Note: The risk of bias by domain corresponds to the highest risk of bias among outcomes by domain.
The overall risk of bias corresponds to the overall highest risk of bias assessed among outcomes.
| Bias | Author's judgement | Support for judgement |
| Confounding |
Moderate |
The analysis adjusted for most key confounders. There was no adjustment for COVID-19 symptoms at the time of potential vaccination, although we suspect this is not a serious issue for test negative studies. |
| Selection of participants into the study |
Moderate |
The study used a test-negative design. This has the potential to suffer from selection bias by being restricted to individuals getting a test, although the issues are not yet well understood. |
| Clasification of interventions |
Low |
No particular concerns in this domain - vaccination status is likely to be adequately measured. |
| Deviations from intervention |
Low |
No concerns in this domain - the study was observational. |
| Missing outcome data |
Low |
Data were fairly complete on vaccination status and confounders. Variant type missing for <5% of participants and these were excluded. |
| Measurement of the outcome |
Low |
No specific concerns. For symptomatic outcomes, propensity to get tested is unlikely to depend on vaccination status as this is a test negative design. |
| Selection of the reported results |
Moderate |
There is no evidence of a protocol or statistical analysis plan, and we have concerns that results could have been selected for reporting because of the findings. |
| Overall risk of bias |
Moderate |
|
| Overall comment | Almost all confounding domains were controlled in analysis or design, except symptoms at the time of intended vaccination. There is some potential for selection bias inherent to test-negative designs. |