### ORIGINAL RESEARCH ![](https://assets.reachrx.ai/images/10.1007%E2%98%8Ds40121-025-01292-2/_page_0_Picture_2.jpeg) # **Evaluating the Effectiveness of 2024–2025 Seasonal mRNA‑1273 Vaccination Against COVID‑19‑Related Hospitalizations and Medically Attended COVID‑19 Among Adults Aged ≥ 18 years in the United States: An Observational Matched Cohort Study** Nevena Vicic · Alina Bogdanov · Zhe Zheng · Taylor Ryan · Ni Zeng · Keya Joshi · Tianyi Lu · Machaon Bonafede · Andre B. Araujo · Amanda Wilson Received: September 30, 2025 / Accepted: December 12, 2025 © The Author(s) 2026 ## ABSTRACT *Introduction***:** This study evaluated the effectiveness of Moderna's updated mRNA-1273 vaccine targeting the KP.2 variant, compared to people who did not receive any 2024–2025 COVID-19 vaccine, in preventing COVID-19-associated hospitalizations and medically-attended COVID-19 among adults aged ≥ 18 years in the United States during the 2024–2025 season. *Methods***:** Data were extracted from linked administrative healthcare claims and electronic health records (EHR) for vaccinations from 23 August 2024 through 23 April 2025 and followed through 30 April 2025. We conducted a retrospective matched cohort study with propensity score weighting to adjust for differences between groups to assess vaccine effectiveness **Prior Presentation**: This study has been presented at IDWeek 2025; October 19–22, 2025; Atlanta, Georgia, USA; P-1592. **Supplementary Information** The online version contains supplementary material available at [https://doi.org/10.1007/s40121-025-01292-2.](https://doi.org/10.1007/s40121-025-01292-2) N. Vicic (\*) · Z. Zheng · K. Joshi · T. Lu · A. B. Araujo · A. Wilson Moderna, Inc., Cambridge, MA, USA e-mail: nvicic@modernatx.com A. Bogdanov · T. Ryan · N. Zeng · M. Bonafede Real World Evidence, Veradigm, Chicago, IL, USA (VE) against COVID-19 outcomes. VE was calculated as 1 minus the hazard ratio (HR) from Cox proportional hazards models. *Results***:** Overall, 596,248 mRNA-1273 KP.2 vaccine recipients were matched 1:1 to unexposed adults. The mean (standard deviation) age was 63 (17) years, with more than half of the population being 65 years or older. Approximately 70% of individuals had an underlying medical condition making them high-risk for severe outcomes for COVID-19. VE was 52.8% [95% confdence interval (CI) 34.8%, 65.8%] against COVID-19-related hospitalization and 39.4% (35.0%, 43.5%) against medically-attended COVID-19 over a median follow-up of 55 (interquartile range 32–77) days in an interim analysis. The VE was sustained throughout the entire study period and shown to be 45.2% (37.7%, 51.8%) against COVID-19-related hospitalizations and 33.1% (30.6–35.4%) against medically-attended COVID-19 over a median follow-up of 127 (interquartile range 84–173) days. *Conclusion***:** The mRNA-1273 KP.2 vaccine demonstrated signifcant incremental effectiveness in preventing hospitalization with COVID-19 and medically-attended COVID-19 in adults during the 2024–2025 season to date. The VE was sustained with longer median follow up time. These fndings support ongoing vaccination efforts to mitigate the public health impact of COVID-19. **Keywords:** COVID-19 vaccine; Hospitalization; Medically attended COVID-19; Vaccine effectiveness; mRNA-1273 KP.2 ### **Key Summary Points** ### *Why carry out this study?* COVID-19 still has a major impact on public health, especially for older adults and people with existing health conditions. It is critical to continue studying how well updated COVID-19 vaccines protect against serious illness. This study looked at how effective the mRNA-1273 KP.2 vaccine was at preventing serious COVID-19 disease in adults. ### *What was learned fom the study?