Observational studies are widely used to estimate vaccine effectiveness under real-world conditions. Two study designs are commonly used: cohort design and test-negative design. A cohort design with explicit emulation of a target trial prevents design-induced bias1,2 and yields estimates of both absolute risks and relative risk, but these estimates may be affected by residual confounding, especially by healthcare-seeking behaviors. The test-negative design3 yields only estimates of relative measures,4 but may reduce confounding because it restricts the study population to those who seek healthcare and get tested for the infection of interest.5,6 However, the test-negative design does not explicitly emulate a target trial and thus its estimates may be affected by design-induced bias. For example, conditioning on receiving a test during the follow-up period is a form of postbaseline stratification that may result in selection bias.5,7

Here we describe a methodologic framework to connect the cohort design and the test-negative design and use both designs to estimate the effectiveness of the BNT162b2 vaccine against COVID-19 outcomes in the largest integrated healthcare system in the United States. We start by specifying a target trial of vaccine effectiveness. Then, we use the observational data to explicitly emulate the target trial under a cohort design, and progressively modify the design until transformation into a test-negative design that no longer emulates a target trial. We then compare the performance of the cohort design and test-negative design when using (1) all available variables in the data and (2) only the subset of the variables that is often available when using test-negative designs. We conclude by providing recommendations for the implementation of these designs in real-world data.

SPECIFICATION OF THE TARGET TRIAL

The preferred approach to estimate vaccine effectiveness is to conduct a randomized trial in which individuals are assigned to either vaccination or no vaccination. Here we specify the (hypothetical) pragmatic trial that would answer the causal question of interest—the target trial.

The key components of the protocol of the target trial are summarized in Table 1. Eligible individuals between 4 January and 27 May 2021 would be randomly assigned to either (1) immediate vaccination with a first dose of the BNT162b2 vaccine with a second dose scheduled 21 days later, or (2) no vaccination at any time over follow-up. The two outcomes of interest are polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infection and symptomatic COVID-19. Individuals would be followed until the outcome, 22 weeks after assignment, or 1 July 2021, whichever occurred first.

TABLE 1. - Specification and Emulation of a Target Trial Evaluating the Effectiveness of the BNT162b2 Vaccine Using Observational Data from Veterans Health Administration Electronic Health Records (4 January–1 July 2021) Target Trial Specification Target Trial Emulation Eligibility criteria •Aged 18 years between 4 January and 27 May 2021
•No previously documented SARS-CoV-2 infection or COVID-19 vaccination
•Known residential address outside of long-term care
•Known smoking status and body-mass index in the past year
•User of VA healthcare system (defined as receiving care at a station eligible to administer the BNT162b2 vaccine and having at least one primary care visit) in the past year
•No healthcare interactions or SARS-CoV-2 tests within the past 7 days (which may indicate preexisting symptomatic SARS-CoV-2 infection) Same as for the target trial, except:
•Previously documented SARS-CoV-2 infections were identified using the VA COVID-19 National Surveillance Tool,8 which integrates data on laboratory tests with natural language processing of clinical notes to capture diagnoses inside and outside the VA healthcare system, supplemented with Medicare data on diagnoses Treatment strategies (1) Immediate vaccination with a first dose of the BNT162b2 vaccine with a second dose scheduled 21 days later, or
(2) No vaccination at any time
The testing strategy is specified to be the same for the two vaccination groups Same as for the target trial. Vaccination was identified using records from the VA Corporate Data Warehouse (i.e., records in the “Immunization” domain, procedures recorded in the “Inpatient” and “Outpatient” domains, and records in the VA COVID-19 Shared Data Resource), linked with Medicare databases. There was strict adherence to vaccine deployment protocols in this population
We confirmed that the frequency of testing was similar in the vaccinated and unvaccinated groups Assignment procedures Individuals are randomly assigned to a strategy at baseline within strata defined by calendar date (5-day bins), age (5-year bins), sex (male or female), race (White, Black, other, or unknown), urbanicity of residence (urban or not urban), geographic location (coded as 18 categories of Veterans Integrated Services Network), smoking status (never, former, or current), body-mass index (<18.5, 18.5–25, 25–30, or ≥30 kg/m2), number of SARS-CoV-2 PCR tests before baseline (0 or 1), and number of influenza vaccinations over the previous 5 years (0, 1–2, 3–4, or ≥5), Individuals will be aware of the assigned treatment strategy We assumed random assignment after matching eligible individuals who were vaccinated with the BNT162b2 vaccine in a 1:1 ratio to eligible unvaccinated individuals, using the same factors used for stratified randomization as in the target trial Follow-up period For each person, follow-up starts on the day of assignment (time zero) and ends on the day of the outcome of interest, 22 weeks after baseline, or the administrative end of follow-up (1 July 2021), whichever occurs first Same as for the target trial Outcome Documented SARS-CoV-2 infection (PCR-confirmed)
Symptomatic COVID-19 (defined as at least one of the following symptoms documented within the VA healthcare system within 4 days before or after a positive PCR test: fever, chills, cough, shortness of breath or difficulty breathing, sore throat, loss of taste or smell, headache, myalgia, diarrhea, and vomiting) Same as for the target trial Causal contrast Intention-to-treat effect, per-protocol effect Observational analogue of per-protocol effect Analysis plan Intention-to-treat analysis: Cumulative incidence (risk) curves and estimates of 22-week risk, risk differences, risk ratios, and incidence rate ratios comparing the BNT162b2-vaccinated vs unvaccinated groups
Per-protocol analysis: Same except that individuals in the no-vaccine group are censored if/when they received the vaccine and prognostic factors are adjusted for Same per-protocol analysis as for the target trial, except that adjustment is achieved by censoring both members of the matched pair when its unvaccinated member received a COVID-19 vaccine

