<html><head><meta http-equiv="content-type" content="text/html; charset=utf-8"></head><body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div><font size="2">We are pleased to announce and invite you to the following talk in our FDS seminar series:</font></div><div><font size="2"><br></font></div><div><font size="2">„On Policy-Relevant Effects in the Presence of Interference“</font></div><div><font size="2">Mats Stensrud, EPFL, Lausanne</font></div><div><font size="2"><br></font></div><div><font size="2">Date and Time: Thursday, 5 December 2024, 16.15 - 17.15 (Zurich)</font></div><div><font size="2">Place: ETH Zurich, HG D 7.1</font></div><div><font size="2"><br></font></div><div><font size="2">Abstract: The exposure of an individual i often affects the outcome of another individual j. A prominent example occurs in infectious disease settings, where vaccinating one individual can reduce disease transmission and thereby affect the health outcomes of others. This spillover effect is a type of interference, which implies that individuals cannot plausibly be perceived as independent and identically distributed (iid). Extensive methodological research has recently been motivated by interference problems and the violation of conventional iid assumptions. However, despite the growing interest in the topic, there remains controversy over whether and when existing methods capture effects of practical interest. In this talk, I will present causal methodology—motivated by infectious disease settings—for addressing interference. The central idea is to consider estimands that are insensitive to the interference structure. I will argue that these estimands have a clear interpretation and can be used to guide decisions made by, for example, doctors and patients facing infectious diseases. The methodology will be illustrated with examples of the effects of vaccines against HIV and influenza.</font></div><div><font size="2"><br></font></div><div><font size="2">Organisers: A. Bandeira, H. Bölcskei, J. Peters, F. Yang</font></div><div><font size="2"><br></font></div><div><font size="2"><br></font></div><div><font size="2">Seminar website: https://math.ethz.ch/sfs/news-and-events/data-science-seminar.html</font></div></body></html>