confounding, selection bias, and misclassification; missing data; sensitivity analysis; topics in regression analysis; and an introduction to the analysis of time to event data, including lifetable methods, survival curves, and Cox proportional hazards regression. Discussions of causal inference and how to read, review, and write scientific literature. Course has a weekly data analysis lab section to develop programming and statistical analysis skills. Instructor: Westreich.
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