Advertisement

COVID Vaccine Hesitancy and Risk of a Traffic Crash

  • Donald A. Redelmeier
    Correspondence
    Requests for reprints should be addressed to Donald A. Redelmeier, MD, Sunnybrook Health Sciences Centre, G-151 2075 Bayview Ave, Toronto, ON M4N 3M5, Canada.
    Affiliations
    Evaluative Clinical Sciences, Sunnybrook Research Institute, Toronto, Ont, Canada

    Department of Medicine, University of Toronto, Ont, Canada

    Institute for Clinical Evaluative Sciences (ICES), Toronto, Ont, Canada

    Division of General Internal Medicine

    Center for Leading Injury Prevention Practice Education & Research, Sunnybrook Health Sciences Centre, Toronto, Ont, Canada
    Search for articles by this author
  • Jonathan Wang
    Affiliations
    Department of Medicine, University of Toronto, Ont, Canada

    Institute for Clinical Evaluative Sciences (ICES), Toronto, Ont, Canada
    Search for articles by this author
  • Deva Thiruchelvam
    Affiliations
    Evaluative Clinical Sciences, Sunnybrook Research Institute, Toronto, Ont, Canada

    Institute for Clinical Evaluative Sciences (ICES), Toronto, Ont, Canada
    Search for articles by this author
Published:December 02, 2022DOI:https://doi.org/10.1016/j.amjmed.2022.11.002

      Abstract

      Background

      Coronavirus disease (COVID) vaccine hesitancy is a reflection of psychology that might also contribute to traffic safety. We tested whether COVID vaccination was associated with the risks of a traffic crash.

      Methods

      We conducted a population-based longitudinal cohort analysis of adults and determined COVID vaccination status through linkages to individual electronic medical records. Traffic crashes requiring emergency medical care were subsequently identified by multicenter outcome ascertainment of all hospitals in the region over a 1-month follow-up interval (178 separate centers).

      Results

      A total of 11,270,763 individuals were included, of whom 16% had not received a COVID vaccine and 84% had received a COVID vaccine. The cohort accounted for 6682 traffic crashes during follow-up. Unvaccinated individuals accounted for 1682 traffic crashes (25%), equal to a 72% increased relative risk compared with those vaccinated (95% confidence interval, 63-82; P < 0.001). The increased traffic risks among unvaccinated individuals extended to diverse subgroups, was similar to the relative risk associated with sleep apnea, and was equal to a 48% increase after adjustment for age, sex, home location, socioeconomic status, and medical diagnoses (95% confidence interval, 40-57; P < 0.001). The increased risks extended across the spectrum of crash severity, appeared similar for Pfizer, Moderna, or other vaccines, and were validated in supplementary analyses of crossover cases, propensity scores, and additional controls.

      Conclusions

      These data suggest that COVID vaccine hesitancy is associated with significant increased risks of a traffic crash. An awareness of these risks might help to encourage more COVID vaccination.

      Keywords

      Clinical Significance
      • Coronavirus disease (COVID) vaccination uptake has stalled despite being safe, effective, and free.
      • COVID vaccine hesitancy is associated with increased traffic risks.
      • The risks in unvaccinated adults apply to differing patients and severe events.
      • The traffic risks are comparable with the risks with sleep apnea.
      • Physicians counseling patients who decline COVID vaccination could consider safety reminders to mitigate traffic risks.

      Introduction

      Motor vehicle traffic crashes are a common cause of sudden death, brain injury, spinal damage, skeletal fractures, chronic pain, and other disabling conditions. Crash risks occur as a complication of several diseases including alcohol misuse, sleep apnea, and diabetes.
      • Redelmeier DA
      • Yarnell CJ
      • Thiruchelvam D
      • Tibshirani RJ
      Physicians' warnings for unfit drivers and the risk of trauma from road crashes.
      Crashes also occur in patients with controlled hypertension, prior cancer, or no disease at all.
      National Highway Traffic Safety Administration
      Traffic Safety Facts 2019.
      The proximate causes of most crashes are human behaviors including speeding, inattention, tailgating, impairment, improper passing, disobeying a signal, failing to yield right-of-way, or other infractions.
      Ontario Ministry of Transportation
      Ontario Road Safety Annual Report 2018.
      These behaviors might partially reflect health consciousness, safety mindedness, community spirit, or other psychological characteristics that are difficult to measure in a systematic manner.
      • Adavikottu A
      • Velaga NR
      Analysis of factors influencing aggressive driver behavior and crash involvement.
      ,
      • Redelmeier DA
      • Najeeb U
      • Etchells EE
      Understanding patient personality in medical care: five-factor model.
      Coronavirus disease (COVID) vaccine hesitancy is defined by the World Health Organization as a delay in acceptance or refusal of vaccination against an important contagious disease despite supply (distribution), access (availability), and awareness (albeit with possible misinformation).
      • MacDonald NE
      SAGE Working Group on Vaccine Hesitancy
      Vaccine hesitancy: definition, scope and determinants.
      ,
      • Dror AA
      • Eisenbach N
      • Taiber S
      • et al.
      Vaccine hesitancy: the next challenge in the fight against COVID-19.
      Vaccine hesitancy or confidence is not new; for example, the original polio vaccine required multifactorial efforts, including celebrity endorsements (eg, the publicized injection for Elvis Presley in 1956).
      • Dudley MZ
      • Privor-Dumm L
      • Dubé È
      • MacDonald NE
      Words matter: vaccine hesitancy, vaccine demand, vaccine confidence, herd immunity and mandatory vaccination.

      Hershfield H, Brody I. How Elvis got Americans to accept the polio vaccine. Scientific American. January 18, 2021. Available at:https://www.scientificamerican.com/article/how-elvis-got-americans-to-accept-the-polio-vaccine/. Accessed June 9, 2022.

      • Sehgal NKR
      Impact of Vax-a-Million Lottery on COVID-19 vaccination rates in Ohio.
      Vaccination preferences mayalso reflect past misadventures (eg, the ill-advised swine-flu vaccine mandate by Gerald Ford in 1976).
      • Fineberg HV
      Swine flu of 1976: lessons from the past. An interview with Dr Harvey V Fineberg.
      Vaccine hesitancy in regions of wide availability, however, can be contentious due to conflicting values, fallible self-report, cognitive blind spots, or other behavioral issues.
      • Nisbett RE
      • Wilson TD
      Telling more than we can know: verbal reports on mental processes.
      • Hall L
      • Johansson P
      • Strandberg T
      Lifting the veil of morality: choice blindness and attitude reversals on a self-transforming survey.
      • Krumpal I
      Determinants of social desirability bias in sensitive surveys: a literature review.
      • Lambooij MS
      • Harmsen IA
      • Veldwijk J
      • et al.
      Consistency between stated and revealed preferences: a discrete choice experiment and a behavioural experiment on vaccination behaviour compared.
      • Arena R
      • Pronk NP
      • Laddu D
      • et al.
      Mapping one million COVID-19 deaths and unhealthy lifestyle behaviors in the United States: recognizing the syndemic pattern and taking action.
      • Murphy J
      • Vallières F
      • Bentall RP
      • et al.
      Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom.
      COVID vaccination is an objective, available, important, authenticated, and timely indicator of human behavior—albeit in a domain separate from motor vehicle traffic crashes. Whether COVID vaccination is associated with increased traffic risks, however, has not been tested and might seem surprising.
      • Redelmeier DA
      • Shafir E
      Pitfalls of judgment during the COVID-19 pandemic.
      Simple immune activation against a coronavirus, for example, has no direct effect on traffic behavior or the risk of a motor vehicle crash.
      • Forchette L
      • Sebastian W
      • Liu T
      A comprehensive review of COVID-19 virology, vaccines, variants, and therapeutics.
      Instead, we theorized that individual adults who tend to resist public health recommendations might also neglect basic road safety guidelines.
      • Norris FH
      • Matthews BA
      • Riad JK
      Characterological, situational, and behavioral risk factors for motor vehicle accidents: a prospective examination.
      • Shrank WH
      • Patrick AR
      • Brookhart MA
      Healthy user and related biases in observational studies of preventive interventions: a primer for physicians.
      • Rosenbaum L
      Escaping Catch-22 – overcoming Covid vaccine hesitancy.
      • Fendrich SJ
      • Balachandran M
      • Patel MS
      Association between behavioral phenotypes and sustained use of smartphones and wearable devices to remotely monitor physical activity.
      The study question was “Does COVID vaccine hesitancy correlate with the risks of a serious traffic crash?”

