In this episode of Season 2 of SERious Epidemiology, Hailey and Matt record, then re-record due to a technical error (ooops!) a discussion on Chapter 5 on measures of association and measures of effect. We say whether we prefer risks or rates. We talk about the counterfactual, causal contrasts, valid inferences and good comparison groups. We use the phrase “living your best epi life”. And we define the difference between associations and effects. We answer whether smoking cessation programs increase the risk of being hit by a drunk driver (and if so, whether that’s causal). There is a mystery related to a mysterious death in the desert. Matt explains why he almost dropped out of intro epi. Oh and if you are wondering why this is the donut episode, Hailey sent Matt donuts after this episode after realizing (60 minutes in….) that she never pressed ‘record’ and Matt’s wife almost sent them back thinking it was a mistake since she had no idea who they were for.

In the episode we mention two papers:

Identifiability, exchangeability, and epidemiological confounding

S Greenland, JM Robins

International journal of epidemiology 15 (3), 413-419

And

Confounding in health research

S Greenland, H Morgenstern

Annual review of public health 22 (1), 189-212

In this episode of Season 2 of SERious Epidemiology, Hailey and Matt go back to chapter 4 of Modern Epidemiology but this time with Dr. Liz Stuart (who may not have trained as an epidemiologist but definitely thinks like an epidemiologist) who has so many insights on what seem like simple concepts. We also get into some of the differences in the way biostatisticians and epidemiologist think about these ideas. And she helps us with some of the disagreements Hailey and I had in the previous episode.

In this episode of Season 2 of SERious Epidemiology, Hailey and Matt dig into chapter 4 of Modern Epidemiology. We focused on the some of the basic building blocks of epidemiology, rates, proportions and prevalence. We found lots to discuss about defining and open and closed populations and the differences (or similarities?) between populations and cohorts. And we debate whether or not this is the “eat your vegetables” chapter. And Matt displays his ignorance of Olympic sports.

In this episode of Season 2 of SERious Epidemiology, Hailey and Matt go back to Chapters 2 and 3 of Modern Epidemiology but this time with guest Dr. Jay Kaufman of McGill University. We focused on the causal inference revolution and how our thinking on some of the issues in the chapter have changed over time as we learn more about these topics.

In this episode of Season 2 of SERious Epidemiology, Hailey and Matt try to finish off Chapter 3 of Modern Epidemiology given they couldn’t get it all into one episode as originally promised. We talked about potential outcomes, sufficient causes models and DAGs (very hard to do in audio only). We focus on the assumptions for causal inference. And we make a pitch for a Modern Epidemiology Audio Book…read by James Earl Jones.

In this episode of Season 2 of SERious Epidemiology, Hailey and Matt take on Chapters 2 and 3 of Modern Epidemiology… at least that was the plan, we really only got to chapter 2 so we’ll be back again in our next episode for Chapter 3. But in this episode we focused on some key insights around replicability and reproducibility. And camp color wars. You’ll have to listen to understand.

We are going in a new direction for Season 2 of SERious Epidemiology. This season Hailey and Matt are focusing exclusively on the new fourth edition of the textbook Modern Epidemiology. The textbook has played such an important role in the training of epidemiologists since the first edition was released and has taken on an even larger role within the field as more editions have come out. We will work through each chapter and talk about what key insights we got from them and we will talk to guests about their experiences with the text. In this first episode of the season, we are delighted to present our interview with Dr. Kenneth Rothman, author of the first edition and co-author of editions two through four.

Show notes:

Link to Epidemiology: An Introduction

Join Matt Fox and Hailey Banack for our final episode of the first season of SERious Epidemiology, a season which happened to take place entirely during the COVID-19 pandemic. The pandemic has raised countless public health issues for us all to consider from virus testing to health disparities to safe classrooms to vaccine distribution. For the first time (maybe ever), nearly everyone knows what epidemiology is, and we are all hopefully done with having to explain that we are not a group of skin doctors (“we study epidemics… not the epidermis”). In this episode we discuss a few pandemic-related issues particularly relevant for epidemiologists, such as whether we’ll ever have to wear work pants again, the use pre-prints and the value of peer review, and issues related to confirmation bias.

In this journal club episode, Dr. Matt Fox and Dr. Hailey Banack discuss a paper recently published in the New England Journal of Medicine by Dagan et al. on the Pfizer COVID-19 vaccine. Listen in for a real-world example of the concept of emulating a target trial and a discussion of how an epidemiologic study can be described as truly beautiful.

Reference:

The topic of this episode is lifecourse epidemiology, defined by Dr. Paola Gilsanz as the biological, behavioural and social processes that influence an individual’s health outcomes throughout their life. Join us as we discuss models commonly used in lifecourse epidemiology, such as the early life critical period model, accumulation model, and pathway model. Is lifecourse epidemiology different than social epidemiology? Is all epidemiology lifecourse epidemiology because we study individuals at some point in their lifetime? Dr. Gilsanz answers these questions for us and also highlights the importance of using different data sources depending on your question of interest and the specific types of bias that are particularly prevalent in lifecourse epidemiology.

Show notes: