This course is multidisciplinary in nature, and aims to equip the global audience of interested lay people, people with chronic disease, public health researchers, health clinicians, students, administrators, and researchers to reflect on the overall impact of the burden of chronic disease . It shows how all chronic diseases (obesity, diabetes, cardiovascular disease, chronic obstructive pulmonary disease, and cancer) are related by a set of common causes, and that such diseases should be tackled, not individually, but as part of a complex system, with interrelated contributing factors. These factors are genetic, environmental, psychological, economic, social, developmental, and media related. The Charles Perkins Centre at the University of Sydney is a unique interdisciplinary education and research hub which seeks solutions to chronic disease through a complex systems approach. Academics in many disciplines (in Science and Medicine, but also in Architecture, Humanities, Law etc) work in a collaborative fashion to produce novel solutions to the problems of chronic disease. All contributors and participants in this course are members of the Charles Perkins Centre and will speak from the unique interdisciplinary perspective that this Centre affords. The course will describe a complex systems approach as the most productive way to ease the burden of chronic disease. It then describes these diseases in detail, their risk factors, and the environmental and biological factors that have led to the current epidemic of obesity, diabetes and cardiovascular disease. Finally, the solutions – and more importantly the process for finding solutions- is the subject of the last module. No one approach by itself can ever be the answer, and certainly not a simple diet and exercise approach. The entire course consists of 5 content modules, plus an extra module for completing assignments and discussions, and takes about 6 weeks to complete. Completion certificates are issued on the basis of participation in all 6 modules. What you'll learn: - How the Charles Perkins Centre recruits interdisciplinary teams to ease the burden of chronic disease - How a complex systems approach is necessary to provide solutions to a complex problem - The fundamentals of chronic disease research and where it is heading - The biggest risk factors for chronic disease and their global incidence - The biological, genetic, social, regulatory, and other influences that have inflated these risk factors - How to provide solutions globally for the reduction of chronic disease

Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, we'll focus on the use of simple regression methods to determine the relationship between an outcome of interest and a single predictor via a linear equation. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include logistic regression, confidence intervals, p-values, Cox regression, confounding, adjustment, and effect modification.

This course is designed for administrators, advocates, policy makers, clinicians, and service users. It will give you the background, recommendations, and tools you need to address issues related to high quality maternal and newborn care in your own setting. In particular, you will learn about the evidence behind implementing the midwifery model of care as a means to advancing the health and wellbeing of mothers and babies globally. The modules in this course are structured around the Quality Maternal and Newborn Care Framework, first published in the landmark 2014 Lancet Series on Midwifery. You will learn from nearly 20 expert contributors as they discuss their research and personal experiences in low, middle, and high resource settings.

This course covers approaches for modelling treatment of infectious disease, as well as for modelling vaccination. Building on the SIR model, you will learn how to incorporate additional compartments to represent the effects of interventions, such the effect of vaccination in reducing susceptibility. You will learn about ‘leaky’ vaccines and how to model them, as well as different types of vaccine and treatment effects. It is important to consider basic relationships between models and data, so, using the basic SIR model you have developed in course 1, you will calibrate this model to epidemic data. Performing such a calibration by hand will help you gain an understanding of how model parameters can be adjusted in order to capture real-world data. Lastly in this course, you will learn about two simple approaches to computer-based model calibration - the least-squares approach and the maximum-likelihood approach; you will perform model calibrations under each of these approaches in R.