      Methods

      Study Setting

      Ontario is the most populous province of Canada, with 14,789,778 residents in 2021.

      Government of Ontario. Ontario demographic quarterly: highlights of first quarter. 2021. Available at: https://www.ontario.ca/page/ontario-demographic-quarterly-highlights-first-quarter. Accessed June 9, 2022.

      The yearly crash risk was 2% for an average adult (minor incidents included), the minimum driving age was 16 years, and novice drivers initially received beginner licenses.
      Ontario Ministry of Transportation
      Ontario Road Safety Annual Report 2018.
      The COVID vaccine became available in winter 2020, doses were widely delivered to adults by spring 2021, and uptake had plateaued in summer 2021.

      Ipsos. Global attitudes on a COVID-19 vaccine. World Economic Forum, 2021. Available at: https://www.ipsos.com/en-ca/global-attitudes-covid-19-vaccine-january-2021. Accessed June 9, 2022.

      ,
      • Tang X
      • Gelband H
      • Nagelkerke N
      • et al.
      COVID-19 vaccination intention during early vaccine rollout in Canada: a nationwide online survey.
      The 4 vaccines were Pfizer-BioNTech (approved December 9, 2020), Moderna (December 23, 2020), AstraZeneca (February 26, 2021), and Johnson & Johnson (March 5, 2021).

      Government of Canada. Canada's COVID-19 vaccine supply and donation strategy. 2021. Available at:https://www.canada.ca/en/public-health/services/diseases/coronavirus-disease-covid-19/vaccines/supply-donation.html. Accessed June 9, 2022.

      Government of Ontario. COVID-19 Vaccine Distribution Plan. 2021. Available at: https://files.ontario.ca/moh-covid-19-vaccine-distribution-plan-en-2021-02-19.pdf. Accessed June 9, 2022.

      Government of Canada. Drug and vaccine authorizations for COVID-19: List of authorized drugs, vaccines and expanded indications. 2022. Available at:https://www.canada.ca/en/health-canada/services/drugs-health-products/covid19-industry/drugs-vaccines-treatments/authorization/list-drugs.html. Accessed June 9, 2022.

      Vaccination was free to all, supported by popular community outreach, accompanied by public campaigns, and connected to a central registration system (COVAXON).

      ICES. ICES COVID-19 Dashboard. 2021. Available at: https://www.ices.on.ca/DAS/AHRQ/COVID-19-Dashboard. Accessed June 9, 2022.

      Vaccination Status

      We identified individuals using encrypted identifiers from official government registries.
      • Iron K
      • Zagorski BM
      • Sykora K
      • Manuel DG
      Living and Dying in Ontario: An Opportunity for Improved Health Information.
      We included adults age 18 years or more on July 31, 2021 to ensure that each was eligible for a regular driver's license and a COVID vaccine.

      Public Health Ontario. Surveillance report: COVID-19 vaccine uptake in Ontario: December 14, 2020 to May 23, 2022. [Page 5]. Available at:https://www.publichealthontario.ca/-/media/documents/ncov/epi/covid-19-vaccine-uptake-ontario-epi-summary.pdf?la=en. Accessed June 9, 2022.

      This population-based approach was fully comprehensive, with the exception of excluding cases marked as invalid, containing faulty identifiers, or missing a birthdate.
      • Williams JI
      • Young W
      A summary of studies on the quality of health care administrative databases in Canada.
      • Juurlink D
      • Preyra C
      • Croxford R
      • et al.
      Canadian Institute for Health Information Discharge Abstract Database: a validation study.
      We also excluded those living elsewhere (home address), having no earlier activity (record gap), or who were not alive (death database). COVID vaccination status was based on the COVAXON database, with further details on product (manufacturer), date of first dose (earlier or later), and completeness (1 or 2 doses).
      • Chung H
      • He S
      • Nasreen S
      • et al.
      Effectiveness of BNT162b2 and mRNA-1273 covid-19 vaccines against symptomatic SARS-CoV-2 infection and severe covid-19 outcomes in Ontario, Canada: test negative design study.
      ,
      • Leung G
      • Verma A
      Epidemiological study of COVID-19 fatalities and vaccine uptake: insight from a public health database in Ontario, Canada.
      The study was registered in advance, approved by the Sunnybrook Research Ethics Board, and conducted using Institute for Clinical Evaluative Sciences safeguards.

      Additional Characteristics

      Information on age (years), sex (binary), home location (urban, rural), and socioeconomic status (quintile) was based on demographic databases.
      • Yarnell CJ
      • Thiruchelvam D
      • Redelmeier DA
      Risks of serious injury with testosterone treatment.
      ,
      • Redelmeier DA
      • Ng K
      • Thiruchelvam D
      • Shafir E
      Association of socioeconomic status with medical assistance in dying: a case-control analysis.
      Linked health care records were used to identify past diagnoses (International Classification of Diseases, Ninth Revision) and access to care (clinic contacts, emergency visits, hospital admissions) based on the preceding year.

      Government of Ontario. Medical services – claims history database. Ontario Ministry of Health and Long-Term Care, IntelliHEALTH ONTARIO. Available at:https://intellihealth.moh.gov.on.ca/. Accessed June 9, 2022.

      ,
      • Macpherson AK
      • Schull M
      • Manuel D
      • Cernat G
      • Redelmeier DA
      • Laupacis A
      Injuries in Ontario: ICES Atlas.
      We directed specific attention to diseases associated with traffic risks, including alcohol misuse, sleep apnea, diabetes, depression, and dementia.
      World Health Organization
      International Statistical Classification of Diseases and Related Health Problems.
      ,
      • Redelmeier DA
      • Tien HC
      Medical interventions to reduce motor vehicle collisions.
      For interest, we also checked for a past diagnosis of hypertension, cancer, and COVID infection. The available databases lacked information on driver skill, functional status, personality traits, traffic infractions, political affiliation, and self-identified ethnicity.
      • Sehgal AR
      Lifetime risk of death from firearm injuries, drug overdoses, and motor vehicle accidents in the United States.

      Traffic Crashes

      We identified serious traffic crashes during the subsequent month based on emergency care throughout the region (178 individual hospitals).
      • Schull MJ
      • Hatcher CM
      • Guttmann A
      • et al.
      Development of a Consensus on Evidence-Based Quality of Care Indicators for Canadian Emergency Departments. ICES Investigative Report.
      This definition reflected incidents sending a patient to an emergency department as a driver, passenger, or pedestrian (codes V00-V69).
      Canadian Institute for Health Information (CIHI)
      CIHI Data Quality Study of Emergency Department Visits for 2004-2005: volume II of IV: Main Study Findings.
      Additional crash characteristics included time (morning, afternoon, night), day (weekend, weekday), ambulance involvement (yes, no), and triage severity score (higher, lower).
      • Bullard MJ
      • Musgrave E
      • Warren D
      • et al.
      Revisions to the Canadian Emergency Department Triage and Acuity Scale (CTAS) guidelines 2016.
      In each case we also determined whether the patient was admitted (yes, no) and final status (dead, alive).
      • Schull MJ
      • Hatcher CM
      • Guttmann A
      • et al.
      Development of a Consensus on Evidence-Based Quality of Care Indicators for Canadian Emergency Departments. ICES Investigative Report.
      ,
      Canadian Institute for Health Information (CIHI)
      CIHI Data Quality Study of Emergency Department Visits for 2004-2005: volume II of IV: Main Study Findings.
      ,
      • Scales DC
      • Guan J
      • Martin CM
      • Redelmeier DA
      Administrative data accurately identified intensive care unit admissions in Ontario.
      • Wodchis WP
      • Bushmeneva K
      • Nikitovic M
      • McKillop I
      Guidelines on Person-Level Costing Using Administrative Databases in Ontario.
      • Wodchis WP
      • Austin PC
      • Henry DA
      A 3-year study of high-cost users of health care.
      Due to privacy restrictions we did not link to insurance records (financial costs from vehicle damage) or police records (deaths at the scene prior to reaching hospital).

