COVID Vaccine Hesitancy and Risk of a Traffic Crash - The American Journal of Medicine

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

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.

1

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.

2 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.

3 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.

4

Analysis of factors influencing aggressive driver behavior and crash involvement.

,5

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).

6 SAGE Working Group on Vaccine Hesitancy

Vaccine hesitancy: definition, scope and determinants.

,7

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).

8

Words matter: vaccine hesitancy, vaccine demand, vaccine confidence, herd immunity and mandatory vaccination.

,  ,  10

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).

11

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.

12

Telling more than we can know: verbal reports on mental processes.

,  13

Lifting the veil of morality: choice blindness and attitude reversals on a self-transforming survey.

,  14

Determinants of social desirability bias in sensitive surveys: a literature review.

,  15

Consistency between stated and revealed preferences: a discrete choice experiment and a behavioural experiment on vaccination behaviour compared.

,  16

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,  17

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.

18

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.

19

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.

20

Characterological, situational, and behavioral risk factors for motor vehicle accidents: a prospective examination.

,  21

Healthy user and related biases in observational studies of preventive interventions: a primer for physicians.

,  22

Escaping Catch-22 – overcoming Covid vaccine hesitancy.

,  23

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.

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.

3 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.

,26

COVID-19 vaccination intention during early vaccine rollout in Canada: a nationwide online survey.

,  , 

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

Vaccination Status

We identified individuals using encrypted identifiers from official government registries.

31

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.

This population-based approach was fully comprehensive, with the exception of excluding cases marked as invalid, containing faulty identifiers, or missing a birthdate.

33

A summary of studies on the quality of health care administrative databases in Canada.

,  ,  35

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).

36

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.

,37

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.

38

Risks of serious injury with testosterone treatment.

,39

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.

40

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.

,41

Injuries in Ontario: ICES Atlas.

We directed specific attention to diseases associated with traffic risks, including alcohol misuse, sleep apnea, diabetes, depression, and dementia.

42 World Health Organization

International Statistical Classification of Diseases and Related Health Problems.

,43

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.

44

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).

45

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).

46 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).

47

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).

45

Development of a Consensus on Evidence-Based Quality of Care Indicators for Canadian Emergency Departments. ICES Investigative Report.

,46 Canadian Institute for Health Information (CIHI)

CIHI Data Quality Study of Emergency Department Visits for 2004-2005: volume II of IV: Main Study Findings.

,48

Administrative data accurately identified intensive care unit admissions in Ontario.

,  49

Guidelines on Person-Level Costing Using Administrative Databases in Ontario.

,  50

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).

51

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.

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 Cumulative 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 Forest 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).

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

).

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.

43

Medical interventions to reduce motor vehicle collisions.

,

Our research agrees with past studies about psychology contributing to traffic risks.

53

Attitudes associated with behavioral predictors of serious road traffic crashes: results from the GAZEL cohort.

,54

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.

55

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.

56

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.

57

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.

58

Lethal misconceptions: interpretation and bias in studies of traffic deaths.

,59

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.

60

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.

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.

62

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.

63

The online competition between pro- and anti-vaccination views.

,

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.

65

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).

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.

67

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

).

68

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.

58

Lethal misconceptions: interpretation and bias in studies of traffic deaths.

These uncertainties are further opportunities for future science.

10

Impact of Vax-a-Million Lottery on COVID-19 vaccination rates in Ohio.

The current findings can help address 4 common misunderstandings.

69

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.

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.

1,71

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.

72

EMS provider compliance with infection control recommendations is suboptimal.

,73

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.

74

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

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

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

§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.

Analysis of General Matched Cohort Pairs

Tabled 1

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.

Analysis of Stringent Matched Cohort Pairs

Tabled 1

“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

§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.

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Article Info

Publication History

Published online: December 02, 2022

Accepted: November 2, 2022

Received: October 14, 2022

Publication stage

In Press Journal Pre-Proof

Footnotes

Funding: This project was supported by a Canada Research Chair in Medical Decision Sciences, the Canadian Institutes of Health Research, the Graduate Diploma in Health Research at the University of Toronto, and the National Sciences & Engineering Research Council of Canada. The views expressed are those of the authors and do not necessarily reflect the Ontario Ministry of Health.

Conflicts of Interest: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, and approval of the manuscript. All authors have no financial or personal relationships or affiliations that could influence the decisions and work on this manuscript.

Authorship: The lead author (DAR) had full access to all the data in the study, takes responsibility for the integrity of the data, and is accountable for the accuracy of the analysis. Other contributions include: Conceptualization (DAR, JW, DT), data curation (DAR, DT), formal analysis (DAR, JW, DT), funding acquisition (DAR, JW), investigation (DAR, JW, DT), methodology (DAR, JW, DT), project administration (DAR, JW), resources (DAR, JW), software (nil), supervision (DAR), validation (DAR, JW, DT), visualization (DAR, JW, DT), original draft (DAR), and revisions (DAR, JW, DT). The protocol was approved by the Sunnybrook Research Ethics board and conducted using privacy safeguards at the Institute for Clinical Evaluative Sciences. Parts of this material are based on data compiled by CIHI; however, the analyses, conclusions, and statements expressed are those of the authors and not necessarily those of CIHI. Study participants contributed in important ways to this research yet it was not feasible to directly involve individuals in study design or conduct. Members of the public provided feedback on study results and earlier presentations of this material.

Data Availability: The study dataset is held securely in coded form at the Institute for Clinical Evaluative Sciences (ICES). While legal data sharing agreements between ICES and data providers (eg, health care organizations and government) prohibit ICES from making the dataset publicly available, access may be granted to those who meet criteria for confidential access, available at www.ices.on.ca/DAS (email [email protected]). The full dataset creation plan and analytic code are available from the authors upon request, understanding that the computer programs might rely upon coding templates or macros that are unique to ICES.

Identification

DOI: https://doi.org/10.1016/j.amjmed.2022.11.002

Copyright

© 2022 Elsevier Inc. All rights reserved.

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