Covid-19 vaccine effectiveness against general SARS-CoV-2 infection from the omicron variant: A retrospective cohort study

Lior Rennert; Zichen Ma; Christopher S McMahan; Delphine Dean

doi:10.1371/journal.pgph.0001111

. 2023 Jan 10;3(1):e0001111. doi: 10.1371/journal.pgph.0001111

Covid-19 vaccine effectiveness against general SARS-CoV-2 infection from the omicron variant: A retrospective cohort study

Lior Rennert ^1,^*, Zichen Ma ², Christopher S McMahan ³, Delphine Dean ⁴

Editor: Patrick DMC Katoto⁵

PMCID: PMC9910751 NIHMSID: NIHMS1866243 PMID: 36777314

Abstract

We aim to estimate the effectiveness of 2-dose and 3-dose mRNA vaccination (BNT162b2 and mRNA-1273) against general Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection (asymptomatic or symptomatic) caused by the omicron BA.1 variant. This propensity-score matched retrospective cohort study takes place in a large public university undergoing weekly Coronavirus Disease 2019 (Covid-19) testing in South Carolina, USA. The population consists of 24,145 university students and employees undergoing weekly Covid-19 testing between January 3^rd and January 31^st, 2022. The analytic sample was constructed via propensity score matching on vaccination status: unvaccinated, completion of 2-dose mRNA series (BNT162b2 or mRNA-1273) within the previous 5 months, and receipt of mRNA booster dose (BNT162b2 or mRNA-1273) within the previous 5 months. The resulting analytic sample consists of 1,944 university students (mean [SD] age, 19.64 [1.42] years, 66.4% female, 81.3% non-Hispanic White) and 658 university employees (mean [SD] age, 43.05 [12.22] years, 64.7% female, 83.3% non-Hispanic White). Booster protection against any SARS-CoV-2 infection was 66.4% among employees (95% CI: 46.1–79.0%; P < .001) and 45.4% among students (95% CI: 30.0–57.4%; P < .001). Compared to the 2-dose mRNA series, estimated increase in protection from the booster dose was 40.8% among employees (P = .024) and 37.7% among students (P = .001). We did not have enough evidence to conclude a statistically significant protective effect of the 2-dose mRNA vaccination series, nor did we have enough evidence to conclude that protection waned in the 5-month period after receipt of the 2^nd or 3^rd mRNA dose. Furthermore, we did not find evidence that protection varied by manufacturer. We conclude that in adults 18–65 years of age, Covid-19 mRNA booster doses offer moderate protection against general SARS-CoV-2 infection caused by the omicron variant and provide a substantial increase in protection relative to the 2-dose mRNA vaccination series.

Introduction

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus that causes Coronavirus Disease 2019 (Covid-19), was first reported in December of 2019 in Wuhan City, China [1]. As of December 6^th, 2022, the World Health Organization has reported over 6.4 million cases of Coronavirus Disease 2019 (Covid-19) [2]. SARS-CoV-2 is primarily transferred through droplets and aerosol particles continating the virus [3]. The B.1.1.529 (omicron) variant of SARS-CoV-2, first detected in South Africa in November 2021, is more infectious than any previous variant of SARS-CoV-2 [4]. Omicron has caused a record number of daily SARS-CoV-2 infections in the United States (US) and world wide [5]. While the Covid-19 mRNA vaccines (BNT162b2 or mRNA-1273) have shown initial strong protection against previous SARS-CoV-2 variants [6–8], protection against symptomatic infection quickly declines [6, 9]. Furthermore, several studies have shown that both the 2-dose and 3-dose mRNA vaccination series offer less protection against the omicron variant [10–12]. Additional studies have demonstrated Covid-19 vaccines have lower neutralization efficacy against omicron and are less protective against hospitalization [10, 13]. However, data on the extent to which Covid-19 vaccines are protective against general infection from omicron, including asymptomatic, presymptomatic, and symptomatic infection, is limited.

While SARS-CoV-2 infections caused by the omicron variant are associated with a reduced risk of severe disease compared to previous variants [14], high infection rates increase the risk of severe disease for the population as a whole. Protection against any SARS-CoV-2 infection is therefore important for reduction of both individual and community risk. In this study, we assess effectiveness of the 2-dose and 3-dose messenger RNA (mRNA) vaccination series approved by the U.S. Food and Drug Administration (FDA), BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna), in a large public university student and employee population undergoing mandatory weekly testing during January 2022. Because such screening captures all infections (including asymptomatic and pre-symptomatic), this study setting is ideal for evaluation of protection against general SARS-CoV-2 infection.

Methods

Study design and population

The study population consists of students and employees undergoing mandatory weekly testing between January 3^rd and January 31^st of 2022 at Clemson University in South Carolina (SC). The study sample was restricted to young-adult students between 18 and 24 years and university employees between 18 and 64 years. Exclusion criteria is provided in Fig 1, and consists of student athletes, recipient of a vaccine dose other than BNT162b2 or mRNA-1273, individuals receiving the second dose of BNT162b2 less than 21 days after their first dose or second dose of mRNA-1273 less than 28 days after first dose, recipient of a booster dose less than 5 months after the second dose of the mRNA-1273 or BNT162b2, and individuals with invalid vaccination cards. Per surveillance testing protocols, individuals testing positive were not required to partake in mandatory pre-arrival or surveillance testing for 90 days since the original positive test result, and are therefore excluded from analyses [15]. Individuals who have self-reported conditions impacting immune response, including HIV, cancer, lupus, rheumatoid arthritis, or solid organ or bone marrow transplant, and who have self-reported medication use of steroids, chemotherapy, or immunosuppressants, were excluded from the sample. Students vaccinated prior to March 31^st, 2021, and employees vaccinated prior to March 8^th, 2021, were excluded, since only high-risk individuals were eligible to be vaccinated in SC during this time period.

Fig 1 — *By end of follow-up (Jan 31^st, 2022). ^† Booster eligible individuals are those receiving their 2^nd mRNA dose prior to August 24, 2021. The fully vaccinated, *booster eligible* cohort could consist of a mix of fully vaccinated individuals (completion of 2-dose mRNA series) and boosted individuals (completion of 3-dose mRNA series), and are therefore excluded. The fully vaccinated, *booster ineligible* cohort consists of individuals vaccinated within 5 months of end of follow-up (Jan 31^st, 2022) and were therefore not eligible to receive the booster dose.