      Other Outcomes

      Our study was not a randomized trial and we selected additional outcomes to check for a difference where a difference was anticipated (positive control) and no difference where no difference was anticipated (negative control).
      • Prasad V
      • Jena AB
      Prespecified falsification end points: can they validate true observational associations?.
      Specifically, we replicated methods by focusing instead on emergency care for COVID pneumonia as an alternative outcome (positive control). The rationale was that a lack of COVID vaccination, in theory, would be associated with an increased risk of subsequent COVID infection. Similarly, we tested emergency care for uncomplicated constipation (negative control). The rationale was that uncomplicated constipation is a frequent and distinct medical disorder among diverse patients unrelated to COVID vaccination or COVID infection.

      Statistical Analysis

      The main analysis evaluated emergency visits for individuals injured in traffic crashes. The primary comparison used the chi-square test to analyze those who had not received a COVID vaccine relative to those who had received a COVID vaccine. Odds ratios were used for relative risk estimates, with no censoring for interval deaths (accounting for deaths at the scene and censoring for interval deaths yielded nearly identical results). Stratified analyses assessed differences according to individual characteristics, with special attention to a diagnosis of alcohol misuse. The analysis was then replicated for patients diagnosed with subsequent COVID pneumonia (positive control) and patients diagnosed with uncomplicated constipation (negative control).
      Secondary analyses explored further nuances to check the robustness of a potential association between COVID vaccination and traffic crash risks. We used multivariable logistic regression analysis to test the strength of association after accounting for baseline demographic and diagnostic predictors. Prespecified subgroup analyses were used to check for replication according to specific vaccine, recency of first dose, and completeness of vaccination. Similarly, subtype analyses were used to examine whether the association extended across the spectrum of crash severity. In addition, a sensitivity analysis was conducted to account for crossover patients who eventually received a vaccination during the 1-month follow-up interval.
      Two more supplementary sets of analyses were conducted in a post hoc manner after examining results from the primary analysis. The first analyses tested a propensity score approach as an alternative method to adjust for observed baseline individual differences. Individual patients were pair matched one-to-one based on age (within 5 years), sex (binary), location (binary), socioeconomic status (quintile), and propensity score of specific diagnosis (total = 8). The second analyses tested additional negative controls to validate statistics and check for a further lack of difference in unrelated outcomes. The 4 separate additional emergency outcomes were a fall, a water transportation incident, appendicitis, and conjunctivitis (Appendix, available online). Study reporting followed the Strengthening the Reporting of Observational Studies in Epidemiology guideline (STROBE checklist).

      Results

      Overview

      A total of 11,270,763 adults were identified. Overall, 9,425,473 (84%) had received a COVID vaccine and 1,845,290 (16%) had not received a COVID vaccine at study baseline (July 31, 2021). The 2 groups spanned a diverse range of demographics, with comparable general health care utilization (Table 1). The largest relative differences were that those who had not received a COVID vaccine were more likely to be younger, living in a rural area, and below the middle socioeconomic quintile. Those who had not received a vaccine also were more likely to have a diagnosis of alcohol misuse or depression and less likely to have a diagnosis of sleep apnea, diabetes, cancer, or dementia. About 4% had a past COVID diagnosis, with no major imbalance between the 2 groups.
      Table 1Baseline Characteristics
      COVID Vaccination
      YesNo
      Variable(n = 9,425,473)(n = 1,845,290)
      Demographic
      Age (years)
      18-393,040,343 (32.3%)938,310 (50.8%)
      40-643,987,941 (42.3%)684,712 (37.1%)
      ≥652,397,189 (25.4%)222,268 (12.0%)
      Sex
      Male4,505,555 (47.8%)928,543 (50.3%)
      Female4,919,918 (52.2%)916,747 (49.7%)
      Home
      Urban8,464,905 (89.8%)1,619,385 (87.8%)
      Rural960,568 (10.2%)225,905 (12.2%)
      Socioeconomic status
      Based on home neighborhood, missing data coded as lower.
      Higher3,956,080 (42.0%)620,654 (33.6%)
      Middle1,913,588 (20.3%)366,488 (19.9%)
      Lower3,555,805 (37.7%)858,148 (46.5%)
      Diagnoses
      Based on previous year.
       Alcohol misuse
      Code 303.
      Yes37,118 (0.4%)13,522 (0.7%)
       Sleep apnea
      Code 786.
      Yes507,054 (5.4%)80,454 (4.4%)
       Diabetes
      Code 250.
      Yes987,422 (10.5%)109,995 (6.0%)
       Depression
      Code 300.
      Yes1,181,992 (12.5%)262,915 (14.2%)
       Dementia
      Code 290.
      Yes151,776 (1.6%)11,522 (0.6%)
       Hypertension
      Code 401.
      Yes1,069,601 (11.3%)123,536 (6.7%)
       Cancer
      Codes 140 to 208.
      Yes654,151 (6.9%)75,226 (4.1%)
       COVID infection
      Code 080.
      Yes390,928 (4.1%)64,696 (3.5%)
      General
      Based on previous year.
       Clinic contacts≥36,283,552 (66.7%)1,116,778 (60.5%)
       Emergency visitYes1,891,240 (20.1%)475,786 (25.8%)
       Hospital admissionYes477,873 (5.1%)107,175 (5.8%)
      low asterisk Based on home neighborhood, missing data coded as lower.
      Based on previous year.
      Code 303.
      § Code 786.
      Code 250.
      Code 300.
      low asterisklow asterisk Code 290.
      †† Code 401.
      ‡‡ Codes 140 to 208.
      §§ Code 080.

      Traffic Crashes

      A total of 6682 individuals required emergency care for a serious traffic crash during the subsequent month of follow-up. This rate averaged over 200 individuals per day and was comparable with population norms for high-income countries. Patients who had not received a COVID vaccine accounted for 1682 crashes (25% of total crashes), equal to an absolute risk of 912 per million. Patients who had received a COVID vaccine accounted for 5000 crashes (75% of total crashes), equal to an absolute risk of 530 per million. The difference corresponded to a relative risk of 1.72 for patients who had not received the COVID vaccine (95% confidence interval, 1.63-1.82; P < 0.001). The risk of a traffic crash was proportional with time for both groups (Figure 1).
      Figure 1
      Figure 1Cumulative incidence plots of absolute risk of a serious traffic crash. X-axis shows days following start of follow-up. Y-axis shows cumulative incidence of events per million individuals. Blue line denotes those vaccinated against coronavirus disease (COVID) and red line denotes those not vaccinated against COVID. Counts in square brackets indicate cumulative total patients in each group with an event at corresponding time. Relative risk ratio based on logistic regression model. Results show substantial incidence of serious traffic crashes that is increased for those who are not vaccinated relative to those who are vaccinated.