* During the 2024–2025 season, the mRNA-1273 KP.2 vaccine provided added protection against hospitalizations and medicallyattended COVID-19, and this protection was sustained over time. These results support continuing annual COVID-19 vaccination efforts, particularly for older adults and people at higher risk. ## INTRODUCTION The COVID-19 pandemic has posed unprecedented challenges to global health, necessitating the development and deployment of vaccines to mitigate the public health impact of COVID-19. The initial vaccines demonstrated high effcacy in clinical trials [\[1](#page-11-0), [2\]](#page-11-1); however, the emergence of variants of concern (VOCs) and increasing immunity in the population due to prior infection and vaccination have raised questions about vaccine effectiveness (VE) over time, as well as the need for vaccination targeting new VOCs. Notably, the Omicron variant and its sublineages have exhibited increased transmissibility and partial resistance to neutralization by antibodies elicited by prior infection or vaccination with the ancestral strain [\[3](#page-11-2)[–5\]](#page-12-0). To address the evolving threat posed by SARS-CoV-2 variants, vaccine manufacturers have updated their formulations. The JN.1 family lineage emerged from BA.2.86 in late 2023 which necessitated an update from the XBB.1.5 formulation that was available beginning in August 2023. The updated vaccine aimed to enhance protection against currently circulating variants, thereby reducing COVID-19-related hospitalizations and medically-attended cases. The mRNA-1273 KP.2 vaccine, developed by Moderna and available in the United States as of 23 August 2024, was designed to target the Omicron KP.2 sublineage [\[6\]](#page-12-1). While this formulation is anticipated to cross-neutralize against JN.1 family members, there is limited evidence of clinical protection to confrm this, driving the need for real-world evidence (RWE) [\[7\]](#page-12-2). Despite widespread immunity from prior vaccination and infection, the burden of COVID-19 remains substantial, particularly among older adults and individuals with underlying medical conditions [[8\]](#page-12-3). Adults aged ≥ 65 years continue to account for the majority of COVID-19-associated hospitalizations. COVID-19 continues to pose signifcant risk to adults with underlying medical conditions, including chronic obstructive pulmonary disease, diabetes mellitus, heart conditions, and obesity, and among hospitalized adults in the United States, those with at least one underlying condition experienced higher risks of ICU admission and death compared with those without such conditions [[8–](#page-12-3)[11](#page-12-4)]. RWE is crucial for assessing the effectiveness of updated vaccines across diverse populations and settings. Observational studies leveraging electronic health records (EHR) and claims data provide valuable insights into VE against severe outcomes, such as hospitalizations [[12,](#page-12-5) [13\]](#page-12-6). Previous RWE studies have demonstrated that updated mRNA vaccines in prior seasons offered substantial protection against severe disease caused by emerging variants [\[14\]](#page-12-7). This study aims to evaluate the effectiveness of the mRNA-1273 KP.2 vaccine in preventing COVID-19-associated hospitalizations and medically-attended COVID-19 among adults aged ≥ 18 years in the United States during the 2024–2025 season. ## METHODS #### **Data Source** This study leveraged EHR data from the Veradigm Network EHR linked to administrative healthcare claims sourced from Komodo Health. The EHR data are sourced from ambulatory/outpatient primary care and specialty settings, and the claims data include inpatient, outpatient, and pharmacy sources. This integrated dataset has been previously characterized and used in COVID-19 epidemiology and VE research [\[15–](#page-12-8)[18](#page-12-9)]. ### **Ethical Approval** This study was conducted in accordance with the Declaration of Helsinki and relevant guidelines for observational studies. The research involved de-identifed data and did not require direct patient involvement. Therefore, specifc ethics approval and informed consent were