In this prospective cohort study, participants were recruited between March 28 and April 17, 2020, through social media and nationwide media coverage. Eligible study participants were volunteers not tested for SARS-CoV-2 at the time of recruitment, who were 18 years or older, had a Norwegian identification number and electronic access to the secure national digital governmental identification service. All 122 453 participants signed an electronic consent form and completed an online baseline questionnaire detailing demographics, use of public transport and other possible risk factors for SARS-CoV-2 where use of public transport was one of many other questions on risk factors. The initial lockdown period in March 2020 lasted six weeks and involved closure of kindergartens, schools, gyms, bars, restaurants and major cultural and sports events. After that, there were no additional national school closures, and the population was, largely, only advised on social distancing, with restrictions reinstated from November 5, 2020.
Use of public transport was defined as the use of public or commercial buses, trams, ferries and/or trains. All participants were asked how many times (1-3 times, 4-10 times and 11 times or more) during a two-week period they used public transport (Appendix). At baseline (March 28, 2020), there were separate questions regarding use of public transport before and after March 12, 2020, whether participants had been standing (due to lack of seats) and if they travelled during rush hour. Norway’s initial lockdown started March 12, 2020.
The outcome was a SARS-CoV-2 positive nasopharyngeal or oropharyngeal swab test determined by real-time polymerase chain reaction in any accredited Norwegian microbiology laboratory reported through the Norwegian Messaging System for Infectious Diseases (MSIS) at a time point later than the date of the baseline questionnaire and before 28 January, 2021. In Norway, it is mandatory to report all cases of SARS-CoV-2 infections to MSIS. The proportion of new positive SARS-CoV-2 tests by day in Norway at the different time points can be found in Supplementary Figure S2.
We defined potential confoundersto beage (5 years categories, missing), calendar time (date of questionnaire, continuous), sex (men, women, missing), income (NOK per household and year, below 299 999, 300 000-599 999, 600 000-1 000 000, more than 1 000 000, missing), fitness (very fit, fairly fit , in bad shape, missing), smoking (never, former, current, missing), underlying medical conditions (no, yes, missing), municipality (358 different municipalities, missing).
We excluded participants with missing on use of public transport at baseline. Missing on covariates was included as a separate category in each covariate.
In the current study all participants were untested at baseline in order to avoid recall bias and self-selection bias (difference in agreement to participate) between SARS-CoV-2 positive and non-positive participants. Outcome status was obtained from accredited laboratories in order to avoid misclassification of the outcome.
Because of the small losses to follow-up and the low percentage of SARS-CoV-2 infected 10,11, cumulative incidence was used, and the association between use of public transport before and after the initial lockdown period and subsequent contraction of SARS-CoV-2 was investigated using logistic regression. All individuals who had not contracted SARS-CoV-2 by January 27, 2021, were included as controls. We estimated odds ratios (ORs) with 95% confidence intervals (CIs) adjusting for age, calendar time, gender, municipality, smoking, income level, fitness and underlying medical conditions. Trend test was performed by fitting ordinal values corresponding to exposure categories and testing whether the slope coefficient differed from zero. All analyses were performed using Stata (Stata Statistical Software, release 16, Stata Corp., College Station, TX) and R (version 3.6.2). A two-sided p-value of less than .05 was considered statistically significant. Sensitivity analyses were performed by employment area (health care workers vs. not) and by sex.