      Consistency for Subgroups

      The association between a lack of COVID vaccination and increased traffic risks extended to important subgroups. The pattern was apparent for younger and middle-aged adults, men and women, those in urban and rural locations, and across the range of socioeconomic status (Figure 2). The smallest relative risk was for adults older than 65 years. The results persisted after stratifying for a diagnosis of alcohol misuse or other specific diagnosis. Stratified analyses based on total clinic contacts, emergency visits, and prior admissions also yielded findings consistent with the primary analysis (Appendix). All subgroups with at least 1000 total crashes showed a significant finding replicating the primary analysis. No subgroup showed a significant opposite association.
      Figure 2
      Figure 2Forest plot of relative risk of a serious traffic crash in different subgroups. Relative risk compares unvaccinated adults with vaccinated adults for each estimate. In each subgroup, counts show total crashes along with absolute crash risk for those vaccinated and for those not vaccinated (events per million). Circles denote relative risk estimate and horizontal lines denote 95% confidence interval. Null association shown as a relative risk of 1.00 on logarithmic axis. Summary data for total cohort at bottom. Findings show substantial counts, increased relative risk for those unvaccinated, and most subgroups overlapping main analysis. High outlier of unvaccinated patients with dementia potentially attributable to chance.

      Additional Predictors of Crash Risk

      The baseline risk of a traffic crash was also related to other individual characteristics (Table 2). In accord with past studies, the risk was greater for younger than older adults, more for men than women, and higher for those with lower socioeconomic status. Living in a rural location was not associated with a large difference in risk in either univariable or multivariable analysis. A diagnosis of alcohol misuse was a substantial risk factor, sleep apnea or depression were modest risk factors, and a past diagnosis of COVID infection was an equivocal risk factor. Adjustment for all measured individual characteristics suggested a relative risk of 1.48 for individuals who had not received a COVID vaccine (95% confidence interval, 1.40-1.57; P < 0.001).
      Table 2Predictors of Traffic Crash Risk
      Basic Analysis
      No adjustments for baseline differences.
      Adjusted Analysis
      Adjusted for other differences through regression model.
      Relative RiskConfidence IntervalRelative RiskConfidence Interval
      No COVID vaccination1.721.63-1.821.481.40-1.57
      Younger age (<40 y)1.501.43-1.581.401.33-1.48
      Older age (≥65 y)0.620.57-0.660.670.62-0.73
      Male sex1.481.41-1.561.501.43-1.57
      Rural home1.030.95-1.111.060.98-1.15
      Higher socioeconomic status
      eferent is middle socioeconomic status.
      0.990.93-1.061.010.94-1.08
      Lower socioeconomic status
      eferent is middle socioeconomic status.
      1.161.09-1.241.131.06-1.21
      Alcohol misuse3.062.49-3.772.251.83-2.78
      Sleep apnea1.211.09-1.331.321.19-1.46
      Diabetes0.760.70-0.830.980.90-1.08
      Depression1.561.46-1.661.531.44-1.63
      Dementia0.390.28-0.540.590.43-0.82
      Hypertension0.630.57-0.690.820.74-0.90
      Cancer0.780.70-0.871.010.90-1.13
      COVID infection1.161.03-1.301.110.99-1.25
      low asterisk No adjustments for baseline differences.
      Adjusted for other differences through regression model.
      ‡R eferent is middle socioeconomic status.

      Secondary Analyses

      The increased traffic crash risks among those who had not received a COVID vaccine applied across diverse analyses (Table 3). The increased risk extended to patients who required ambulance transport, had higher triage severity, and needed hospital admission. The increased risk was accentuated in analyses distinguishing earlier rather than later vaccine timing and distinguishing those with 2 rather than 1 dose. The risk was similar for the Pfizer, Moderna, or other vaccines. As expected, the risk of subsequent COVID pneumonia was increased for those who had not received a COVID vaccine, whereas the risk of constipation was unrelated to the COVID vaccine. Results were further validated in analyses of those eventually vaccinated during follow-up, those matched by propensity scores, and those with additional outcomes (Appendix).
      Table 3Secondary Analyses
      Total EventsRisk with Vaccine
      Risk is crash rate per million individuals.
      Risk with No Vaccine
      Risk is crash rate per million individuals.
      Relative Risk
      Calculated from logistic regression.
      Confidence Interval
      Primary analysis66825309121.721.63-1.82
      Crash details
       Involvement
      Driver28562184341.991.83-2.16
      Passenger1189921751.911.68-2.17
      Pedestrian26372213031.381.25-1.51
       Time
      Morning 4 AM to 11:59 AM, afternoon 12 noon to 7:59 PM, night is remainder.
      Morning14901231781.451.28-1.64
      Afternoon35892924551.561.45-1.69
      Night16031162782.412.17-2.67
       Day
      Weekend21421722851.661.51-1.84
      Weekday45403596271.751.63-1.87
       Ambulance transport
      Yes26572073811.841.69-2.00
      No40253235311.641.53-1.77
       Triage severity
      Based on Canadian Triage Severity Score, higher is 1 or 2, lower is remainder.
      Higher18381372972.171.96-2.39
      Lower48443946151.561.46-1.67
       Hospital admission
      Yes55042821.971.64-2.38
      No61324898281.691.60-1.80
       Outcome
      Based on Canadian Triage Severity Score, higher is 1 or 2, lower is remainder.
      Alive66745309091.721.62-1.81
      Dead80.422.175.111.28-20.43
      Vaccine details
       Timing
      enotes control group for each sub-analysis based on first dose.
      Earlier
      Earlier is prior to May 1, 2021, later is after May 1, 2021.
      39014579122.001.88-2.13
      Later
      Earlier is prior to May 1, 2021, later is after May 1, 2021.
      44636099121.501.41-1.59
       Completeness
      enotes control group for each sub-analysis based on first dose.
      Two doses58955059121.811.71-1.91
      One dose24697259121.261.16-1.37
       Specific type
      enotes control group for each sub-analysis based on first dose.
      Pfizer51905239121.741.64-1.85
      Moderna27185589121.631.51-1.77
      Other
      AstraZeneca or Johnson & Johnson.
      21385289121.731.56 tp 1.92
      Validation analysis
       Eventual vaccination66825349391.761.66-1.86
       Propensity matched28996619111.381.28-1.49
      Other outcomes
      Supplementary details in accompanying appendix.
       COVID pneumonia535830313544.474.23-4.74
       Constipation29852632721.030.94-1.14
       Fall28,805259823370.900.87-0.93
       Water craft
      Transportation incident on waterway not roadway.
      46240441.100.87-1.40
       Appendicitis11641011151.140.98-1.32
       Conjunctivitis16771491501.010.89-1.15
      low asterisk Risk is crash rate per million individuals.
      Calculated from logistic regression.
      Morning 4 AM to 11:59 AM, afternoon 12 noon to 7:59 PM, night is remainder.
      § Based on Canadian Triage Severity Score, higher is 1 or 2, lower is remainder.
      ‖D enotes control group for each sub-analysis based on first dose.
      Earlier is prior to May 1, 2021, later is after May 1, 2021.
      low asterisklow asterisk AstraZeneca or Johnson & Johnson.
      †† Supplementary details in accompanying appendix.
      ‡‡ Transportation incident on waterway not roadway.