not needed, as the data were anonymized and complied with patient privacy regulations. Access to the data was provided under agreements with the data provider, which ensured adherence to ethical standards, including the protection of patient confdentiality. #### **Participants and Study Design** This was an observational, matched cohort study of adults in the US who were vaccinated from 23 August 2024 through 23 April 2025 (intake period) and followed through 30 April 2025 in the fnal analysis. In the interim analysis, the intake period ended 24 December 2024 and patients were followed through 31 December 2024. Patients vaccinated with mRNA-1273 2024–25 formulation targeting the KP.2 variant (exposed) were 1:1 matched to those without evidence of receiving a 2024–2025 COVID-19 vaccine (unexposed) on the eligible index date. The index date was defned as the date of mRNA-1273 KP.2 vaccination among the exposed and the matched date among the unexposed. To allow for establishment of vaccine-induced immunity, the cohort entry date (CED) was defned as 7 days following the index date. The pre-index period started 12 September 2023, the date the prior season's mRNA1273 vaccine became available + 1 day. Individuals were eligible for inclusion in the study if they were ≥ 18 years at the start of the intake period and had continuous medical and pharmacy enrollment (with 45-day allowable gaps) from the start of the pre-index period through CED, regardless of prior vaccination history. Patients were excluded if they had missing or conficting age, sex, or state of residence, evidence of a COVID-19 diagnosis or COVID-19 treatment 90 days prior to index date through CED, evidence of vaccination with any seasonal updated 2024–2025 COVID-19 vaccine from 60 days prior to index date through the end of the intake period (excluding index date, where by definition exposed patients received mRNA-1273 KP.2), receipt of any other COVID-19 vaccine from 60 days prior to index date through CED, or had < 1 day of follow-up. Subpopulations of interest were identified as 65 years and older (at start of intake), and individuals 18–64 years with underlying medical conditions associated with increased risk of severe COVID-19 outcomes, as defned by the Centers for Disease Control and Prevention, combined with those 65 and older [[14](#page-12-7)]. These conditions included asthma, cancer, cerebrovascular disease, chronic kidney disease, chronic liver disease, chronic lung disease, cystic fbrosis, dementia, diabetes mellitus, disability, heart conditions, HIV, mental health conditions, obesity (body mass index > 30), physical inactivity, pregnancy, primary immunodefciencies, respiratory tuberculosis, smoking, and solid organ or stem cell transplant, and use of select immunosuppressive medications. #### **Outcomes** The primary outcome of COVID-19 hospitalization was defned as a hospitalization claim with a COVID-19 International Classifcation of Diseases (ICD)-10 diagnosis code (U07.1 or J12.82) in any position. The secondary outcome of medically-attended COVID-19 was defned as at least one claim or record with a COVID-19 ICD-10 diagnosis code (U07.1 or J12.82) or related Systematized Nomenclature of Medicine code in any position or setting (including hospital admissions as in the primary outcome, as well as emergency department visits, urgent care visits, offce visits, telemedicine visits, and laboratory results). Follow-up time for the assessment of the outcomes started on CED. Patients were followed until the frst occurrence of the outcome, or other censoring criteria (health plan disenrollment, vaccination with any COVID-19 vaccine during follow-up, or end of study) (Supplemental Fig. [1\)](#page-8-0). #### **Covariates** Covariates included demographic variables (age, sex, race, ethnicity, geographic region), comorbidities (e.g., diabetes, cardiovascular disease), and healthcare utilization patterns. The frequency and distribution of