In your previous course, you learned some medical interventions and skills to keep newborns healthy in the days and weeks after they have been born. In this course, you will learn what some additional skills that medical providers do to keep babies healthy. The Newborn Assessment Course will walk you through the physical examination from head to toe. You are going to learn that this is so much we can discover just by looking at a baby. And yes, we will be listening too, and discussing how medical equipment, such as a stethoscope or a pulse oximeter, can help in your exam. You will begin to be able to distinguish some normal findings from some abnormal findings. In all of the modules up until this one, we have discussed abnormalities or illnesses of newborns. In order to understand and recognize what is not normal, it is worthwhile to be clear on what is normal. In this module, Dr. Kohn will demonstrate how to examine a very well newborn. Aside from the obvious size differences and the unbelievable cuteness of newborns relative to adults, there are the influences of fetal development and transition that impact the newborn exam. Keep in mind that your exam may be the first physical evaluation that this baby has in its life! Our task as providers of health care to newborns is to detect which of the many seemingly well babies has an underlying health care problem that needs to be addressed. Previously, we reviewed the screening method that we use to look for critical congenital heart disease. In this module, we will cover the surveillance technique, that is, the physical findings that should make us suspect a newborn might have congenital heart disease. Nearly 41% of children who die under the age of 5 are less than 28 days old. The first month of life is a particularly vulnerable time for these little ones. In this module, you will learn some signs or symptoms that are concerning in newborns in the first month of life, and that need medical attention. You will also learn some common findings that are concerning to parents, but not concerning medically. Those are conditions for which reassurance and/or watchful waiting is appropriate. Distinguishing between concerning and benign conditions will help you ensure the safety and health of newborn babies! A newborn baby is an amazing beautiful life filled with hope. Unfortunately, many babies die or experience preventable harm even in 21st century. It is imperative that babies who are born healthy get off to a healthy start in the first month of life. There are some easy tenets of care to implement that help ensure that babies and families get off to a healthy start no matter where they are in the world. In this specialization learners will acquire the skills necessary for newborn baby care to optimize their health in the hours, days and weeks after they are born.

Epidemiological studies can provide valuable insights about the frequency of a disease, its potential causes and the effectiveness of available treatments. Selecting an appropriate study design can take you a long way when trying to answer such a question. However, this is by no means enough. A study can yield biased results for many different reasons. This course offers an introduction to some of these factors and provides guidance on how to deal with bias in epidemiological research. In this course you will learn about the main types of bias and what effect they might have on your study findings. You will then focus on the concept of confounding and you will explore various methods to identify and control for confounding in different study designs. In the last module of this course we will discuss the phenomenon of effect modification, which is key to understanding and interpreting study results. We will finish the course with a broader discussion of causality in epidemiology and we will highlight how you can utilise all the tools that you have learnt to decide whether your findings indicate a true association and if this can be considered causal.

Often called “the cornerstone” of public health, epidemiology is the study of the distribution and determinants of diseases, health conditions, or events among populations and the application of that study to control health problems. By applying the concepts learned in this course to current public health problems and issues, students will understand the practice of epidemiology as it relates to real life and makes for a better appreciation of public health programs and policies. This course explores public health issues like cardiovascular and infectious diseases – both locally and globally – through the lens of epidemiology.

Introduces students to the core principles of health equity research. Covers topics such as defining health equity, engaging community and policy stakeholders, patient-centeredness, cultural competence, and dissemination of research findings. Content will recognize different geographic, cultural, and social contexts where health inequities occur.

This History of Medical Cannabis course is designed to have you think critically about past, present, and future research on the health effects of cannabis by developing a more nuanced understanding of the barriers to research as well as different approaches to research. You will learn about the history of cannabis cultivation, the legal history of cannabis or "marijuana", and the obstacles that led to the lack of science on its medicinal use. You will also learn how to critically evaluate research on the effects of cannabis and discuss the associated risks of using cannabis in the context of public health and epidemiological research. Finally, you will learn about how to administer cannabis products in ways that minimize risk and maximize any potential benefits. Obtaining this knowledge will be helpful in terms of informing public policy, public health, and personal decisions regarding the use of cannabis products.

Synbio is a diverse field with diverse applications, and the different contexts (e.g., gain-of-function research, biofuels) raise different ethical and governance challenges. The objective of this course is to increase learners’ awareness and understanding of ethical and policy/governance issues that arise in the design, conduct and application of synthetic biology. The course will begin with a short history of recombinant DNA technology and how governance of that science developed and evolved, and progress through a series of areas of application of synbio. Content will be presented in many forms, including not only reading and lectures, but also recorded and live interviews and discussions with scientists, ethicists and policy makers. Learners will have the opportunity to think, write and talk about the issues and challenges in their own work and in real-life case examples. A final project will engage students in the development of governance models for synbio.