      Discussion

      We studied millions of adults and found that COVID vaccine hesitancy was associated with significant increased traffic risks. The increased risks included adults with diverse characteristics who spanned the range of socioeconomic status and home locations. The increased risks extended across the spectrum of crash severity, including cases requiring ambulance transport and acute hospitalization. The magnitude of estimated risk was substantial and similar to the relative risk associated with sleep apnea, less than associated with alcohol misuse, and greater than associated with diabetes. A relative risk of this magnitude, furthermore, exceeds the safety gains from modern automobile engineering advances and also imposes risks on other road users.
      • Redelmeier DA
      • Tien HC
      Medical interventions to reduce motor vehicle collisions.
      ,
      • Evans L
      Traffic Safety.
      Our research agrees with past studies about psychology contributing to traffic risks.
      • Nabi H
      • Rachid Salmi L
      • Lafont S
      • Chiron M
      • Zins M
      • Lagarde E
      Attitudes associated with behavioral predictors of serious road traffic crashes: results from the GAZEL cohort.
      ,
      • Nunn J
      • Erdogan M
      • Green RS
      The prevalence of alcohol-related trauma recidivism: a systematic review.
      One of the earliest studies evaluated taxi drivers and observed a 7-times greater frequency of personality disorders among those with multiple crashes compared with those with no crashes.
      • Tillmann WA
      • Hobbs GE
      The accident-prone automobile driver; a study of the psychiatric and social background.
      A study of young drivers identified a near doubling of crash incidents associated with an aggressive personality pattern.
      • Gulliver P
      • Begg D
      Personality factors as predictors of persistent risky driving behavior and crash involvement among young adults.
      A psychometric analysis of motorcycle riders found that personal temperament was the largest predictor of crash involvement.
      • Cheng ASK
      • Ng TCK
      • Lee HC
      A comparison of the hazard perception ability of accident-involved and accident-free motorcycle riders.
      The weaknesses of past studies include small sample sizes, fallible self-report, cross-sectional designs, low outcome counts, and narrow generalizability.
      • Redelmeier DA
      • Yarnell CJ
      Lethal misconceptions: interpretation and bias in studies of traffic deaths.
      ,
      • Brown TG
      • Ouimet MC
      • Eldeb M
      • et al.
      Personality,executive control, and neurobiological characteristics associated with different forms of risky driving.
      We are aware of no past study testing COVID vaccination and traffic risks.
      A limitation of our study is that correlation does not mean causality because our data do not explore potential causes of vaccine hesitancy or risky driving.
      • Bullock J
      • Lane JE
      • Shults FL
      What causes COVID-19 vaccine hesitancy? Ignorance and the lack of bliss in the United Kingdom.
      One possibility relates to a distrust of government or belief in freedom that contributes to both vaccination preferences and increased traffic risks.

      Kirzinger A, Sparks G, Brodie M. KFF COVID-19 vaccine monitor: in their own words, six months later. Kaiser Family Foundation, July 13, 2021. Available at: https://www.kff.org/coronavirus-covid-19/poll-finding/kff-covid-19-vaccine-monitor-in-their-own-words-six-months-later/. Accessed June 9, 2022.

      A different explanation might be misconceptions of everyday risks, faith in natural protection, antipathy toward regulation, chronic poverty, exposure to misinformation, insufficient resources, or other personal beliefs.
      • Rosenbaum L
      No cure without care – soothing science skepticism.
      Alternative factors could include political identity, negative past experiences, limited health literacy, or social networks that lead to misgivings around public health guidelines.
      • Johnson NF
      • Velásquez N
      • Restrepo NJ
      • et al.
      The online competition between pro- and anti-vaccination views.
      ,

      Angus Reid Institute. Dwindling group of unvaccinated cite ‘personal freedom’ and ‘health concerns’ as main reasons for dodging the jab. November 3, 2021. Available at: https://angusreid.org/canada-unvaccinated-freedom-reasons/. Accessed June 9, 2022.

      These subjective unknowns remain topics for more research.
      Another limitation of our study is the lack of direct data on driving exposure in different groups. A 100% increase in driving distance, however, is unlikely to explain the magnitude of traffic risks observed in this study.
      • Redelmeier DA
      The fallacy of interpreting deaths and driving distances.
      A difference in driving distance would also not explain why the increased risks extended to pedestrians, why the increased risks were not lower in urban locations, and why the increased risks were not higher on weekends (when discretionary driving is common).

      Redelmeier DA, Zipursky JS. Pedestrian deaths during the COVID-19 pandemic [online ahead of print]. Am J Lifestyle Med. Published online November 26, 2021. Available at: https://journals.sagepub.com/doi/10.1177/15598276211058378. Accessed November 15, 2022.

      To be sure, physical factors such as vehicle speed and distance are controlled by the driver and part of the mechanism that ultimately results in a traffic crash. These physical unknowns do not change the importance of our study for estimating prognosis.
      Our study has other limitations. The analysis does not correct for barriers in access to care or risk compensation that each bias results in the contrary direction.
      • Trogen B
      • Caplan A
      Risk compensation and COVID-19 vaccines.
      The analysis does not include minor crashes that do not lead to emergency care or deaths at the scene prior to reaching the hospital (Appendix).
      • Rojas Castro MY
      • Orriols L
      • Basha Sakr D
      • et al.
      A web-based prospective cohort study of home, leisure, school and sports injuries in France: a descriptive analysis.
      The data do not examine the long-term recovery, quality of life, and insurance costs for those who survive initial injuries. Many vehicle factors remain unexplored, including speed, spacing, configuration, location, weather, and distances driven. The study does not test the reliability of COVID vaccination as a proxy for COVID vaccine hesitancy. The available data do not examine long-term trends, test at-fault liability, or assess measurement error that biases results toward the null.
      • Redelmeier DA
      • Yarnell CJ
      Lethal misconceptions: interpretation and bias in studies of traffic deaths.
      These uncertainties are further opportunities for future science.
      • Sehgal NKR
      Impact of Vax-a-Million Lottery on COVID-19 vaccination rates in Ohio.
      The current findings can help address 4 common misunderstandings.
      • Hitti FL
      • Weissman D
      Debunking mRNA Vaccine Misconceptions-An Overview for Medical Professionals.
      We show the high numbers and the diverse profile of adults who are not vaccinated (Table 1), contrary to claims that COVID vaccine hesitancy is concentrated in men, in poverty, and in rural regions. We validate that vaccination is associated with large reductions in subsequent COVID pneumonia (Table 3), contrary to claims that industry-funded trials are misleading. We document that traffic crashes have continued unabated during the COVID pandemic (Figure 1), contrary to claims that social distancing would lead to fewer traffic fatalities or that one pandemic somehow might replace another. We verify that traffic crashes disproportionately involve those in poverty (Table 2), contrary to claims that traffic safety is unrelated to health disparities.
      Our findings have direct relevance by highlighting how injury risks have continued despite the COVID pandemic.

      National Highway Traffic Safety Administration. Early estimate of motor vehicle traffic fatalities in 2020. Washington DC: United States Department of Transportation. Available at: https://www.nhtsa.gov/press-releases/2020-fatality-data-show-increased-traffic-fatalities-during-pandemic. Accessed June 9, 2022.

      Primary care physicians who wish to help patients avoid becoming traffic statistics, for example, could take the opportunity to stress standard safety reminders such as wearing a seatbelt, obeying speed limits, and never driving drunk.1,
      • Redelmeier DA
      • McLellan BA
      Modern medicine is neglecting road traffic crashes.
      The observed risks are sufficiently large that paramedics, emergency staff, and other first responders should be aware that unvaccinated patients are overrepresented in the aftermath of a traffic crash.
      • Bledsoe BE
      • Sweeney RJ
      • Berkeley RP
      • Cole KT
      • Forred WJ
      • Johnson LD
      EMS provider compliance with infection control recommendations is suboptimal.
      ,
      • Prezant DJ
      • Zeig-Owens R
      • Schwartz T
      • et al.
      Medical leave associated with COVID-19 among emergency medical system responders and firefighters in New York City.
      The observed risks might also justify changes to driver insurance policies in the future.
      • Weisburd S
      Identifying moral hazard in car insurance contracts.
      Together, the findings suggest that unvaccinated adults need to be careful indoors with other people and outside with surrounding traffic.

      Acknowledgments

      We thank Melany Gaetani, Fizza Manzoor, Sheharyar Raza, Eldar Shafir, Richard Thaler, Robert Tibshirani, Chris Yarnell, the Stanford Department of Biomedical Data Science, and the Princeton University Center for Behavioral Science & Public Policy for helpful suggestions on specific points.

