BEMC Talks

BEMC Talks are generally held on the first Wednesday of each month at 4pm Berlin time (GMT+01:00) with some adjustments for holidays. An hour-long lecture will be followed by an interactive group discussion with the speaker.

Currently some BEMC Talks are held in a hybrid format (in-person plus live-streaming) and others are held in a digital format only.

We encourage you to register to secure your spot. Select BEMC Talks are recorded and posted on our YouTube channel.

2023 BEMC Talks

January 11, 2023
On Optimal Treatment Regimes Assisted by Algorithms
Mats Stensrud
École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland

“Doctors and other care providers desire to implement decision rules that, when applied to individuals in the population of interest, yield the best possible outcomes. For example, the current focus on precision medicine reflects the search for individualized treatment decisions, adapted to a patient’s characteristics. In this presentation, I will introduce superoptimal regimes, which are guaranteed to outperform conventional optimal regimes. Importantly, identification of superoptimal regimes and their values require exactly the same assumptions as identification of conventional optimal regimes in several common settings, including instrumental variable settings. The superoptimal regimes can also be identified in data fusion contexts, where experimental data and (possibly confounded) observational data are available. I will present two examples that have appeared in the optimal regimes literature, illustrating that the superoptimal regimes perform better than conventional optimal regimes.”

On YouTube – watch recording

February 1, 2023
The Ethics of Adjustment
Jay Kaufman
McGill University, Montreal, Canada

“It is well-known that the conceptual basis for confounding adjustment in observational epidemiology is to mimic a randomized trial, but this does not provide a framework for descriptive studies. In particular, a major surveillance function of public health is the monitoring of social disparities, but the choice of covariate adjustments for such comparisons is not settled in the literature. This talk will propose a framework for such decisions.”

On YouTube – watch recording

March 1, 2023
Time exists so that everything doesn’t happen at once
Jeremy Labrecque
Erasmus MC, Rotterdam, Netherlands

“In the last few decades, many of the advances made in causal inference and epidemiologic methods are explicitly related to time (e.g. estimating the effects of time-varying exposures, mediation analyses). But, in this talk, I will argue that we still don’t take time seriously enough. Building off work on time-varying exposures in Mendelian randomization, I will demonstrate that many of the directed acyclic graphs we use in epidemiology oversimplify the nature of time which can lead to bias, unclear research questions and incorrect interpretations.”

May 3, 2023
The Spillover Effects of Housing Policies on Health
Craig Pollack
Johns Hopkins Bloomberg School of Public Health, Baltimore, USA

“The cost of housing is high and rising, contributing to tremendous housing instability. Policies designed to promote housing security have the potential to impact well-being and promote health equity. In this presentation, I discuss studies that investigate the spillover effect of a range of different housing policies, including policies that increase housing affordability, those enacted in response to the COVID-19 pandemic and ones designed to enable neighborhood choice. I highlight cross-sectoral approaches to data linkage that provide new information on the connection between social and health policies.”

June 7, 2023
Estimating vaccine impact using counterfactual prediction
Anabelle Wong
Max Planck Institute for Infection Biology, Berlin, Germany

Vaccine impact estimation is challenging because the population-level vaccine impact involves indirect protection of the unvaccinated, which cannot be easily assessed in traditional RCTs. In addition, estimating vaccine impact requires a counterfactual, which is difficult to obtain. In this talk, I will present an approach using LASSO regression to predict the counterfactual outcome for vaccine impact inference. There is also a discussion on its application and outlook.

Registration (in-person)

Registration (online)

July 5, 2023

August 2023 – Summer Break

September 6, 2023

October 4, 2023

November 1, 2023

December 6, 2023

Talk titles/descriptions are subject to change. Use the links to register in advance. Space is limited!