covariates were assessed at relevant time points prior to and/or including the index date and described between exposed and unexposed patients. Presence of high-risk and immunocompromising conditions were assessed in the pre-index period from up to 365 days prior to the index date, up through the index date (inclusive). Healthcare resource utilization was assessed from up to 365 days prior to the index date, up to 1 day before the index date. Infuenza history and infuenza vaccination history was assessed from the start of the pre-index period up to 1 day before the index date. COVID-19 vaccination history was assessed from the start of the pre-index period up to 60 days prior to the index date, and COVID-19 history from the start of the pre-index period up to 90 days prior to the index date. Demographic variables were assessed on the start of the intake period. #### **Statistical Analysis** Unexposed individuals were 1:1 matched to the exposed based on age, sex, race, ethnicity, geographic region, week of last healthcare activity before start of intake period, evidence of vaccination with a prior season's vaccine during the pre-index period, and the calendar date of the index date in the exposed. Matching procedures and statistical analyses were conducted for the overall cohort and subgroup analyses stratifed by age or occurrence of a high-risk condition used this matched cohort. Note that occurrence of a high-risk condition was not a criterion for matching, so in sub-populations based on high-risk status the numbers of exposed and unexposed patients are not equal. To account for potential differences in measured baseline confounders even after matching, logistic regression models were used to calculate propensity scores (based on the matched variables, as well as insurance type, index months, comorbidities, time since last COVID-19 vaccination and infection, evidence of infuenza vaccination, diagnosis of infuenza, number of hospitalizations, and number of outpatient visits as described previously) and corresponding inverse probability of treatment weights (IPTWs). Stabilized IPTWs were calculated as the probability of being exposed to mRNA-1273 KP.2 by the propensity score (PS) for the exposed group and as the probability of being unexposed divided by (1−PS) among the unexposed group. Sample balance before and after IPTW was assessed by calculation of the standardized mean differences (SMD). SMDs with absolute values > 0.1 indicated covariate imbalance. Following IPTW, no covariates had remaining imbalance. Covariates were reported descriptively before and after weighting with means and standard deviations for continuous variables and number and percent for categorical variables. Incidence rates and unadjusted HRs were reported for the unweighted sample, and adjusted HRs were reported for the weighted sample. Unadjusted HRs were calculated using a Cox regression model with mRNA-1273 KP.2 vaccine as the only predictor. Adjusted HRs were calculated for the weighted sample using a weighted Cox regression model that included mRNA-1273 KP.2 vaccination status and any covariates with an SMD greater than 0.1 after IPTW. Cumulative incidence plots with 95% confidence intervals (CIs) were generated to visually assess the vaccine effectiveness changes over time to assess the proportional hazards assumption. Subsequently, the unadjusted and adjusted VE for each outcome were calculated as (1 − HR) × 100% and reported with 95% CIs. Data cleaning and analytic fle generation was conducted via SQL. Statistical analyses were conducted using SAS V9.4. ## RESULTS In the fnal analysis, 596,248 mRNA-1273 KP.2 recipients were matched 1:1 to unexposed adults (Supplemental Fig. [2\)](#page-8-1); 63% of the 18–64 population had a high-risk condition and 61.4% of the total study population was ≥ 65. The 18–64 with a high-risk condition and patients ≥ 65 combined represented 72% of the full study population and included 429,228 exposed