      Appendix: COVID Vaccine Hesitancy and Risk of a Traffic Crash

      Table of Contents:
      • §1. Research in Context...........................................................................2
      • §2. Directed Acyclic Graph.....................................................................4
      • §3. Description of Patient Flows..............................................................5
      • §4. Additional Negative Controls............................................................6
      • §5. Additional Propensity Score Analyses..............................................7
      • §6. Additional Stratified Analysis...........................................................8
      • §7. Accounting for Scene Deaths..........................................................10
      • §8. Accounting for Later Vaccinations..................................................11

      §1 Research in Context

      Evidence prior to this study: We searched MEDLINE, PsychInfo, Scopus, and Google Scholar on December 31, 2021 with no language or date restrictions. The search terms for MEDLINE were (“vaccines” OR “immunization”) AND (“traffic accidents” OR “automobile driving”). The search terms for other databases were adapted as appropriate (details on request). Only 3 surveys examined the association of vaccination with traffic crash risks. One survey (n = 104,594) correlated previous influenza vaccinations with driving safety and detected a significant inverse association (individuals who had not received an influenza vaccination were 15% more likely to report risky driving). Two other survey studies (n = 348 and n = 654) assessed general attitudes toward public health and also found clustering of risks (individuals who reported risk-taking tendencies were 39% less likely to be coronavirus disease (COVID) vaccinated and 41% less likely to follow COVID public health instructions). No studies used validated longitudinal analysis to compare objective vaccination status with actual traffic crash risks.
      Added value of this study: This is the first population-based longitudinal cohort study to examine an adult's COVID vaccination status and subsequent traffic crash risk. The analysis of over 10 million adults found the risk of a serious traffic crash was significantly higher for adults who had not received a COVID vaccine compared with adults who had received a COVID vaccine. The increased traffic risk associated with COVID vaccine hesitancy persisted in relevant subgroups stratifying for age, sex, home location, socioeconomic status, medical diagnoses, and access to care. The relative risk was similar to the relative risk associated with sleep apnea, less than the risk associated with alcohol misuse, and greater than the risk associated with diabetes. The increased risk was primarily explained by events when driving at night. The increased risk extended across differing degrees of crash severity, was more prominent in analyses based on 2 doses rather than 1 dose, and similar for the Pfizer, Moderna, or other COVID vaccines.
      Implications of all available evidence: COVID vaccine hesitancy is associated with an increased risk of a traffic crash. A direct effect from immunization is unlikely; instead, diverse psychological factors contribute to vaccine willingness and driving safety (eg, both entail inconveniences advocated by authorities to protect the community). Traffic crashes have continued during the COVID pandemic, implying that physicians have a responsibility to counsel at-risk patients in primary care. In addition, COVID vaccine status might be considered for regions that prioritize road safety, such as those that mandate physicians to warn risky drivers and report to vehicle licensing agencies. Prehospital care providers need to also be aware that unvaccinated adults are overrepresented in the aftermath of a traffic crash, thereby justifying maintaining adherence to COVID precautions at the frenzied crash scene. In addition, the clustering of risks imposed on others might indirectly promote new strategies to promote COVID vaccination.

      §2 Directed Acyclic Graph

      Unlabelled image
      Footnote: Directerd Acyclic Graph of possible causal pathways relevant to vaccine hesitancy and traffic risks. The diagram displays measured factors (white), unmeasured ancestors of vaccine hesitancy (green), unmeasured ancestors of traffic risks (blue), and unmeasured ancestors to both vaccine hesitancy and traffic risks (pink). Causal pathways denoted as closed (black lines) or open (magenta lines). Specific causal pathways based on literature review, direct clinical experience (Canada's largest trauma center), and expert consultation (International Traffic Medicine Association).

      §3 Description of Patient Flows

      §4 Additional Negative Controls

      Tabled 1
      ICD 10 CodesTotal Events
      Positive Control
       COVID pneumoniaU075358
      Negative Control
       ConstipationK952985
       FallsW00 to W1928,805
       AppendicitisK35 to K381164
       ConjunctivitisH10 to H131677
       Water transportationV90 to V94462
      COVID = coronavirus disease; ICD = International Classification of Diseases.

      §5 Additional Propensity Score Analyses: General and Stringent

      The purpose of the first propensity score analysis was to retain a large sample size when matching an unvaccinated individual 1-to-1 with a vaccinated individual and accounting for baseline demographic characteristics and individual diseases.
      Unlabelled image
      Analysis of General Matched Cohort Pairs
      Tabled 1
      Unvaccinated Control
      YES CRASHNO CRASH
      Vaccinated IndividualYES CRASH31216
      NO CRASH16771,841,591
      Total individuals = 3,688,974; total pairs = 1,844,487; total crashes = 2899; odds ratio = 1.38; 95% confidence interval, 1.28-1.44; P-value < 0.001.
      The purpose of the second propensity score analysis was to be stringent when matching an unvaccinated individual 1-to-1 with a vaccinated individual and excluding cases where any person had a medical diagnosis.
      Unlabelled image
      Analysis of Stringent Matched Cohort Pairs
      Tabled 1
      Unvaccinated Control
      YES CRASHNO CRASH
      Vaccinated individualYES CRASHX42X
      NO CRASH68X584,41X
      “X” denotes single digit suppression for privacy regulations; total individuals = 1,171,044; total pairs = 585,522; total crashes = 1111; odds ratio = 1.63; 95% confidence interval, 1.45-1.85; P-value < 0.001.

      §6 Additional Stratified Analysis

      Tabled 1
      Total EventsRisk with Vaccine
      Risk is crash rate per million individuals.
      Risk with

      No Vaccine
      Risk is crash rate per million individuals.
      Relative Risk
      Calculated from logistic regression.
      Confidence Interval
      Primary analysis66825309121.721.63-1.82
      Health care
      Based on previous year.
       Clinic contacts ≥346205629751.741.62-1.86
       Clinic contacts ≤220624688141.741.58-1.92
       Emergency visit yes229883415151.821.67-1.99
       Emergency visit no43844547021.551.44-1.66
       Hospital admit yes3635827931.361.07-1.74
       Hospital admit no63195289191.741.65-1.84
      low asterisk Risk is crash rate per million individuals.
      Calculated from logistic regression.
      Based on previous year.

      §7 Accounting for Scene Deaths

      The study examined serious traffic crashes based on emergency care throughout the region and thereby did not include deaths at the scene. In turn, we considered extreme assumptions to examine how results might change based on these missing deaths. Specifically, traffic statistics for this setting (602 total deaths in Ontario, 2018) suggested that 50 total deaths might have occurred in our study during follow-up (602/12). Taking into account the 8 deaths that were included, therefore, we estimated potentially 42 total deaths at the scene (50−8).
      Making an extreme assumption and assigning all these deaths to the vaccinated group yielded minimal changes to final results. In particular, the observed event count increased from a total of 5000 crashes to 5042 crashes, equivalent to an absolute risk of 535 per million (rather than 530 per million). This observed absolute risk was still substantially lower than the observed risk of 912 per million in the unvaccinated group. These results suggested that extreme assumptions about the deaths at the scene make minimal difference to final estimates of relative risk.

      §8 Accounting for Later Vaccinations

      The study examined vaccination status based on records on July 31, 2021 and did not include possible later vaccination that might have eventually occurred. In turn, we retrieved information on these subsequent vaccinations and considered extreme assumptions to examine how results might change based on the crossover cases. Specifically, we found 219,740 individuals who were eventually vaccinated from the cohort of 1,8450,290 who had been classified as unvaccinated. These individuals accounted for 155 total traffic crashes during follow-up.
      Making an extreme assumption and assigning all individuals to the vaccinated group yielded minimal changes to final results. In particular, the observed event count increased from a total of 5000 crashes to 5155 crashes, equivalent to an absolute risk of 534 per million (rather than 530 per million). This observed absolute risk was still substantially lower than the recalculated risk of 939 per million in the unvaccinated group. These results suggested that extreme assumptions about possible eventual vaccination during follow-up make minimal difference to final estimates of relative risk.

