A Test-Negative Design with Additional Population Controls Can Be Used to Rapidly Study Causes of the SARS-CoV-2 Epidemic.

Jan P Vandenbroucke; Elizabeth B Brickley ORCID logo; Christina MJE Vandenbroucke-Grauls; Neil Pearce ORCID logo; (2020) A Test-Negative Design with Additional Population Controls Can Be Used to Rapidly Study Causes of the SARS-CoV-2 Epidemic. EPIDEMIOLOGY, 31 (6). pp. 836-843. ISSN 1044-3983 DOI: 10.1097/EDE.0000000000001251
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Testing of symptomatic persons for infection with severe acute respiratory syndrome coronavirus-2 is occurring worldwide. We propose two types of case-control studies that can be carried out jointly in test settings for symptomatic persons. The first, the test-negative case-control design (TND) is the easiest to implement; it only requires collecting information about potential risk factors for Coronavirus Disease 2019 (COVID-19) from the tested symptomatic persons. The second, standard case-control studies with population controls, requires the collection of data on one or more population controls for each person who is tested in the test facilities, so that test-positives and test-negatives can each be compared with population controls. The TND will detect differences in risk factors between symptomatic persons who have COVID-19 (test-positives) and those who have other respiratory infections (test-negatives). However, risk factors with effect sizes of equal magnitude for both COVID-19 and other respiratory infections will not be identified by the TND. Therefore, we discuss how to add population controls to compare with the test-positives and the test-negatives, yielding two additional case-control studies. We describe two options for population control groups: one composed of accompanying persons to the test facilities, the other drawn from existing country-wide healthcare databases. We also describe other possibilities for population controls. Combining the TND with population controls yields a triangulation approach that distinguishes between exposures that are risk factors for both COVID-19 and other respiratory infections, and exposures that are risk factors for just COVID-19. This combined design can be applied to future epidemics, but also to study causes of nonepidemic disease.


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