Ethics statement

Ethical review for this study was obtained by the Institutional Review Board (IRB) of Clemson University (IRB # 2021-043-02). No consent was needed for this study; students consented to being tested and voluntarily uploaded vaccination information, and we used de-identified data for these analyses.

Vaccination status

Vaccine information was collected through voluntary upload of vaccination cards through Clemson University’s Covid-19 Voluntary Vaccine Upload Tool. Financial incentives were provided to individuals uploading proof of complete vaccination during the Fall 2021 semester [16]. Individuals also had the option to upload information on booster doses at any point. While this was encouraged through university communications, financial incentives were not offered for booster upload. Vaccination data includes vaccine manufacturer and administration dates of first, second, and booster doses. At Clemson University, the Fall semester typically starts in middle to late-August and continues through mid-December. The spring semester typically starts in early to mid-January and continues through early May.

Individuals who were not affiliated with the University during the Fall 2021 semester were excluded from analyses, since this population was not eligible to participate in the University’s financial incentive program for voluntary upload of Covid-19 vaccination and is therefore subject to underreporting. Furthermore, the incentive program only required proof of full vaccination. That is, university students and employees were provided financial incentives to upload proof of completion of 2-dose Covid-19 mRNA vaccine series (BNT162b2 or mRNA-1273) or 1-dose of the Jansen/Johnson and Johnson (Ad26.COV2.S) Covid-19 vaccine during the Fall 2021 semester. Many individuals were not eligible for a booster dose when they provided proof of complete vaccination. Even among those that were booster eligible (defined as completed 2-dose series mRNA series > 5 months ago), there were no incentives to upload proof of the booster dose and thus many students and employees who received a booster dose likely never reported it.

Therefore, in this population, individuals labeled as “booster eligible” consist of a mixed population of those who truly received only 2 doses, but also those who received the booster dose and never reported it. Since is no way of differentiating between these two subgroups, we cannot include individuals that were booster eligible but never reported a booster dose. Otherwise, there would be many boosted individuals classified as only completing full vaccination. Therefore, from the fully vaccinated cohort (i.e., people reporting only a 2-dose mRNA vaccination series), we excluded all individuals who received their 2^nd dose more than 5 months prior to the end of the follow-up (Jan 31^st, 2022). This ensures that the resulting fully vaccinated cohort would be devoid of boosted individuals since its constituents would not be eligible to receive the mRNA booster dose during the study period.

Vaccination status was coded as partially vaccinated if 14-days had passed since the first dose of mRNA-1273 or BNT162b2, fully vaccinated if at least 14 days had passed since the second dose of BNT162b2 or mRNA-1273 [17], and boosted if 7 days had passed since the receipt of a the BNT162b2 or mRNA-1273 booster dose [18]. The analytic sample was restricted to individuals reporting no vaccination, completion of the 2-dose mRNA vaccination series within 5 months of end of follow-up (fully vaccinated), and receipt of an mRNA booster dose (boosted).

SARS-CoV-2 testing

Pre-arrival testing was required for all individuals between January 3^rd and January 12^th (in-person instruction), followed by weekly surveillance testing. Residential students were also required to test upon arrival to residence halls (beginning January 9^th). All students had the option of receiving a SARS-CoV-2 test on campus or obtaining their test elsewhere and uploading their result to the University’s Covid-19 test upload portal. Accepted methods included nasal, throat, or saliva-based polymerase-chain-reaction (PCR) tests [19]. Testing was available on-campus through the University’s high-complexity CLIA-certified clinical diagnostics lab, which utilized saliva-based PCR tests. This compromised the majority of tests conducted during the study follow-up period (N = 101,982; 92.9% of all tests). Test results with quantification cycle (Cq) values under 33 were considered positive for SARS-CoV-2 (test sensitivity ≥ 95%, test specificity ≥ 99.5%) [20, 21]. Testing was mandated for all university-affiliated individuals; access to campus facilities was restricted until a negative test result was obtained. Therefore, unreported at-home testing is not expected to impact study findings. Pre-arrival and surveillance testing protocols for previous semesters, including clinical descriptions of testing procedures, are described elsewhere [15, 20]. It is estimated that 99.2% of all SARS-CoV-2 infections in South Carolina were caused by the original omicron variant (BA.1) in January of 2022 [22].

Data collection and management

SARS-CoV-2 testing data was collected by three independent sources: Rymedi (Greenville, SC, USA) for tests conducted by the University CLIA-certified diagnostics lab, which included demographic and clinical information along with university affiliation (collected at test registration) [20], Clemson University Student Health Center for all other tests conducted on campus, and Clemson Computing and Information Technology (CCIT) for tests conducted off-campus and uploaded via the testing upload portal. Vaccine information was collected through CCIT via the voluntary vaccination upload tool. All data was stored and managed on a secure server provide by Clemson University.

Propensity score matching

Propensity-score matching was used to adjust for confounding of vaccine effectiveness estimates due to reporting bias and differences in health-seeking behavior. To achieve covariate balance while preserving sample size, matching was conducted using a common-referent approach [23]. In the student sample, 1:1 nearest neighbor caliper matching was conducted between boosted and fully vaccinated individuals and 1:2 nearest neighbor caliper matching was conducted between boosted and unvaccinated individuals [24, 25]. The post-matched student sample consists of unvaccinated and fully vaccinated individuals who had a common match with a boosted individual [23]. In the employee study sample, 1:4 nearest neighbor caliper matching was conducted between fully vaccinated and boosted individuals and 1:4 nearest neighbor caliper matching was conducted between fully vaccinated and unvaccinated individuals. The post-matched employee sample consists of boosted and unvaccinated individuals who had a common match with a fully vaccinated individual. The caliper width was set to 0.20 times the standard deviation of the logit of the propensity scores [26]. Variables in the propensity score model included age, sex, affiliation (students: residential or non-residential living, employees: faculty or staff), graduate student status (students only), race/ethnicity, self-reported pre-existing conditions (high blood pressure, heart disease, diabetes, overweight or obesity, kidney disease or dialysis, previous stroke or other neurological condition affecting ability to cough, liver disease, or lung disease), use of tobacco or nicotine products, number of SARS-CoV-2 tests in Fall 2020, Spring 2021, and Fall 2021 semesters, and history of previous SARS-CoV-2 infection.