      References

        • Redelmeier DA
        • Yarnell CJ
        • Thiruchelvam D
        • Tibshirani RJ
        Physicians' warnings for unfit drivers and the risk of trauma from road crashes.
        N Engl J Med. 2012; 367: 1228-1236
        • National Highway Traffic Safety Administration
        Traffic Safety Facts 2019.
        US Department of Transportation, Washington, DC2021 (Available at:) (Accessed June 9, 2022)
        • Ontario Ministry of Transportation
        Ontario Road Safety Annual Report 2018.
        Government of Ontario, Toronto2021 (Available at:) (Accessed June 9, 2022)
        • Adavikottu A
        • Velaga NR
        Analysis of factors influencing aggressive driver behavior and crash involvement.
        Traffic Inj Prev. 2021; 22: S21-S26
        • Redelmeier DA
        • Najeeb U
        • Etchells EE
        Understanding patient personality in medical care: five-factor model.
        J Gen Intern Med. 2021; 36: 2111-2114
        • MacDonald NE
        • SAGE Working Group on Vaccine Hesitancy
        Vaccine hesitancy: definition, scope and determinants.
        Vaccine. 2015; 33: 4161-4164
        • Dror AA
        • Eisenbach N
        • Taiber S
        • et al.
        Vaccine hesitancy: the next challenge in the fight against COVID-19.
        Eur J Epidemiol. 2020; 35: 775-779
        • Dudley MZ
        • Privor-Dumm L
        • Dubé È
        • MacDonald NE
        Words matter: vaccine hesitancy, vaccine demand, vaccine confidence, herd immunity and mandatory vaccination.
        Vaccine. 2020; 38: 709-711
      1. Hershfield H, Brody I. How Elvis got Americans to accept the polio vaccine. Scientific American. January 18, 2021. Available at:https://www.scientificamerican.com/article/how-elvis-got-americans-to-accept-the-polio-vaccine/. Accessed June 9, 2022.

        • Sehgal NKR
        Impact of Vax-a-Million Lottery on COVID-19 vaccination rates in Ohio.
        Am J Med. 2021; 134: 1424-1426
        • Fineberg HV
        Swine flu of 1976: lessons from the past. An interview with Dr Harvey V Fineberg.
        Bull World Health Organ. 2009; 87: 414-415
        • Nisbett RE
        • Wilson TD
        Telling more than we can know: verbal reports on mental processes.
        Psychol Rev. 1977; 84: 231-259
        • Hall L
        • Johansson P
        • Strandberg T
        Lifting the veil of morality: choice blindness and attitude reversals on a self-transforming survey.
        PLoS One. 2012; 7: e45457
        • Krumpal I
        Determinants of social desirability bias in sensitive surveys: a literature review.
        Qual Quant. 2013; 47: 2025-2047
        • Lambooij MS
        • Harmsen IA
        • Veldwijk J
        • et al.
        Consistency between stated and revealed preferences: a discrete choice experiment and a behavioural experiment on vaccination behaviour compared.
        BMC Med Res Methodol. 2015; 15: 19
        • Arena R
        • Pronk NP
        • Laddu D
        • et al.
        Mapping one million COVID-19 deaths and unhealthy lifestyle behaviors in the United States: recognizing the syndemic pattern and taking action.
        Am J Med. 2022; 135: 1288-1295
        • Murphy J
        • Vallières F
        • Bentall RP
        • et al.
        Psychological characteristics associated with COVID-19 vaccine hesitancy and resistance in Ireland and the United Kingdom.
        Nat Commun. 2021; 12: 29
        • Redelmeier DA
        • Shafir E
        Pitfalls of judgment during the COVID-19 pandemic.
        Lancet Public Health. 2020; 5: e306-e308
        • Forchette L
        • Sebastian W
        • Liu T
        A comprehensive review of COVID-19 virology, vaccines, variants, and therapeutics.
        Curr Med Sci. 2021; 41: 1037-1051
        • Norris FH
        • Matthews BA
        • Riad JK
        Characterological, situational, and behavioral risk factors for motor vehicle accidents: a prospective examination.
        Accid Anal Prev. 2000; 32: 505-515
        • Shrank WH
        • Patrick AR
        • Brookhart MA
        Healthy user and related biases in observational studies of preventive interventions: a primer for physicians.
        J Gen Intern Med. 2011; 26: 546-550
        • Rosenbaum L
        Escaping Catch-22 – overcoming Covid vaccine hesitancy.
        N Engl J Med. 2021; 384: 1367-1371
        • Fendrich SJ
        • Balachandran M
        • Patel MS
        Association between behavioral phenotypes and sustained use of smartphones and wearable devices to remotely monitor physical activity.
        Sci Rep. 2021; 11: 21501
      2. Government of Ontario. Ontario demographic quarterly: highlights of first quarter. 2021. Available at: https://www.ontario.ca/page/ontario-demographic-quarterly-highlights-first-quarter. Accessed June 9, 2022.

      3. Ipsos. Global attitudes on a COVID-19 vaccine. World Economic Forum, 2021. Available at: https://www.ipsos.com/en-ca/global-attitudes-covid-19-vaccine-january-2021. Accessed June 9, 2022.

        • Tang X
        • Gelband H
        • Nagelkerke N
        • et al.
        COVID-19 vaccination intention during early vaccine rollout in Canada: a nationwide online survey.
        Lancet Reg Health Am. 2021; 2100055
      4. Government of Canada. Canada's COVID-19 vaccine supply and donation strategy. 2021. Available at:https://www.canada.ca/en/public-health/services/diseases/coronavirus-disease-covid-19/vaccines/supply-donation.html. Accessed June 9, 2022.

      5. Government of Ontario. COVID-19 Vaccine Distribution Plan. 2021. Available at: https://files.ontario.ca/moh-covid-19-vaccine-distribution-plan-en-2021-02-19.pdf. Accessed June 9, 2022.

      6. Government of Canada. Drug and vaccine authorizations for COVID-19: List of authorized drugs, vaccines and expanded indications. 2022. Available at:https://www.canada.ca/en/health-canada/services/drugs-health-products/covid19-industry/drugs-vaccines-treatments/authorization/list-drugs.html. Accessed June 9, 2022.

      7. ICES. ICES COVID-19 Dashboard. 2021. Available at: https://www.ices.on.ca/DAS/AHRQ/COVID-19-Dashboard. Accessed June 9, 2022.

        • Iron K
        • Zagorski BM
        • Sykora K
        • Manuel DG
        Living and Dying in Ontario: An Opportunity for Improved Health Information.
        Institute for Clinical Evaluative Sciences, Toronto2008 (ICES Investigative Report)
      8. Public Health Ontario. Surveillance report: COVID-19 vaccine uptake in Ontario: December 14, 2020 to May 23, 2022. [Page 5]. Available at:https://www.publichealthontario.ca/-/media/documents/ncov/epi/covid-19-vaccine-uptake-ontario-epi-summary.pdf?la=en. Accessed June 9, 2022.

        • Williams JI
        • Young W
        A summary of studies on the quality of health care administrative databases in Canada.
        (eds)in: Goel V Williams JI Anderson GM Blackstien-Hirsch P Fooks C Naylor CD Patterns of Health Care in Ontario: The ICES Practice Atlas. Canadian Medical Association, Ottawa1996: 339-345 (2nd ed)
      9. (eds)Tu JV Penfold SP McColgan P Laupacis A Access to Health Services in Ontario: ICES Atlas. Institute for Clinical Evaluative Sciences, Toronto2006
        • Juurlink D
        • Preyra C
        • Croxford R
        • et al.
        Canadian Institute for Health Information Discharge Abstract Database: a validation study.
        Institute for Clinical Evaluative Sciences, Toronto2006
        • Chung H
        • He S
        • Nasreen S
        • et al.
        Effectiveness of BNT162b2 and mRNA-1273 covid-19 vaccines against symptomatic SARS-CoV-2 infection and severe covid-19 outcomes in Ontario, Canada: test negative design study.
        BMJ. 2021; 374: n1943
        • Leung G
        • Verma A
        Epidemiological study of COVID-19 fatalities and vaccine uptake: insight from a public health database in Ontario, Canada.
        Cureus. 2021; 13: e16160
        • Yarnell CJ
        • Thiruchelvam D
        • Redelmeier DA
        Risks of serious injury with testosterone treatment.
        Am J Med. 2021; 134: 84-94.e6
        • Redelmeier DA
        • Ng K
        • Thiruchelvam D
        • Shafir E
        Association of socioeconomic status with medical assistance in dying: a case-control analysis.
        BMJ Open. 2021; 11e043547
      10. Government of Ontario. Medical services – claims history database. Ontario Ministry of Health and Long-Term Care, IntelliHEALTH ONTARIO. Available at:https://intellihealth.moh.gov.on.ca/. Accessed June 9, 2022.