adults and 435,448 unexposed. The exposed and unexposed cohorts were well balanced after weighting, with no standardized mean differences (SMDs) greater than 0.1. In the interim analysis 465,073 mRNA-1273 KP.2 recipients were matched 1:1 to unexposed adults and the overall median (interquartile range) follow-up time was 55 (32–77) days. Demographic and clinical characteristics were similar in the interim analysis and were also well balanced after weighting (Supplemental Table [1a](#page-5-0)). In the fnal analysis of the entire study population, the mean (standard deviation) age in both exposed and unexposed cohorts was 63 (17) years; 58.1% were female. Most patients (over 70%) in the overall population had documentation of the previous season's vaccination for COVID-19 during the pre-index period. Over 88% had their most recent documented activity with the healthcare system within 4 weeks prior to the index date. Most vaccinations during the study period occurred during September (33.9%) or October (36.8%). The most common underlying medical conditions pre-weighting were obesity (26.3% in the exposed and 27.2% in the unexposed), diabetes mellitus (23.1% in the exposed and 24.8% in the unexposed), and heart conditions (18.9% in the exposed and 20.5% in the unexposed). See Table [1](#page-5-0). Baseline characteristics of all subpopulations of interest for the interim and fnal analysis can be found in the supplemental (Supplemental Table [1a](#page-5-0)–c). The overall median (interquartile range) follow-up time for the fnal analysis was 127 (84–173) days. A total of 347 COVID-19-related hospitalizations and 5085 COVID-19-related medical encounters were identifed pre-weighing in the exposed, and 678 and 7501 in the unexposed, respectively. The incidence of COVID-19-related hospitalizations was 0.06% in the exposed cohort and 0.11% in the unexposed cohort over the entire follow-up period. The incidence of medically-attended COVID-19 was 0.86% in the exposed cohort and 1.26% in the unexposed cohort over the follow-up period. Cumulative incidence curves for hospitalizations and medically-attended COVID-19 of the entire study population are presented in Fig. [1.](#page-8-0) Cumulative incidence curves for hospitalization and medically-attended COVID-19 for all subpopulations of interest for the interim and fnal analysis can be found in Supplemental Fig. 3a–c. Table 1 Baseline characteristics (pre-weighting and post-weighting, and SMDs) of the study population (≥ 18 years of age), fnal analysis | | Pre-weighting | | | Post-weighting | | | |-----------------------|----------------|----------------|--------|----------------|----------------|--------| | | Exposed | Unexposed | SMD | Exposed | Unexposed | SMD | | Number of patients | 596,248 | 596,248 | | 593,984 | 595,079 | | | Age; mean (SD) | 63 (17.1) | 63 (17.1) | 0.0000 | 63 (17.0) | 63 (17.0) | 0.0002 | | Age categories; n (%) | | | 0.0000 | | | 0.0015 | | 18–24 | 15,285 (2.6) | 15,285 (2.6) | | 15,074 (2.5) | 15,101 (2.5) | | | 25–29 | 14,742 (2.5) | 14,742 (2.5) | | 14,544 (2.4) | 14,569 (2.4) | | | 30–34 | 20,894 (3.5) | 20,894 (3.5) | | 20,628 (3.5) | 20,691 (3.5) | | | 35–39 | 24,530 (4.1) | 24,530 (4.1) | | 24,262 (4.1) | 24,306 (4.1) | | | 40–44 | 25,924 (4.3) | 25,924 (4.3) | | 25,728 (4.3) | 25,752 (4.3) | | | 45–49 | 25,973 (4.4) | 25,973 (4.4) | | 25,774 (4.3) | 25,794 (4.3) | | | 50–54 | 32,094 (5.4) | 32,094 (5.4) | | 31,897 (5.4) | 31,897 (5.4) | | | 55–59 | 42,999 (7.2) | 42,999 (7.2) | | 42,794 (7.2) | 42,815 (7.2) | | | 60–64 | 65,397 (11.0) | 65,397 (11.0) | | 65,172 (11.0) | 65,243 (11.0) | | | 65–69 | 68,623 (11.5) | 68,623 (11.5) | | 68,438 (11.5) | 68,597 (11.5) | | | 70–74 | 87,240 (14.6) | 87,240 (14.6) | | 87,045 (14.7) | 87,285 (14.7) | | | 75–79 | 77,138 (12.9) | 77,138 (12.9) | | 77,065 (13.0) | 77,273 (13.0) | | | 80–84 | 50,855 (8.5) | 50,855 (8.5) | | 50,887 (8.6) | 51,003 (8.6) | | | 85–89 | 44,554 (7.5) | 44,554 (7.5) | | 