PCR indicates polymerase chain reaction; VA, Department of Veterans Affairs.

Both the intention-to-treat effect and the per-protocol effect would be of interest. In the intention-to-treat analysis, risks (cumulative incidences) would be calculated using the Kaplan–Meier estimator,9 and 22-week risks of each outcome would be calculated and compared between the vaccine groups via differences and ratios. The per-protocol analysis would be identical except that unvaccinated individuals would be censored if and when they received a COVID-19 vaccine, and the analysis would be adjusted for prognostic factors measured at baseline if they became imbalanced between the groups after censoring.

For comparison with previous studies, risks would also be estimated between day 28 (7 days after the second scheduled dose) and the end of follow-up. Excluding this early follow-up period, when immunity is gradually building,10 was standard practice in randomized trials, but may induce selection bias.11 To facilitate comparison with estimates from the randomized trial and other designs that we consider below, incidence rates (number of cases per person–days of follow-up) would also be calculated in each group and vaccine effectiveness would be defined as (1—incidence rate ratio) × 100%. Nonparametric bootstrapping with 500 samples would be used to calculate percentile-based 95% confidence intervals (CIs) for all estimates.

The protocol of the target trial also needs to specify the frequency with which participants would be tested for infection because, by definition, individuals can be determined to have the outcome only on days when a test is performed. That is, the protocol needs to specify a joint intervention strategy on both vaccination and testing. Ideally, individuals would be tested every day so that infections would be detected as soon as possible (Figure 1). Because daily testing may be infeasible, the protocol of a pragmatic trial would establish weekly testing or any other testing strategy (e.g., testing whenever an individual reports symptoms of infection) that is the same for the vaccinated and unvaccinated groups. For each participant, all days before a positive test would be considered days free of the outcome, regardless of whether a test was conducted (with a negative result) or not.

FIGURE 1.:

Study designs when outcome ascertainment requires a test as in studies of vaccine effectiveness for documented infection. Boxes denote person–days contributing to the analysis, C covariate ascertainment, E eligibility criteria assessment, A vaccination status ascertainment, T− negative PCR test, and T+ positive PCR test.

We now use the observational data to (1) explicitly emulate the target trial under a cohort design, (2) perform case–control sampling of the cohort to confirm empirically that the same estimate is obtained, and, last, sequentially implement modifications that transform the case–control design into a test-negative design by (3) further restricting the sampling to person–days with a test, and (4) assessing eligibility, vaccination status, and covariates at the time of testing. Throughout this process, we describe how the modifications associated with the test-negative design result in deviations from the target trial. Figure 1 illustrates the progression of designs considered in this study.

EMULATION OF THE TARGET TRIAL UNDER A COHORT DESIGN

We emulated the above target trial using nationwide healthcare databases from the United States Department of Veterans Affairs, the largest integrated healthcare system in the country, as described previously.12 (Additional details on the target trial emulation are provided in Table 1, and detailed definitions of all study variables are provided in eTable 1; https://links.lww.com/EDE/C100).