        • Macpherson AK
        • Schull M
        • Manuel D
        • Cernat G
        • Redelmeier DA
        • Laupacis A
        Injuries in Ontario: ICES Atlas.
        Institute for Clinical Evaluative Sciences, Toronto2005
        • World Health Organization
        International Statistical Classification of Diseases and Related Health Problems.
        World Health Organization, Geneva, Switzerland2010
        • Redelmeier DA
        • Tien HC
        Medical interventions to reduce motor vehicle collisions.
        CMAJ. 2014; 186: 118-124
        • Sehgal AR
        Lifetime risk of death from firearm injuries, drug overdoses, and motor vehicle accidents in the United States.
        Am J Med. 2020; 133: 1162-1167.e1
        • Schull MJ
        • Hatcher CM
        • Guttmann A
        • et al.
        Development of a Consensus on Evidence-Based Quality of Care Indicators for Canadian Emergency Departments. ICES Investigative Report.
        Institute for Clinical Evaluative Sciences, Toronto2010
        • Canadian Institute for Health Information (CIHI)
        CIHI Data Quality Study of Emergency Department Visits for 2004-2005: volume II of IV: Main Study Findings.
        CIHI, Ottawa2008
        • Bullard MJ
        • Musgrave E
        • Warren D
        • et al.
        Revisions to the Canadian Emergency Department Triage and Acuity Scale (CTAS) guidelines 2016.
        CJEM. 2017; 19: S18-S27
        • Scales DC
        • Guan J
        • Martin CM
        • Redelmeier DA
        Administrative data accurately identified intensive care unit admissions in Ontario.
        J Clin Epidemiol. 2006; 59: 802-807
        • Wodchis WP
        • Bushmeneva K
        • Nikitovic M
        • McKillop I
        Guidelines on Person-Level Costing Using Administrative Databases in Ontario.
        Health System Performance Research Network, Toronto, Canada2013 (Working Paper Series. Volume 1)
        • Wodchis WP
        • Austin PC
        • Henry DA
        A 3-year study of high-cost users of health care.
        CMAJ. 2016; 188: 182-188
        • Prasad V
        • Jena AB
        Prespecified falsification end points: can they validate true observational associations?.
        JAMA. 2013; 309: 241-242
        • Evans L
        Traffic Safety.
        Science Serving Society, Bloomfield Hills, Mich2004
        • Nabi H
        • Rachid Salmi L
        • Lafont S
        • Chiron M
        • Zins M
        • Lagarde E
        Attitudes associated with behavioral predictors of serious road traffic crashes: results from the GAZEL cohort.
        Inj Prev. 2007; 13: 26-31
        • Nunn J
        • Erdogan M
        • Green RS
        The prevalence of alcohol-related trauma recidivism: a systematic review.
        Injury. 2016; 47: 551-558
        • Tillmann WA
        • Hobbs GE
        The accident-prone automobile driver; a study of the psychiatric and social background.
        Am J Psychiatry. 1949; 106: 321-331
        • Gulliver P
        • Begg D
        Personality factors as predictors of persistent risky driving behavior and crash involvement among young adults.
        Inj Prev. 2007; 13: 376-381
        • Cheng ASK
        • Ng TCK
        • Lee HC
        A comparison of the hazard perception ability of accident-involved and accident-free motorcycle riders.
        Accid Anal Prev. 2011; 43: 1464-1471
        • Redelmeier DA
        • Yarnell CJ
        Lethal misconceptions: interpretation and bias in studies of traffic deaths.
        J Clin Epidemiol. 2012; 65: 467-473
        • Brown TG
        • Ouimet MC
        • Eldeb M
        • et al.
        Personality,executive control, and neurobiological characteristics associated with different forms of risky driving.
        PLoS One. 2016; 11e0150227
        • Bullock J
        • Lane JE
        • Shults FL
        What causes COVID-19 vaccine hesitancy? Ignorance and the lack of bliss in the United Kingdom.
        Humanit Soc Sci Commun. 2022; 9: 1-7
      11. Kirzinger A, Sparks G, Brodie M. KFF COVID-19 vaccine monitor: in their own words, six months later. Kaiser Family Foundation, July 13, 2021. Available at: https://www.kff.org/coronavirus-covid-19/poll-finding/kff-covid-19-vaccine-monitor-in-their-own-words-six-months-later/. Accessed June 9, 2022.

        • Rosenbaum L
        No cure without care – soothing science skepticism.
        N Engl J Med. 2021; 384: 1462-1465
        • Johnson NF
        • Velásquez N
        • Restrepo NJ
        • et al.
        The online competition between pro- and anti-vaccination views.
        Nature. 2020; 582: 230-233
      12. Angus Reid Institute. Dwindling group of unvaccinated cite ‘personal freedom’ and ‘health concerns’ as main reasons for dodging the jab. November 3, 2021. Available at: https://angusreid.org/canada-unvaccinated-freedom-reasons/. Accessed June 9, 2022.

        • Redelmeier DA
        The fallacy of interpreting deaths and driving distances.
        Med Decis Making. 2014; 34: 940-943
      13. Redelmeier DA, Zipursky JS. Pedestrian deaths during the COVID-19 pandemic [online ahead of print]. Am J Lifestyle Med. Published online November 26, 2021. Available at: https://journals.sagepub.com/doi/10.1177/15598276211058378. Accessed November 15, 2022.

        • Trogen B
        • Caplan A
        Risk compensation and COVID-19 vaccines.
        Ann Intern Med. 2021; 174: 858-859
        • Rojas Castro MY
        • Orriols L
        • Basha Sakr D
        • et al.
        A web-based prospective cohort study of home, leisure, school and sports injuries in France: a descriptive analysis.
        Inj Epidemiol. 2021; 8: 50
        • Hitti FL
        • Weissman D
        Debunking mRNA Vaccine Misconceptions-An Overview for Medical Professionals.
        Am J Med. 2021; 134: 703-704
      14. National Highway Traffic Safety Administration. Early estimate of motor vehicle traffic fatalities in 2020. Washington DC: United States Department of Transportation. Available at: https://www.nhtsa.gov/press-releases/2020-fatality-data-show-increased-traffic-fatalities-during-pandemic. Accessed June 9, 2022.

        • Redelmeier DA
        • McLellan BA
        Modern medicine is neglecting road traffic crashes.
        PLoS Med. 2013; 10e1001463
        • Bledsoe BE
        • Sweeney RJ
        • Berkeley RP
        • Cole KT
        • Forred WJ
        • Johnson LD
        EMS provider compliance with infection control recommendations is suboptimal.
        Prehosp Emerg Care. 2014; 18: 290-294
        • Prezant DJ
        • Zeig-Owens R
        • Schwartz T
        • et al.
        Medical leave associated with COVID-19 among emergency medical system responders and firefighters in New York City.
        JAMA Netw Open. 2020; 3e2016094
        • Weisburd S
        Identifying moral hazard in car insurance contracts.
        Rev Econ Stat. 2015; 97: 301-313