Statistical analyses

Demographic and clinical characteristics are provided for the analytic sample and stratified by vaccination status in Tables 1 and 2. Differences between unvaccinated, fully vaccinated, and boosted individuals were assessed using ANOVA for continuous variables and chi-squared tests for categorical variables. Time-varying Cox proportional hazard models were used to estimate the unadjusted hazard rate (HR) and adjusted hazard rate (aHR) of SARS-CoV-2 infection by vaccination status during the follow-up period (1/3/2022-1/31/2022). The outcome was days between start of follow-up and date of first SARS-CoV-2 positive test (event date). Individuals who did not test positive during the follow-up period were right censored at their last negative test date (censoring date). Vaccination status was modeled as a time-varying exposure variable. Because university students tend to engage in high-density social interactions which result in exposure to higher viral loads [27], models were run independently for student and employee populations. We adjust for all potential confounders included in the propensity score models to account for residual imbalance after matching [28]. Specifically, models were adjusted for previous SARS-CoV-2 infection history, age, race, gender, residential status, self-reported pre-existing conditions, use of nicotine or other smoking products, and number of previous SARS-CoV-2 tests (surrogate for health-seeking behavior) [29, 30]. Unadjusted and adjusted vaccine effectiveness (i.e., protection) was estimated by 1-HR and 1-aHR, respectively; [15] vaccine effectiveness estimates are supplemented with 95% confidence intervals (CI) and p-values (where appropriate). Overall mRNA vaccine protection was estimated via Model 1.1 (S1 Appendix). Effectiveness by vaccine manufacturer was estimated via Model 1.2 (S1 Appendix).

Table 1. Descriptive characteristics for students in the analytic sample after propensity score matching.

Characteristic	Total N = 1944	Unvaccinated N = 954	Fully vaccinated^● N = 495	Booster N = 495	P-value
Age: Mean (SD)	19.64 (1.42)	19.56 (1.42)	19.73 (1.43)	19.70 (1.40)	0.07
Race/Ethnicity: N (%)
…White non-Hispanic	1580 (81.3%)	778 (81.6%)	407 (82.2%)	395 (79.8%)	0.59
…Black non-Hispanic	91 (4.7%)	43 (4.5%)	24 (4.8%)	24 (4.8%)	0.94
…Any race Hispanic	143 (7.4%)	70 (7.3%)	34 (6.9%)	39 (7.9%)	0.83
…All other races non-Hispanic	130 (6.7%)	63 (6.6%)	30 (6.1%)	37 (7.5%)	0.67
Gender: N (%)
…Female	1291 (66.4%)	639 (67.0%)	330 (66.7%)	322 (65.1%)	0.75
…Male	646 (33.2%)	311 (32.6%)	164 (33.1%)	171 (34.5%)	0.76
…Not reported	7 (0.4%)	4 (0.4%)	1 (0.2%)	2 (0.4%)	0.79
Affiliation: N (%)
…Residential	985 (50.7%)	518 (54.3%)	226 (45.7%)	241 (48.7%)	0.005
…Non-residential	959 (49.3%)	436 (45.7%)	269 (54.3%)	254 (51.3%)	0.005
Graduate student: N (%)	63 (3.2%)	31 (3.2%)	17 (3.4%)	15 (3.0%)	0.94
Pre-existing condition: N (%) ^■	58 (3.0%)	30 (3.1%)	13 (2.6%)	15 (3.0%)	0.7
…High blood pressure	9 (0.5%)	2 (0.2%)	3 (0.6%)	4 (0.8%)	0.45
…Heart disease	1 (0.1%)	1 (0.1%)	0 (0.0%)	0 (0.0%)	1
…Diabetes	14 (0.7%)	9 (0.9%)	1 (0.2%)	4 (0.8%)	0.2
…Overweight	36 (1.9%)	18 (1.9%)	9 (1.8%)	9 (1.8%)	1
…Kidney disease	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	NA
…Cough inefficacy	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	NA
…Liver disease	1 (0.1%)	1 (0.1%)	0 (0.0%)	0 (0.0%)	1
Use of tobacco or nicotine products: N (%)	37 (1.9%)	15 (1.6%)	13 (2.6%)	9 (1.8%)	0.24
SARS-CoV-2 Tests Per Person: Mean (SD)	30.61 (11.96)	29.67 (11.66)	30.58 (12.15)	32.45 (12.17)	<0.001
…Fall 2020 Semester	3.62 (4.11)	3.45 (4.05)	3.65 (4.10)	3.92 (4.24)	0.12
…Spring 2021 Semester	7.30 (7.59)	6.98 (7.42)	7.38 (7.53)	7.84 (7.93)	0.12
…Fall 2021 Semester	16.20 (3.49)	16.07 (3.46)	16.21 (3.25)	16.45 (3.75)	0.15
…Spring 2022 Semester^¶^*	3.49 (1.44)	3.17 (1.35)	3.34 (1.44)	4.24 (1.34)	<0.001
Previous SARS-CoV-2 Infection: N (%) ^†	444 (22.8%)	218 (22.9%)	114 (23.0%)	112 (22.6%)	0.99
SARS-CoV-2 Infection During Follow-up: N (%) ^#	550 (28.3%)	299 (31.3%)	171 (34.5%)	80 (16.2%)	<0.001

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^● 2^nd dose administered within 5.25 months of study end date

^■ Self-reported presence of any of the following conditions: high blood pressure, heart disease, diabetes, overweight or obesity, kidney disease or dialysis, previous stroke or other neurological condition affecting ability to cough, liver disease, or lung disease; sample size may not add to N due to non-selection of specific conditions.

^¶ During follow-up period (1/3/2022 to 1/31/2022)

^† Infection occurring prior to follow-up period (1/3/22)

^# % is proportion of individuals within each population infected with SARS-CoV-2 during follow-up period

* Variable not included in propensity score model

Table 2. Descriptive characteristics for employees in the analytic sample after propensity score matching.