Because vaccination was not randomly assigned in the real world, we assumed that vaccination occurred approximately at random within levels of measured prognostic factors: calendar date (5-day bins), age (5-year bins), sex (male or female), race (White, Black, other, or unknown), urban residence (yes or no), geographic location (coded as one of 18 categories of the Veterans Integrated Services Network), smoking status (never, former, or current), body-mass index (<18.5, 18.5–25, 25–30, or ≥30 kg/m2), number of SARS-CoV-2 PCR tests previously received (0 or 1), and number of influenza vaccinations over the previous 5 years (0, 1–2, 3–4, or ≥5). We then matched eligible vaccinated and unvaccinated persons with the same values of these variables in a 1:1 ratio.12 The matching factors are potential confounders associated with the probability of receiving a vaccine and the risk of the outcomes. (Additional details on the matching algorithm are provided in eMethods 1; https://links.lww.com/EDE/C100).

If no prognostic factors are imbalanced between groups, then this matching appropriately emulates randomization in a target trial conducted in individuals with the same distribution of baseline characteristics as the vaccinated persons. We evaluated the balance of measured factors between matched groups via standardized mean differences, with a difference of 0.1 or less considered acceptable.13 To assess the potential for unmeasured confounding (e.g., by healthcare-seeking behavior, as depicted in Figure 2A), we evaluated documented SARS-CoV-2 infection during the first 10 days of follow-up as a negative control outcome that is not affected by vaccination, but for which the effect of vaccination is expected to be confounded similarly to the main outcome.14 Due to the absence of a prespecified testing strategy in the real world, we also checked whether the frequency of testing over follow-up was similar in the vaccinated and unvaccinated groups.

FIGURE 2.:

Causal-directed acyclic graphs (DAGs) under (A) a cohort design, (B) case–control sampling, and (C) case–control sampling restricted to person–days with a test. A denotes vaccination status, T receipt of a PCR test, Y SARS-CoV-2 infection, Y* documented SARS-CoV-2 infection (positive PCR test), U unmeasured confounders (e.g., healthcare-seeking behavior), S selection of cases and controls. Boxes around nodes denote stratification/conditioning. For simplicity, all DAGs omit measured covariates (matching factors) and censoring of matched pairs, and the DAG in panel (C) omits matching on test dates.

The analysis proceeded as for the target trial, except (1) to estimate the per-protocol effect, we censored follow-up of a matched pair if and when its unvaccinated member received a COVID-19 vaccine, (2) we estimated the risk between day 28 and the end of follow-up using matched pairs in which both members were still at risk at the beginning of the period, and (3) we repeated the analysis sequentially starting on each day between 4 January and 27 May 2021.

In sensitivity analyses, we defined documented SARS-CoV-2 infection as a positive PCR or antigen test (identified via the VA COVID-19 National Surveillance Tool),8 and restricted membership in the vaccinated group to individuals who received a BNT162b2 vaccine inside the VA healthcare system (to further restrict the population to those who may be more likely to seek healthcare within the VA system).

Analyses were performed with SAS software, version 8.3 (SAS Institute), SAS PROC IML on Linux Operating System, and R software, version 4.1.2 (R Foundation for Statistical Computing).

Results

Of 571,307 vaccinated individuals who were eligible for the cohort analysis (Figure 3), 546,810 were matched with unvaccinated individuals (see eTable 2; https://links.lww.com/EDE/C100 for comparison with the unmatched population). Measured variables were well-balanced between the vaccinated and unvaccinated groups (Table 2, eFigure 1; https://links.lww.com/EDE/C100). We found a nearly identical risk pattern of documented SARS-CoV-2 infection in the first 10 days of follow-up in both groups (Figure 4), which suggests little unmeasured confounding. The frequency of negative PCR tests during the follow-up was similar in the vaccinated and unvaccinated groups, except that vaccinated individuals received fewer tests during the first week after their first dose and more tests around the second dose (eFigure 2; https://links.lww.com/EDE/C100), which suggests that differences in risk between groups cannot be attributed to differences in testing patterns.

