English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Due to the rapidly evolving COVID-19 pandemic caused by the SARS-CoV-2 virus,quick public health investigations of the relationships between behaviours andinfection risk are essential. Recently the test-negative design was proposed torecruit and survey participants who are symptomatic and being tested forSARS-CoV-2 infection with the goal of evaluating associations between thesurvey responses (including behaviours and environment) and testing positive onthe test. It was also proposed to recruit additional controls who are part ofthe general population as a baseline comparison group in order to evaluate riskfactors specific to SARS-CoV-2 infection. In this study, we consider analternative design where we recruit among all individuals, symptomatic andasymptomatic, being tested for the virus in addition to population controls. Wedefine a regression parameter related to a prospective risk factor analysis andinvestigate its identifiability under the two study designs. We review thedifference between the prospective risk factor parameter and the parametertargeted in the typical test-negative design where only symptomatic and testedpeople are recruited.  Using missing data directed acyclic graphs we provide conditions and requireddata collection under which identifiability of the prospective risk factorparameter is possible and compare the benefits and limitations of thealternative study designs and target parameters. We propose a novel inverseprobability weighting estimator and demonstrate the performance of thisestimator through simulation study.

Identifiability and estimation under the test-negative design with  population controls with the goal of identifying risk and preventive factors  for SARS-CoV-2 infection