Infectious DiseasesIdentifiability and Estimation Under the Test-negative Design With Population Controls With the Goal of Identifying Risk and Preventive Factors for SARS-CoV-2 InfectionSchnitzer, Mireille E.a,b,c; Harel, Daphnad,e; Ho, Vikkib,f; Koushik, Anitab,f; Merckx, Joannac Author Information From the aFaculty of Pharmacy, Université de Montréal, Montréal, Québec, Canada bDepartment of Social and Preventive Medicine, School of Public Health, Université de Montréal, Montréal, Québec, Canada cDepartment of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Québec, Canada dDepartment of Applied Statistics, Social Science, and Humanities, Steinhardt School of Culture Education and Human Development, New York University, New York, NY eCenter for Practice and Research at the Intersection of Information, Society, and Methodology (PRIISM), Steinhardt School of Culture Education and Human Development, New York University, New York, NY fUniversité de Montréal Hospital Research Centre (CRCHUM), Montréal, Québec, Canada. Submitted June 5, 2020; accepted May 24, 2021 M.E.S. holds a Canada Research Chair from the Canadian Institutes of Health Research (CIHR). V.H. holds a Sex and Gender Science Chair in Cancer Research from CIHR. She is currently supported by the Cancer Research Society, Fonds de recherche du Québec – Santé (FRQS) and Ministére de l'économie, de la Science et de l'Innovation du Québec (MESI). No human data were used in this methodological study. All code for simulated data generation are provided in the Supplementary Materials. J.M. is an employee of bioMérieux. This work is unrelated to her function as Director Medical Affairs, bioMérieux Canada, Inc. The other authors have declared no conflict of interest. Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com). Correspondence: Mireille E. Schnitzer, PhD, Faculty of Pharmacy, Université de Montréal, Office 2236, Pavillon Jean-Coutu, 2940, chemin de Polytechnique, Montréal, Québec H3T 1J4, Canada. E-mail: [email protected]. Epidemiology: September 2021 - Volume 32 - Issue 5 - p 690-697 doi: 10.1097/EDE.0000000000001385 Buy SDC Metrics Abstract Owing to the rapidly evolving coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, quick public health investigations of the relationships between behaviors and infection risk are essential. Recently the test-negative design (TND) was proposed to recruit and survey participants who are symptomatic and being tested for SARS-CoV-2 infection with the goal of evaluating associations between the survey responses (including behaviors and environment) and testing positive on the test. It was also proposed to recruit additional controls who are part of the general population as a baseline comparison group to evaluate risk factors specific to SARS-CoV-2 infection. In this study, we consider an alternative design where we recruit among all individuals, symptomatic and asymptomatic, being tested for the virus in addition to population controls. We define a regression parameter related to a prospective risk factor analysis and investigate its identifiability under the two study designs. We review the difference between the prospective risk factor parameter and the parameter targeted in the typical TND where only symptomatic and tested people are recruited. Using missing data directed acyclic graphs, we provide conditions and required data collection under which identifiability of the prospective risk factor parameter is possible and compare the benefits and limitations of the alternative study designs and target parameters. We propose a novel inverse probability weighting estimator and demonstrate the performance of this estimator through simulation study. Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.