TABLE 2. - Baseline Characteristics of Matched Individuals in the Cohort Analysis for Evaluating the Effectiveness of the BNT162b2 Vaccine, US Veterans Health Administration (4 January–1 July 2021) Vaccinated (n = 546,810) Unvaccinated (n = 546,810) Age group, years (%)  18–39 32,281 (5.9) 32,488 (5.9)  40–49 38,275 (7.0) 38,435 (7.0)  50–59 74,969 (13.7) 75,487 (13.8)  60–69 128,975 (23.6) 130,273 (23.8)  70–79 210,171 (38.4) 207,917 (38.0)  ≥80 62,139 (11.4) 62,210 (11.4) Male sex (%) 502,520 (91.9) 502,520 (91.9) Race (%)  White 392,248 (71.7) 392,248 (71.7)  Black 117,515 (21.5) 117,515 (21.5)  Other 13,093 (2.4) 13,093 (2.4)  Unknown 23,954 (4.4) 23,954 (4.4) Ethnicity (%)  Not Hispanic 490,620 (89.7) 490,569 (89.7)  Hispanic 38,528 (7.0) 38,304 (7.0)  Unknown 17,662 (3.2) 17,937 (3.3)  Urban residence (%) 407,362 (74.5) 407,362 (74.5) Smoking status (%)  Never 199,682 (36.5) 199,682 (36.5)  Current 167,059 (30.6) 167,059 (30.6)  Former 180,069 (32.9) 180,069 (32.9) Body-mass index, kg/m²—mean (SD) 30.3 (6.0) 30.3 (6.1) Comorbidities (%)  Cancer 66,003 (12.1) 61,459 (11.2)  Chronic lung disease 79,647 (14.6) 83,134 (15.2)  Cardiovascular disease 133,992 (24.5) 135,741 (24.8)  Hypertension 333,592 (61.0) 334,791 (61.2)  Diabetes 176,085 (32.2) 180,868 (33.1)  Chronic kidney disease 48,418 (8.9) 49,729 (9.1)  Chronic liver disease 16,762 (3.1) 16,542 (3.0)  Obesity 255,614 (46.7) 255,614 (46.7)  Dementia 9,354 (1.7) 11,184 (2.0)  Substance use disorder 33,926 (6.2) 35,189 (6.4)  Immunocompromised state 31,225 (5.7) 28,670 (5.2) Primary care visits in the past 5 years (%)  1–9 100,363 (18.4) 91,232 (16.7)  10–19 197,086 (36.0) 193,392 (35.4)  20–29 124,367 (22.7) 126,129 (23.1)  ≥30 124,994 (22.9) 136,057 (24.9) Hospital admissions in the past 5 years (%)  0 416,224 (76.1) 420,121 (76.8)  1–4 79,855 (14.6) 70,498 (12.9)  ≥5 50,731 (9.3) 56,191 (10.3) Emergency room visits in the past 5 years (%)  0 272,286 (49.8) 276,220 (50.5)  1–2 129,431 (23.7) 125,171 (22.9)  3–4 59,282 (10.8) 57,355 (10.5)  ≥5 85,811 (15.7) 88,064 (16.1) Influenza vaccinations in the past 5 years (%)  0 74,190 (13.6) 74,190 (13.6)  1–2 107,187 (19.6) 107,187 (19.6)  3–4 177,800 (32.5) 177,800 (32.5)  ≥5 187,633 (34.3) 187,633 (34.3) PCR tests in the past (%)  0 427,327 (78.1) 427,327 (78.1)  1–2 101,365 (18.5) 101,900 (18.6)  3–4 14,134 (2.6) 13,544 (2.5)  ≥5 3,984 (0.7) 4,039 (0.7)

PCR indicates polymerase chain reaction.

FIGURE 3.:

Selection of individuals for the emulation of a target trial evaluating the effectiveness of the BNT162b2 vaccine under a cohort design, US Veterans Health Administration (4 January–1 July 2021). VA denotes Department of Veterans Affairs.

FIGURE 4.:

Negative control outcome: cumulative incidence of documented SARS-CoV-2 infections in the first 10 days after the first dose by vaccination status under a cohort design, US Veterans Health Administration (4 January–1 July 2021).

Over 22 weeks, 2,808 SARS-CoV-2 infections were documented, of which 1,308 were detected as symptomatic within the VA healthcare system. Among individuals who received a first dose of the vaccine and had at least 21 days of follow-up, 97% received a second dose of the vaccine (69% on day 21, 90% before day 24, and 93% before day 28). Data for 61% of the unvaccinated individuals and their matched pairs were censored when the unvaccinated received a vaccine.