Characteristic	Total N = 658	Unvaccinated N = 342	Fully vaccinated^● N = 87	Booster N = 229	P-value
Age: Mean (SD)	43.05 (12.22)	41.70 (12.61)	42.97 (11.41)	45.10 (11.69)	0.005
Race/Ethnicity: N (%)
…White, non-Hispanic	548 (83.3%)	289 (84.5%)	69 (79.3%)	190 (83.0%)	0.5
…Black, non-Hispanic	45 (6.8%)	21 (6.1%)	8 (9.2%)	16 (7.0%)	0.6
…All other, races non-Hispanic	65 (9.9%)	32 (9.4%)	10 (11.5%)	23 (10.0%)	0.83
Gender: N (%)
…Female	426 (64.7%)	225 (65.8%)	58 (66.7%)	143 (62.4%)	0.66
…Male	232 (35.3%)	117 (34.2%)	29 (33.3%)	86 (37.6%)	0.66
Affiliation: N (%)
…Faculty	89 (13.5%)	39 (11.4%)	10 (11.5%)	40 (17.5%)	0.1
…Staff	569 (86.5%)	303 (88.6%)	77 (88.5%)	189 (82.5%)	0.1
Pre-existing condition: N (%) ^■	184 (28.0%)	86 (25.1%)	23 (26.4%)	75 (32.8%)	0.91
…High blood pressure	88 (13.4%)	44 (12.9%)	10 (11.5%)	34 (14.8%)	0.87
…Heart disease	5 (0.8%)	3 (0.9%)	0 (0.0%)	2 (0.9%)	0.88
…Diabetes	23 (3.5%)	7 (2.0%)	2 (2.3%)	14 (6.1%)	1
…Overweight	128 (19.5%)	57 (16.7%)	15 (17.2%)	56 (24.5%)	1
…Kidney disease	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	NA
…Cough inefficacy	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	NA
…Liver disease	2 (0.3%)	1 (0.3%)	0 (0.0%)	1 (0.4%)	1
Use of tobacco or nicotine products: N (%)	16 (2.4%)	8 (2.3%)	3 (3.4%)	5 (2.2%)	0.84
SARS-CoV-2 Tests Per Person: Mean (SD)	27.55 (13.43)	26.34 (13.84)	27.39 (13.30)	29.42 (12.67)	0.03
…Fall 2020 Semester	1.92 (2.58)	1.94 (3.01)	1.74 (1.89)	1.97 (2.08)	0.76
…Spring 2021 Semester	10.77 (8.16)	10.35 (8.21)	10.52 (8.51)	11.51 (7.92)	0.23
…Fall 2021 Semester	10.79 (5.07)	10.25 (5.39)	11.01 (4.55)	11.50 (4.68)	0.01
…Spring 2022 Semester^¶^*	4.07 (1.61)	3.81 (1.63)	4.13 (1.68)	4.44 (1.48)	<0.001
Previous SARS-CoV-2 Infection: N (%) ^†	110 (16.7%)	77 (22.5%)	12 (13.8%)	21 (9.2%)	<0.001
SARS-CoV-2 Infections During Follow-up: N (%) ^# ^*	141 (21.4%)	96 (28.1%)	23 (26.4%)	22 (9.6%)	<0.001

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^● 2^nd dose administered within 5.25 months of study end date

^¶ During follow-up period (1/3/2022 to 1/31/2022)

^† Infection occurring prior to follow-up period (1/3/22)

^# % is proportion of individuals within each population infected with SARS-CoV-2 during follow-up period

* Variable not included in propensity score model

To evaluate vaccine effectiveness by previous infection history, an interaction term between vaccine status and previous infection was included in separate models (S1 Appendix, Models 1.3–1.4). To account for heavy censoring of event times, we apply Firth’s penalized likelihood method [31]. Waning vaccine effectiveness over time was evaluated by including time since vaccination as a predictor (S2 Appendix, Models 2.1–2.2). Time-adjusted RR of SARS-CoV-2 infection between the boosted and fully vaccinated groups were estimated via Model 2.3 (S2 Appendix). Additional model details are provided in the S1 and S2 Appendices. All analyses were conducted using R version 4.1.2.

Results

Descriptive characteristics for students and employees in the post-matching analytic sample are presented in Tables 1 and 2. This sample consists of 1,944 students who were tested for Covid-19 during the follow-up period, of which 954 did not report any vaccination (49.0%), 495 reported full vaccination (25.5%), and 495 reported receiving a booster dose (25.5%). The average age of this population was 19.64 years (SD = 1.42). The majority of the population was non-Hispanic White (81.3%), female (66.4%), lived in residential housing (50.7%), did not report any pre-existing condition (97.0%), did not use tobacco or nicotine products (98.1%), and did not have a previous SARS-CoV-2 infection (77.2%). The average number of SARS-CoV-2 tests per person since the Fall 2020 semester was 30.61 (SD = 11.96). Statistically significant differences were observed in the proportion of residential students (boosted: 48.7%, fully vaccinated: 45.7%, unvaccinated: 54.3%, P = .005) and the number of SARS-CoV-2 tests during the Spring 2022 semester (boosted: 4.24, fully vaccinated: 3.34, unvaccinated: 3.17, P < .001). However, the latter variable was not included in the propensity score models since it is strongly correlated with the outcome (due to the 90-day exemption from mandatory testing after a positive result). In total, 28.3% of individuals tested positive during the follow-up period. Positivity rates were significantly lower (P < .001) among boosted individuals (16.2%) compared to fully vaccinated (34.5%) and unvaccinated individuals (31.3%).

The post-matching analytic sample for employees consists of 658 individuals who were tested for Covid-19 during the follow-up period, of which 342 did not report any vaccination (52.0%), 87 reported full vaccination (13.2%), and 229 reported receiving a booster dose (34.8%). The average age of this population was 43.05 years (SD = 12.22). The majority of the population was non-Hispanic White (83.3%), female (64.7%), staff (86.5%), did not report any pre-existing condition (72.0%), did not use tobacco or nicotine products (97.6%), and did not have a previous SARS-CoV-2 infection (83.3%). The average number of SARS-CoV-2 tests per person since the Fall 2020 semester was 27.55 (SD = 13.43). Statistically significant differences were observed in the individuals’ age (boosted: 45.10, fully vaccinated: 42.97, unvaccinated: 41.70, P = .005), the number of individuals with a previous SARS-CoV-2 infection (boosted: 9.2%, fully vaccinated: 13.8%, unvaccinated: 22.5%, P < .001), the number of SARS-CoV-2 tests during the Fall 2021 semester (boosted: 11.50, fully vaccinated: 11.01, unvaccinated: 10.25, P = .01), and the number of SARS-CoV-2 tests during the Spring 2022 semester (boosted: 4.44, fully vaccinated: 4.13, unvaccinated: 3.81, P < .001); the latter variable was not included in the propensity score models. In total, 21.4% of individuals tested positive during the follow-up period. Positivity rates were significantly lower (P < .001) among boosted individuals (9.6%) compared to fully vaccinated (26.4%) and unvaccinated individuals (28.1%).

