The Corona Immunitas Digital Follow-Up eCohort to Monitor Impacts of the SARS-CoV-2 Pandemic in Switzerland: Study Protocol and First Results

Speierer, Alexander and Chocano-Bedoya, Patricia O. and Anker, Daniela and Schmid, Alexia and Keidel, Dirk and Vermes, Thomas and Imboden, Medea and Levati, Sara and Franscella, Giovanni and Corna, Laurie and Amati, Rebecca and Harju, Erika and Luedi, Chantal and Michel, Gisela and Veys-Takeuchi, Caroline and Zuppinger, Claire and Gonseth Nusslé, Semira and D'Acremont, Valérie and Tall, Ismaël and Éric, Salberg and Hélène, Baysson and Elsa, Lorthe and Francesco, Pennacchio and Anja, Frei and Marco, Kaufmann and Marco, Geigges and Erin, Ashley West and Nathalie, Schwab and Stéphane, Cullati and Arnaud, Chiolero and Christian, Kahlert and Silvia, Stringhini and Fabian, Vollrath and Nicole, Probst-Hensch and Nicolas, Rodondi and Milo A., Puhan and Viktor, von Wyl (2022) The Corona Immunitas Digital Follow-Up eCohort to Monitor Impacts of the SARS-CoV-2 Pandemic in Switzerland: Study Protocol and First Results. International Journal of Public Health, 67. ISSN 1661-8564

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Abstract

Mitigating the consequences of the ongoing Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic requires sound evidence on ever-changing medical, scientific, economic and social issues. Recent examples are the individuallevel and population-based impacts of vaccinations [1, 2]or clinical and social implications of long COVID [3, 4]. Anticipating the need for a flexible study base, a consortium was founded in Switzerland in spring 2020. The Corona Immunitas research program has been described extensively elsewhere (www.corona-immunitas.ch) [5]. The primary aim of Corona Immunitas is to assess the nationwide, populationbased seroprevalence (as measured by antibodies against nucleoid and spike proteins) of SARS-CoV-2 during different pandemic phases among randomly selected individuals from the general population, as well as in selected subgroups such as highly exposed healthcare workers or essential workers, such as bus drivers. To date, four waves of seroprevalence sampling (study phases covering different epidemiological situations) have been conducted. The first three study phases also saw an expansion of Corona Immunitas into further regions in Switzerland. The Corona Immunitas Digital Follow-Up (CI-DFU) eCohort was planned as an integral part of Corona Immunitas from the outset, and all participants of the Corona Immunitas seroprevalence study were invited to join the CI-DFU. Whilst Corona Immunitas provides individual- and population-level assessments of natural and vaccine-induced immunity levels to SARS-CoV-2, the CI-DFU was designed to longitudinally follow Corona Immunitas seroprevalence study participants and to capture self-reported new and re-infections with SARS-CoV-2. Thereby, the CI-DFU contributes to the scientific evidence base on the extent and duration of antibody-mediated immunity. In addition, the CI-DFU eCohort aims to monitor physical and mental health effects of the pandemic, the adoption of preventive measures, changes in societal perception, socioeconomic changes and vaccine uptake. Similar to the “parent” Corona Immunitas seroprevalence study, the CI-DFU is also regionally organized, thereby allowing study sites to address scientific questions of regional interests and fulfil local mandates of health authorities whilst contributing to the national monitoring via a standardized data collection protocol. This set-up has led to a decentralized organizational structure with agreed-upon data collection standards and questionnaires, which could potentially serve as a model for other longitudinal, regionally diverse research endeveaours. The present article is structured as follows. The Methods section describes the rationale, organization, and procedures of the CI-DFU eCohort. In the Results section we present the characteristics of participants enrolled during CI study phase 2 (covering 6 cantons from all language regions) compared to the general population, thus evaluating representativeness of our sample. Further, we provide preliminary descriptions of factors associated with study follow-up retention. Finally, in the Discussion section, we present advantages and challenges of the decentralized CI-DFU organization structure, provide an overview of lessons learned and an outlook on upcoming topics to be addressed by the CI-DFU.

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