BEGIN:VCALENDAR VERSION:2.0 PRODID:-//132.216.98.100//NONSGML kigkonsult.se iCalcreator 2.20.4// BEGIN:VEVENT UID:20250708T225033EDT-25069TxstL@132.216.98.100 DTSTAMP:20250709T025033Z DESCRIPTION:Xu Shi\, PhD\n\nAssistant Professor\, Department of Biostatisti cs\n University of Michigan\n\nWHEN: Wednesday\, February 14\, 2024\, from 3:30 to 4:30 p.m.\n\nWHERE: hybrid | 2001 ºÃÉ«TVl College Avenue\, room 114 0\; Zoom\n\nNOTE: Dr. Shi will be presenting from Michigan\n\nAbstract\n\n The test-negative design (TND) has become a standard approach to evaluate vaccine effectiveness. Despite TND's potential to reduce unobserved differ ences in healthcare-seeking behavior (HSB) between vaccinated and unvaccin ated subjects\, it remains subject to various potential biases. First\, re sidual confounding bias may remain due to unobserved HSB\, occupation as a healthcare worker\, or previous infection history. Second\, because selec tion into the TND sample is a common consequence of infection and HSB\, co llider stratification bias may exist when conditioning the analysis on tes ting\, which further induces confounding by latent HSB. Third\, generaliza bility of the results to the general population is not guaranteed. In this talk\, we present a novel approach to identify and estimate vaccine effec tiveness in the general population by carefully leveraging a pair of negat ive control exposure and outcome variables to account for potential hidden bias in TND studies. We illustrate our proposed method with extensive sim ulation and an application to COVID-19 vaccine effectiveness using data fr om the University of Michigan Health System.\n\nSpeaker bio\n\nXu Shi is a n Assistant Professor in the Department of Biostatistics at the University of Michigan. She is interested in developing statistical methods for elec tronic health records and claims data\, focusing on causal inference\, dat a harmonization across healthcare systems and comparative effectiveness an d safety research. \n DTSTART:20240214T203000Z DTEND:20240214T213000Z SUMMARY:Double Negative Control Inference in Test-Negative Design Studies o f Vaccine Effectiveness URL:/epi-biostat-occh/channels/event/double-negative-c ontrol-inference-test-negative-design-studies-vaccine-effectiveness-353630 END:VEVENT END:VCALENDAR