Characteristics of the original study populations are presented in S1 Table (students) and S2 Table (employees) and described in S3 Appendix. The matching protocol substantially improved balanced on most variables, as measured by standardized differences pre- and post-matching (S1 and S2 Figs). Using a threshold of standardized differences < 0.25 [32], balance was achieved on 100% and 95.5% of pairwise comparisons between all variables for students and employees, respectively. Using a threshold of 0.10 [28, 32], balance was achieved on 86.3% and 60.0% of pairwise comparisons. For employees, the lower proportion is due to, at least in part, the small sample size for fully vaccinated individuals [28]. Residual imbalance is adjusted for through inclusion of all confounders in the models for vaccine effectiveness [28].

Vaccine effectiveness

Estimates of vaccine effectiveness for students and employees are presented in Table 3 and Fig 2. The median time between full vaccination and end of follow-up was 4.49 months for students (range: 0.66–5.25) and 4.43 months for employees (range: 0.79–5.21). Protection (adjusted) from the 2-dose mRNA vaccination series was 7.7% among students (95% CI: -11.5–23.5%; P = .409) and 25.6% among employees (95% CI: -17.6–52.9%; P = 0.205). Differences between manufacturers were not statistically significant for students (P = .328) or employees (P = .626).

Table 3. Estimated protection from vaccination against any SARS-CoV-2 infection between January 3^rd-31^st, 2022.

Vaccination Protection	# of Individuals	# Positive (%)	Unadjusted Protection: % (95% CI)	Adjusted Protection: % (95% CI)
Students
Unvaccinated	954	299 (31.3%)	Reference	Reference
Fully Vaccinated^*^●	495	171 (34.5%)	7.6% (-11.6–23.5) ^a ^†	7.7% (-11.5–23.5) ^a
…mRNA-1273	176	53 (30.1%)	19.6% (-7.7–39.9) ^b ^†	17.3% (-10.8–38.3) ^b
…BNT162b2	319	118 (37%)	0.5% (-23.3–19.6) ^b ^†	2.1% (-21.2–21.0) ^b
Booster^*	495	80 (16.2%)	45.1% (29.7–57.1) ^a ^†	45.4% (30.0–57.4) ^a
…mRNA-1273	199	30 (15.1%)	49.2% (26.2–65.1) ^b ^†	48.5% (25.0–64.7) ^b
…BNT162b2	296	50 (16.9%)	41.7% (21.3–56.8) ^b ^†	42.8% (22.7–57.6) ^b
Employees
Unvaccinated	342	96 (28.1%)	Reference	Reference
Fully Vaccinated^*^●	87	23 (26.4%)	28.0% (-13.6–54.4) ^a ^†	25.6% (-17.6–52.9) ^a
…mRNA-1273	30	10 (33.3%)	13.1% (-66.1–54.5) ^b ^†	14.4% (-64.2–55.4) ^b
…BNT162b2	57	13 (22.8%)	34.3% (-17.0–63.1) ^b ^†	30.1% (-24.5–60.8) ^b
Booster^*	229	22 (9.6%)	67.8% (48.7–79.8) ^a ^†	66.4% (46.1–79.0) ^a
…mRNA-1273	140	16 (11.4%)	61.4% (34.4–77.3) ^b ^†	60.4% (32.4–76.8) ^b
…BNT162b2	89	6 (6.7%)	76.0% (46.4–89.3) ^b ^†	74.3% (42.1–88.6) ^b

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*Protection is relative to unvaccinated individuals

^● 2^nd dose administered within 5.25 months of study end date

^a Estimated via Model 1.1 in S1 Appendix

^b Estimated via Model 1.2 in S1 Appendix

^† Estimated via setting η ≡ 0 in Model 1.1 and 1.2 in S1 Appendix

Fig 2 — Estimates of (adjusted) vaccine protection against any SARS-CoV-2 infection caused by the omicron variant in university students (left) and employees (right).

The median time between booster dose and end of follow-up was 1.31 months for students (range: 0.39–3.51) and 2.03 months for employees (range: 0.52–4.00). Protection (adjusted) from the mRNA booster dose was 45.4% among students (95% CI = 30.0–57.4%; P < .001) and 66.4% among employees (95% CI = 46.1–79.0%; P < .001). Differences between booster manufacturers were not statistically significant for students (P = .652) or employees (P = .417). Furthermore, statistically significant differences were not observed between individuals who mixed and matched (i.e., 2-dose primary series and booster dose from different manufacturers) and those completing the 3-dose BNT16b2 sequence (students: P = .360, employees P = .985), or those completing the 3-dose mRNA-1273 sequence (students: P = .353, employees: P = .589).

Compared to completion of the 2-dose mRNA series, receipt of the mRNA booster dose increased (adjusted) protection by 37.7% among students (95% CI: 15.3–60.2%; P = .001) and 40.8% among employees (95% CI: 5.4–76.2%; P = .024). In a separate analysis accounting for time since vaccination, we directly compare (adjusted) protection among individuals receiving the mRNA booster dose to those completing the 2-dose mRNA series (S2 Appendix, Model 2.3). Relative to the 2-dose series, the (time-adjusted) risk of SARS-CoV-2 infection for those receiving the mRNA booster dose was 2.16 times lower for students (95% CI: 1.47–3.18, P < .001) and 1.52 times lower for employees (95% CI: 0.66–3.46, P = .324); however, we did not have enough evidence to conclude statistical significance for the latter effect.

