Neil Pearce | Search arXiv

arXiv2021

The evolving usefulness of the Test-Negative Design in studying risk factors for COVID-19 due to changes in testing policy

This paper is a short extension of our previous paper [arXiv:2004.06033] about the use of the Test-Negative design to study risk factors for COVID-19 [See: PubMed and ArXiv reference below] Reason for the extension is that the conditions under which people refer themselves for testing have greatly changed: originally, in most countries priority was given to people with symptoms, but nowadays people without symptoms are also tested for different reasons, e.g., during contact tracing, or to be allowed on an (international) flight. Interestingly, this opens new possibilities to separately investigate risk factors for infection and risk factors for becoming diseased. To use this new situation to best effect, one has to think carefully about how to elucidate the different reasons for testing and what analyses one might do with the different groups.

q-bio.PE↗

arXiv2020

The test-negative design with additional population controls: a practical approach to rapidly obtain information on the causes of the SARS-CoV-2 epidemic

Testing of symptomatic persons for infection with SARS-CoV-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 demands collecting information about potential risk factors for 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 health care 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 non-epidemic disease.

q-bio.PE↗