Figure 5 shows the cumulative incidence curves. The estimated 22-week risk ratios (95% CI) for the BNT162b2 vaccine vs. no vaccine were 0.30 (0.28 to 0.35) for documented SARS-CoV-2 infection and 0.26 (0.22 to 0.30) for symptomatic COVID-19 (eTable 3; https://links.lww.com/EDE/C100). In the period starting on day 28, estimated vaccine effectiveness was 87.2% (85.4% to 91.8%) for symptomatic COVID-19 (Table 3); as a benchmark, the estimates also based on incidence rate ratios for symptomatic COVID-19 from a randomized trial were 95.0% (90.3% to 97.6%) up to 14 weeks after the second dose10 and 91.3% (89.0% to 93.2%) up to 6 months (~24 weeks) after the second dose.15 (See eMethods 2; https://links.lww.com/EDE/C100 for a discussion of differences between risk ratio and rate ratio estimates). Estimates were similar under all sensitivity analyses (eTable 4; https://links.lww.com/EDE/C100, eFigure 3; https://links.lww.com/EDE/C100).

TABLE 3. - Estimated Vaccine Effectiveness (VE)a of the BNT162b2 Vaccine Under Different Designs, US Veterans Health Administration (4 January–1 July 2021) From Day 0 From Day 28 Cases VE, % (95% CI) Cases VE, % (95% CI) Documented SARS-CoV-2 infection  Target trial emulation—Cohort 2,808 63.6 (59.5, 65.9) 1,292 80.4 (77.1, 82.7)  Target trial emulation—Case–control sampling 2,808 63.5 (59.3, 65.7) 1,292 80.6 (77.0, 82.8)  Case–control sampling restricted to test days 2,798 59.6 (54.2, 62.9) 1,290 80.4 (76.6, 83.2)  Test-negative designb 14,159 66.3 (63.9, 68.5) 13,407 80.2 (78.2, 82.0) Symptomatic COVID-19  Target trial emulation—Cohort 1,308 66.3 (61.9, 70.9) 504 87.2 (85.4, 91.8)  Target trial emulation—Case–control sampling 1,308 66.0 (61.6, 70.7) 504 87.2 (85.2, 91.7)  Case–control sampling restricted to test days 1,104 61.9 (56.4, 69.9) 455 87.0 (84.3, 92.6)  Test-negative designb 6,696 67.8 (64.2, 71.1) 6,308 86.8 (84.2, 89.0)

aAll analyses adjusted for calendar date, age, sex, race, urban residence, geographic location, smoking status, body-mass index, number of SARS-CoV-2 PCR tests previously received, and number of influenza vaccinations over the previous 5 years.

bAs the test-negative design does not explicitly specify the period of follow-up, we considered estimates from day 0 as “receipt of the first dose of BNT162b2 between 4 January 2021 and the test date” and estimates from day 28 as “receipt the first dose of BNT162b2 between 4 January 2021 and 28 days before the test date.”

FIGURE 5.:

Cumulative incidence of COVID-19 Outcomes by vaccination status under a cohort design, US Veterans Health Administration (4 January–1 July 2021).

CASE–CONTROL SAMPLING OF THE ABOVE COHORTS

We performed risk-set case–control sampling16 of each of the above sequential cohorts (after matching and censoring). Cases were all individuals with a positive PCR test over the study period. For each case, we randomly selected 1,000 controls who were under follow-up and without a positive PCR test on the case’s test date (Figure 2B). The odds ratio from this case–control sampling is an unbiased estimator of the incidence rate ratio in the target trial.16 However, the case–control sampling generally precludes the estimation of absolute risk. We used conditional logistic regression to estimate odds ratios, and defined vaccine effectiveness as (1—odds ratio) × 100%. We repeated the case–control sampling in each of the 500 bootstrap samples from the cohort design to calculate percentile-based 95% CIs for all estimates.

Results

As expected, vaccine effectiveness estimates were the same as those from the cohort (Table 3).

In the analyses that follow, we sequentially implement modifications that transform this case–control design into a test-negative design.

CASE–CONTROL SAMPLING RESTRICTED TO PERSON–DAYS WITH A TEST

Our analyses above strongly suggest little residual confounding (e.g., by healthcare-seeking behavior), because there was similar testing frequency for the vaccinated and unvaccinated groups, comparable distributions of measured risk factors, nearly identical risk patterns for the negative control outcome, and effect estimates were close to those of a randomized trial. In other settings, however, there may be concerns about unmeasured confounding because those who seek healthcare and get tested for the infection may be different from those who are not tested. A proposed approach to tackle this problem is to restrict the analysis to individuals who received a test during the follow-up. However, this approach is the equivalent of a postbaseline restriction in the target trial and thus may result in selection bias. The magnitude of the bias increases with the amount of residual confounding and the association of testing with vaccination status and with the outcome of interest (Figure 2C).17–19

To implement this approach, we repeated the case–control sampling described above, but selected matched controls only from person–days with a negative test near the case’s test date20–23 (in a 5-day bin), in a ratio of 4 controls:1 case. For symptomatic COVID-19, we only considered person–days with a test and with symptoms recorded within 4 days of the test date. As above, we used conditional logistic regression to estimate odds ratios and defined vaccine effectiveness as (1—odds ratio) × 100%. The odds ratio from this design can be interpreted as the rate ratio from a target trial with daily testing if both groups were tested daily or adequate adjustment could be made for prognostic factors associated with differences in testing strategies.