We did not have evidence to conclude that mRNA vaccine protection varied by previous infection history. Significant interactions were not observed between previous SARS-CoV-2 infection and the 2-dose mRNA vaccination series (students: P = .130, employees: P = .184) or mRNA booster dose (students: P = .599, employees: P = .085). Months since completion of the 2-dose mRNA vaccination series was not a statistically significant predictor of SARS-CoV-2 infection from Omicron among students (RR = 0.93, 95% CI: 0.86–1.02; P = .110) or employees (RR = 0.99, 95% CI: 0.82–1.19; P = .549). A significant decline in mRNA booster protection was not observed among students (RR = 1.27, 95% CI: 0.81–1.98; P = .304) or employees (RR = 1.03, 95% CI: 0.65–1.65; P = .886).

Discussion

In this study setting, 21.4% of university employees and 28.3% of university students tested positive for SARS-CoV-2 during a 4-week period in which omicron was the dominant SARS-CoV-2 variant. The mRNA booster dose offered moderately high protection for employees (66.4%) and moderate protection for students (45.4%) against any SARS-CoV-2 infection caused by the omicron variant. Furthermore, estimated protection from the mRNA vaccine booster dose was approximately 40% higher for both students and employees relative to the 2-dose mRNA vaccine series.

We did not have enough evidence to conclude that the 2-dose mRNA series was protective against general SARS-CoV-2 infection from the omicron variant. Compared to our study, recent studies have found higher 2-dose and 3-dose mRNA vaccine effectiveness against symptomatic and severe SARS-CoV-2 infection from omicron [10–12]. This is to be expected, since this study evaluates protection against any SARS-CoV-2 infection from omicron (asymptomatic, pre-symptomatic, and symptomatic) as opposed to severe infection. While protection against severe SARS-CoV-2 infection is the primary objective of Covid-19 vaccination, protection against general infection is important for mitigating community transmission, since asymptomatic and pre-symptomatic individuals are substantial contributors to disease spread [33]. Therefore, less protection against general infection increases the risk for all individuals in the population. Taken together, this study and others provide evidence that booster shots are beneficial for both individual health and reduction in community transmission [34, 35].

On the surface, our findings of higher protection in older university employees relative to younger university students appear to contradict evidence that Covid-19 vaccines are (relatively) less protective in older adults [36, 37]. However, the risk of infection is dependent on the size of the infecting dose of the virus (i.e., viral load) [38–43]. Compared to the average adult, university students typically engage in more frequent and higher-density social interactions [27, 44]. Such social behavior increases exposure to higher viral loads and subsequently impacts the protective effect of vaccines.

Due to mandated weekly testing, this study design is well-suited for evaluating vaccine effectiveness against any SARS-CoV-2 infection caused by Omicron. Based on the temporal dynamics in SARS-CoV-2 viral shedding [45, 46], most cases were likely detected since the start of January. Mandatory testing also reduces the risk of confounding that may occur in clinical populations due to differences in risk-seeking behavior [47]. Relative to the general population, there is a higher degree of homogeneity in this study sample of university students and employees. This feature, combined with stratification by affiliation (student, employee), propensity score matching, and covariate adjustment based on demographics, occupation, clinical characteristics, and health-seeking behavior, further reduces the risk of confounding in this study.

Our study is subject to several limitations. First, due to low variability in month of vaccination in our study sample and a relatively short follow-up period, there was insufficient power to assess waning vaccine immunity after the 2^nd and 3^rd dose against any SARS-CoV-2 infection caused by omicron. Second, the omicron surge in South Carolina began at least one week before arrival testing was initiated [48]. While underreporting of infections prior to this period was less likely for symptomatic individuals (proof of a positive SARS-CoV-2 test provided a 90-day exemption from mandatory testing), asymptomatic individuals during this time-period were less likely to be tested and reported. Because vaccinated individuals are more likely to have mild infections relative to unvaccinated individuals, it is likely that a larger proportion of vaccine breakthrough infections were underreported during this time. While this would lead to overestimation of vaccine effectiveness, the overall impact of underreporting is expected to be low, since only a small fraction of Omicron infections in South Carolina are estimated to have occurred prior to 2022 [48].

Third, misclassification of vaccination status may attenuate estimates of vaccine effectiveness towards the null [17]. Financial incentives offered during the Fall 2021 semester for voluntary vaccination upload likely minimized underreporting of the 2-dose mRNA series. Therefore, unvaccinated individuals are unlikely to be misclassified since the analytic population was restricted to those affiliated with the university during Fall 2021. However, booster doses became widely available after the financial incentive program was announced. It is therefore possible that booster doses are underreported among fully vaccinated individuals (i.e., recipients of the 2-dose mRNA series) who are booster eligible. Underreporting of boosters in this situation would lead to overestimation of 2-dose mRNA vaccine effectiveness among individuals who received their 2^nd dose more than 5 months prior to the end of study follow-up (i.e., booster-eligible individuals). For this reason, we excluded this population from analysis.

This study evaluated vaccines effectiveness in relatively healthy university populations. Due to our exclusion criteria and matching protocol, the resulting analytic sample for students tended to be both healthier and have greater health-seeking behavior. On the other hand, university students typically have a higher number of social contacts relative to other young adult populations. Hence, this population is more susceptible to contracting SARS-CoV-2 and may be subjected to higher viral loads. Caution must therefore be taken when extrapolating estimates of vaccine effectiveness beyond the analytic population in this study.

Conclusions

Among adults 18–65 years of age, messenger RNA (mRNA) booster doses offer moderate protection against general SARS-CoV-2 infection caused by the omicron variant. In both university students and employees, receipt of the mRNA booster dose substantially increased protection relative to the 2-dose mRNA vacccination series. The effectiveness of mRNA boosters on both individual health and reduction in community transmission support continued efforts for Covid-19 booster doses. This is especially important in the young-adult population, which has suboptimal vaccine uptake yet is a major contributor to community spread. However, given that approximately one-third to one-half of the study population remains susceptible to breakthrough infection, certain precautions after vaccination may still be warranted.

Supporting information

S1 Appendix. Statistical models for vaccine protection (Table 3).

(DOCX)

Click here for additional data file.^{(19.3KB, docx)}

S2 Appendix. Statistical models for waning vaccine protection.

(DOCX)

Click here for additional data file.^{(17.9KB, docx)}

S3 Appendix. Study sample description.

(DOCX)

Click here for additional data file.^{(15.7KB, docx)}

S1 Table. Characteristics of student study population (prior to matching).

(DOCX)

Click here for additional data file.^{(30.6KB, docx)}

S2 Table. Characteristics of employee study population (prior to matching).

(DOCX)

Click here for additional data file.^{(22.4KB, docx)}

S1 Fig. Absolute standardized mean difference between vaccination groups among students.

Absolute standardized mean difference between unvaccinated versus booster (left) and unvaccinated versus fully vaccinated (right) for baseline covariates before and after propensity score matching among students. Vertical lines represent the thresholds of 0.1 and 0.25.

(TIF)

Click here for additional data file.^{(424.2KB, tif)}

S2 Fig. Absolute standardized mean difference between vaccination groups among employees.

Absolute standardized mean difference between unvaccinated versus booster (left) and unvaccinated versus fully vaccinated (right) for baseline covariates before and after propensity score matching among employees. Vertical lines represent the thresholds of 0.1 and 0.25.

(TIF)

Click here for additional data file.^{(383.3KB, tif)}

S3 Fig. Histogram of propensity scores of the unmatched sample and the matched sample for students.

The common reference group (boosted) is represented in red, the unvaccinated group is represented in grey, and the fully vaccinated group is represented in green, respectively.

(TIF)

Click here for additional data file.^{(312.2KB, tif)}

S4 Fig. Histogram of propensity scores of the unmatched sample and the matched sample for employees.

The common reference group (fully vaccinated) is represented in green, the unvaccinated group is represented in grey, and the boosted group is represented in red, respectively.

(TIF)

Click here for additional data file.^{(332KB, tif)}

S5 Fig. Distribution of receipt of the 2nd dose and the booster dose by calendar month for university students and employees in the matched sample.

(TIF)

Click here for additional data file.^{(246.5KB, tif)}

S1 Checklist. STROBE checklist for cohort studies.

(DOCX)

Click here for additional data file.^{(22KB, docx)}

Acknowledgments

We thank the Clemson University administration, medical staff, and all other testing providers who helped implement and manage SARS-CoV-2 testing at Clemson University. We thank Clemson’s Computing & Information Technology department for their role in collecting, managing, and distributing test results.

Data Availability

The raw data are protected and are not available due to data privacy laws. Covid-19 data used in this study can be requested at the following link: https://www.clemson.edu/covid-19/testing/research-data.html.

Funding Statement

LR and DD acknowledge support from US National Institutes of Health (P20 GM121342) during conduct of this study. DD acknowledges support from the State of South Carolina (CARES act) for building of the on-campus Covid-19 testing lab and support from US National institutes of Health (R01 MH111366) during conduct of this study. LR, ZM, and CM acknowledge salary support from Clemson University for consulting and modelling work pertaining to development and evaluation of public health strategies (project #1502934). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0001111.r001

Decision Letter 0

Patrick DMC Katoto

4 Aug 2022

PGPH-D-22-00917

Covid-19 vaccine effectiveness against general SARS-CoV-2 infection from the omicron variant: A retrospective cohort study

PLOS Global Public Health

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I don't know

Reviewer #2: No

**********

3. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS Global Public Health does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I did not find it easy to understand the model chosen to select or exclude participants.

I also fail to understand how in a follow-up period between 3 and 31 January 2022, it has between 27 to 30 tests performed, from which I assume that the follow-up was longer but it is not clear from the text.

I also find remarkable the low number of tobacco users, about 2%, which makes me doubt the demographic data (maybe it is a real data, if so, I think it is fantastic).

only polymerase chain reaction was used for diagnosis? at the time of the study there were many antigen self-tests available which may have also altered the possible interpetation of results. This is not mentioned on the text

Another point that seems to me of utmost importance and that is mentioned in the discussion is the reporting error that may exist in those who did receive a booster, since there is no economic incentive, so many participants could have had a booster and not be reported, which alters the interpretation of the data.

Reviewer #2: Abstract

SARS-CoV-2? Write in full then after abbreviate.

COVID-19? Write in full then after abbreviate.

“Unvaccinated” should be written “unvaccinated”

within “the” previous 5 months

Intervention should be well described, what were the BNT162b2 or mRNA-1273 vaccine doses?

Results: How many university students and employees did you include in your results? sex and age distribution should be included.

The result is poorly reported. Please include the BNT162b2 and mRNA-1273 vaccine effectiveness in the result.

Conclusion: your conclusion should be based on the study population. What are your recommendation based on your results?

Introduction

Syndrom should be written “syndrome”

Omicron has caused “a” record number of daily….

The epidemiology of COVID-19 in the US is poorly described.

Please briefly review the vaccine effectiveness of Wuhan, beta, and delta variants in the US. Compared this with recent studies conducted about Omicron variant.

Please state clearly the objective of this study and how this study can be considered as particular compared to other studies conducted in the US about Omicron variant.

we assess “the” effectiveness of the 2-dose and 3-dose messenger RNA (mRNA) vaccination

“Adminstration” should be written “administration”

Methods

The method should include a list of all sociodemographic and covariate variables used in the results.

“Time-varying Cox proportional hazard models were used to estimate the relative risk (RR)”, this use to estimate the hazard risk rate.

I would like you to compute non adjusted and adjusted RR to estimate the vaccine effectiveness.

As the p-value and the 95%CI are included in the results, this should be well stated in the statistical analysis.

Kind state in the methods that 1-aRR was used to compute the vaccine effectiveness.

Be consistent between COVID-19 and Covid-19 throughout the study.

I do not see anything about data collection and management. Please specify.

Results

As stated in the abstract, the socio-demographic characteristics should be included in your results.

Age should be classified because the Anova of unvaccinated, fully vaccinated, and booster was statistically significant. It will also be interesting to see how vaccine effectiveness varies by age distribution in this population.

As stated in the methodology, adjusted RR should be used.

Discussion

The discussion should be strengthened. How do you compare this study results to other studies related to Omicron vaccine effectiveness?

Authors just state the study limitations. Where are the study strengths?

Clearly state how misclassification of vaccination status may bias estimates of vaccine effectiveness.

Conclusion

The study recommendation for this specific population should be clearly stated.