Results

In the period starting on day 28, the estimated vaccine effectiveness was 80.4% (76.6% to 83.2%) for documented SARS-CoV-2 infection, and 87.0% (84.3% to 92.6%) for symptomatic COVID-19 (Table 3). These estimates were similar to those obtained under the previous designs.

TEST-NEGATIVE DESIGN

The test-negative design resembles a case–control sampling restricted to person–days with a test. However, the test-negative design deviates from the emulation of a target trial because it uses the time of testing, rather than the start of follow-up of the target trial, to determine eligibility, define vaccination status, and assess covariates for confounding adjustment. This is equivalent to adjusting for postbaseline variables in the target trial and thus may induce selection bias.24,25

To implement a test-negative design in our data, we applied the same eligibility criteria as in the cohort analysis (except “having no healthcare interaction or SARS-CoV-2 tests within the past seven days”), but we assessed eligibility on the test day rather than at time zero of follow-up. We then matched cases to controls in a 1:4 ratio on the test date (5-day bins, same as above). For analyses of symptomatic COVID-19, we restricted cases and controls to individuals who had symptoms around the time of testing. We classified individuals as vaccinated if they received the first dose of BNT162b2 between 4 January 2021, and 28 days before the test date, and unvaccinated if they had not received any dose of vaccine before the test date. In an attempt to estimate vaccine effectiveness that also includes the first 28 days of follow-up, we conducted separate analyses in which individuals were instead classified as vaccinated if they received the first dose of BNT162b2 between 4 January 2021, and the test date (i.e., these analyses included individuals vaccinated in the 28 days before the test date). Multivariable conditional logistic regression was used to estimate odds ratios and 95% CIs, conditional on the matched sets and adjusted for covariates (same as the matching factors in the cohort design, except calendar date at time zero) measured at the time of testing. We estimated vaccine effectiveness as (1—odds ratio) × 100%.

Finally, in sensitivity analyses for our test-negative designs, we (1) excluded individuals with a history of documented SARS-CoV-2 infection within 90 days (vs. ever) before the test date, (2) removed the eligibility criterion of receiving care at a station eligible to administer the BNT162b2 vaccine, (3) redefined controls as individuals with exclusively negative tests during the follow-up, (4) assessed eligibility criteria and covariates on 4 January 2021, instead of on the test date, (5) restricted each individual to be matched as a control at most once, (6) additionally adjusted for symptoms recorded in the database within 4 days of the test date (via conditional logistic regression), (7) conducted a test-negative analysis within each of the sequential cohorts used to emulate the target trial, and (8) only considered vaccines administered inside the VA healthcare system.

Results

Of 1,176,837 SARS-CoV-2 PCR tests documented in the VA healthcare system between 4 January and 1 July 2021, 363,677 tests met the eligibility criteria (Figure 6). After excluding tests within 28 days of vaccination, 13,407 test-positive cases were matched to 53,628 test-negative controls. The matched controls had a lower proportion of vaccinated individuals than the initially eligible controls (eTable 5; https://links.lww.com/EDE/C100). Compared with matched controls, matched cases included a higher proportion of younger individuals, never smokers, documented symptoms around the test date, and a lower proportion of individuals with comorbidities (except for obesity) and markers of high healthcare utilization (Table 4). 4.9% of cases and 16.5% of controls were vaccinated.

TABLE 4. - Characteristicsa of the Matched Study Participants Under a Test-negative Design, US Veterans Health Administration (4 January–1 July 2021) Cases (n = 13,407) Controls (n = 53,628) BNT162b2 vaccinatedb (%) 651 (4.9) 8,831 (16.5) Age group, years (%)  18–39 1,749 (13.0) 4,922 (9.2)  40–49 1,581 (11.8) 5,008 (9.3)  50–59 2,740 (20.4) 9,444 (17.6)  60–69 3,183 (23.7) 14,676 (27.4)  70–79