References

Pubmed should be used for referencing. Many of the references are incorrect.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Jacques L Tamuzi

**********

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PLOS Glob Public Health. 2023 Jan 10;3(1):e0001111. doi: 10.1371/journal.pgph.0001111.r002

Author response to Decision Letter 0

19 Sep 2022

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0001111.r003

Decision Letter 1

Patrick DMC Katoto

8 Nov 2022

PGPH-D-22-00917R1

Covid-19 vaccine effectiveness against general SARS-CoV-2 infection from the omicron variant: A retrospective cohort study

PLOS Global Public Health

Dear Dr. Rennert,

Thank you for submitting your manuscript to PLOS Global Public Health. Your work has received thorough consideration from our reviewers and may be published subject to the satisfaction of the minor suggestions attached. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 08 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at globalpubhealth@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pgph/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Prof Patrick DMC Katoto, MD, MSC, PhD

Academic Editor

PLOS Global Public Health

Journal Requirements:

1. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I don't know

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: No

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: dont use Spring or fall "...in a large public university student and employee population undergoing mandatory

weekly testing during the Spring 2022 semester"

do not use spring or autumn as a measure of a time period. It is only used in the northern hemisphere and is confusing for those who do not live in that hemisphere. Use the months of the year, which are the same for everyone.

it is possible to understand, but difficult to do so, the criteria of inclusion and exclusion of the participants, I suggest to improve the wording.

How can it be explained that unvaccinated individuals had fewer infections than those vaccinated with two doses? "Compared to fully vaccinated (34.5%) and unvaccinated individuals (31.3%)".

it would be interesting to know which omicron subvariant was circulating at that date in that place.

Reviewer #2: The authors have worked hard to improve the manuscript. The majority of my previous comments have been well addressed. However, the discussion remains poorly described. How do you discuss the statistically significant P-values in table 1A? 1B? and the comparison between students and employees in this study, which was conducted in a university setting? Please make this clear in the discussion.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Jacques L. Tamuzi

**********

PLOS Glob Public Health. 2023 Jan 10;3(1):e0001111. doi: 10.1371/journal.pgph.0001111.r004

Author response to Decision Letter 1

7 Dec 2022

Attachment

Submitted filename: Response to Reviewers.docx

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0001111.r005

Decision Letter 2

Patrick DMC Katoto

13 Dec 2022

Covid-19 vaccine effectiveness against general SARS-CoV-2 infection from the omicron variant: A retrospective cohort study

PGPH-D-22-00917R2

Dear Professor Lior Rennert,

We are pleased to inform you that your manuscript 'Covid-19 vaccine effectiveness against general SARS-CoV-2 infection from the omicron variant: A retrospective cohort study' has been provisionally accepted for publication in PLOS Global Public Health.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they'll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact globalpubhealth@plos.org.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Global Public Health.

Best regards,

Prof. Patrick DMC Katoto, MD, MSC, PhD

Academic Editor

PLOS Global Public Health

***********************************************************

Reviewer Comments (if any, and for reference):

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Appendix. Statistical models for vaccine protection (Table 3).

(DOCX)

Click here for additional data file.^{(19.3KB, docx)}

S2 Appendix. Statistical models for waning vaccine protection.

(DOCX)

Click here for additional data file.^{(17.9KB, docx)}

S3 Appendix. Study sample description.

(DOCX)

Click here for additional data file.^{(15.7KB, docx)}

S1 Table. Characteristics of student study population (prior to matching).

(DOCX)

Click here for additional data file.^{(30.6KB, docx)}

S2 Table. Characteristics of employee study population (prior to matching).

(DOCX)

Click here for additional data file.^{(22.4KB, docx)}

S1 Fig. Absolute standardized mean difference between vaccination groups among students.

(TIF)

Click here for additional data file.^{(424.2KB, tif)}

S2 Fig. Absolute standardized mean difference between vaccination groups among employees.

Absolute standardized mean difference between unvaccinated versus booster (left) and unvaccinated versus fully vaccinated (right) for baseline covariates before and after propensity score matching among employees. Vertical lines represent the thresholds of 0.1 and 0.25.

(TIF)

Click here for additional data file.^{(383.3KB, tif)}

S3 Fig. Histogram of propensity scores of the unmatched sample and the matched sample for students.

The common reference group (boosted) is represented in red, the unvaccinated group is represented in grey, and the fully vaccinated group is represented in green, respectively.

(TIF)

Click here for additional data file.^{(312.2KB, tif)}

S4 Fig. Histogram of propensity scores of the unmatched sample and the matched sample for employees.

The common reference group (fully vaccinated) is represented in green, the unvaccinated group is represented in grey, and the boosted group is represented in red, respectively.

(TIF)

Click here for additional data file.^{(332KB, tif)}

S5 Fig. Distribution of receipt of the 2nd dose and the booster dose by calendar month for university students and employees in the matched sample.

(TIF)

Click here for additional data file.^{(246.5KB, tif)}

S1 Checklist. STROBE checklist for cohort studies.

(DOCX)

Click here for additional data file.^{(22KB, docx)}

Attachment

Submitted filename: Response to Reviewers.docx

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Submitted filename: Response to Reviewers.docx

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Data Availability Statement

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PERMALINK

Covid-19 vaccine effectiveness against general SARS-CoV-2 infection from the omicron variant: A retrospective cohort study

Lior Rennert

Zichen Ma

Christopher S McMahan

Delphine Dean

Roles

Abstract

Introduction

Methods

Study design and population

Fig 1. Flowchart of sample selection process for students and employees in main analysis during follow-up period between January 3rd, 2022 and January 31st, 2022.

Ethics statement

Vaccination status

SARS-CoV-2 testing

Data collection and management

Propensity score matching

Statistical analyses

Table 1. Descriptive characteristics for students in the analytic sample after propensity score matching.

Table 2. Descriptive characteristics for employees in the analytic sample after propensity score matching.

Results

Vaccine effectiveness

Table 3. Estimated protection from vaccination against any SARS-CoV-2 infection between January 3rd-31st, 2022.

Fig 2.

Discussion

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Patrick DMC Katoto

Roles

Author response to Decision Letter 0

Decision Letter 1

Patrick DMC Katoto

Roles

Author response to Decision Letter 1

Decision Letter 2

Patrick DMC Katoto

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Links to NCBI Databases

Fig 1. Flowchart of sample selection process for students and employees in main analysis during follow-up period between January 3^rd, 2022 and January 31^st, 2022.

Table 3. Estimated protection from vaccination against any SARS-CoV-2 infection between January 3^rd-31^st, 2022.