44,675 (7.5) | 44,752 (7.5) | | | Sex; n (%) | | | 0.0000 | | | 0.0002 | | Female | 346,713 (58.1) | 346,713 (58.1) | | 345,272 (58.1) | 345,964 (58.1) | | | Male | 249,535 (41.9) | 249,535 (41.9) | | 248,712 (41.9) | 249,115 (41.9) | | | Race; n (%) | | | 0.0000 | | | 0.0006 | | Black | 34,036 (5.7) | 34,036 (5.7) | | 33,911 (5.7) | 33,922 (5.7) | | | Other | 86,782 (14.6) | 86,782 (14.6) | | 86,532 (14.6) | 86,663 (14.6) | | | White | 360,963 (60.5) | 360,963 (60.5) | | 359,817 (60.6) | 360,538 (60.6) | | | Unknown | 114,467 (19.2) | 114,467 (19.2) | | 113,724 (19.1) | 113,956 (19.1) | | | Ethnicity; n (%) | | | 0.0000 | | | 0.0000 | | Hispanic | 11,208 (1.9) | 11,208 (1.9) | | 11,180 (1.9) | 11,176 (1.9) | | | Non-Hispanic | 357,416 (59.9) | 357,416 (59.9) | | 356,158 (60.0) | 356,817 (60.0) | | | Unknown | 227,624 (38.2) | 227,624 (38.2) | | 226,646 (38.2) | 227,087 (38.2) | | | Insurance type; n (%) | | | 0.1034 | | | 0.0047 | Table 1 continued | | Pre-weighting | | | Post-weighting | | | |------------------------------------------|----------------|----------------|--------|----------------|----------------|--------| | | Exposed | Unexposed | SMD | Exposed | Unexposed | SMD | | Commercial | 249,196 (41.8) | 237,578 (39.8) | | 242,037 (40.7) | 241,950 (40.7) | | | Medicaid | 29,379 (4.9) | 42,515 (7.1) | | 35,084 (5.9) | 35,643 (6.0) | | | Medicare advantage | 279,031 (46.8) | 272,806 (45.8) | | 276,003 (46.5) | 276,419 (46.5) | | | Medicare FFS | 36,647 (6.1) | 40,167 (6.7) | | 38,343 (6.5) | 38,487 (6.5) | | | Unknown | 1995 (0.3) | 3182 (0.5) | | 2516 (0.4) | 2579 (0.4) | | | Region; n (%) | | | 0.0000 | | | 0.0009 | | Midwest | 121,857 (20.4) | 121,857 (20.4) | | 121,451 (20.4) | 121,542 (20.4) | | | Northeast | 194,347 (32.6) | 194,347 (32.6) | | 193,522 (32.6) | 193,904 (32.6) | | | South | 146,125 (24.5) | 146,125 (24.5) | | 145,652 (24.5) | 145,915 (24.5) | | | West | 133,913 (22.5) | 133,913 (22.5) | | 133,354 (22.5) | 133,713 (22.5) | | | Unknown | 6 (0.0) | 6 (0.0) | | 5 (0.0) | 5 (0.0) | | | Month of index date; n (%) | | | 0.0000 | | | 0.0190 | | 2024–08 | 17,514 (2.9) | 17,514 (2.9) | | 18,060 (3.0) | 17,226 (2.9) | | | 2024–09 | 201,943 (33.9) | 201,943 (33.9) | | 203,881 (34.3) | 200,118 (33.6) | | | 2024–10 | 219,254 (36.8) | 219,254 (36.8) | | 216,645 (36.5) | 218,673 (36.7) | | | 2024–11 | 96,130 (16.1) | 96,130 (16.1) | | 94,637 (15.9) | 96,852 (16.3) | | | 2024–12 | 37,480 (6.3) | 37,480 (6.3) | | 37,053 (6.2) | 37,926 (6.4) | | | 2025–1 | 15,471 (2.6) | 15,471 (2.6) | | 15,341 (2.6) | 15,640 (2.6) | | | 2025–2 | 5597 (0.9) | 5597 (0.9) | | 5591 (0.9) | 5678 (1.0) | | | 2025–3 | 2246 (0.4) | 2246 (0.4) | | 2178 (0.4) | 2326 (0.4) | | | 2025–4 | 613 (0.1) | 613 (0.1) | | 598 (0.1) | 640 (0.1) | | | Number of OP visits; mean (SD) | 2 (6.0) | 3 (6.6) | 0.0384 | 2 (6.4) | 2 (6.2) | 0.0015 | | Number of hospitalizations; mean
(SD) | 0.1 (0.4) | 0.1 (0.5) | 0.0689 | 0.1 (0.5) | 0.1 (0.5) | 0.0043 | | Baseline clinical comorbidities; n (%) | | | | | | | | Cancer | 62,992 (10.6) | 63,414 (10.6) | 0.0023 | 63,103 (10.6) | 63,277 (10.6) | 0.0003 | | Cerebrovascular disease | 45,508 (7.6) | 51,927 (8.7) | 0.0393 | 48,578 (8.2) | 48,863 (8.2) | 0.0012 | | Chronic kidney disease | 78,360 (13.1) | 83,349 (14.0) | 0.0244 | 80,900 (13.6) | 81,158 (13.6) | 0.0005 | | Chronic lung diseases | 57,411 (9.6) | 64,891 (10.9) | 0.0414 | 61,038 (10.3) | 61,343 (10.3) | 0.0011 | | Chronic liver diseases | 7964 (1.3) | 8661 (1.5) | 0.0100 | 8297 (1.4) | 8339 (1.4) | 0.0004 | | Cystic fbrosis | 113 (0.0) | 120 (0.0) | 0.0008 | 118 (0.0) | 118 (0.0) | 0.0001 | Table 1 continued | | Pre-weighting | | | Post-weighting | | | |---------------------------------------------------------------------------------------------|----------------|----------------|--------|----------------|----------------|--------| | | Exposed | Unexposed | SMD | Exposed | Unexposed | SMD | | Diabetes mellitus, type 1 and type 2 | 137,516 (23.1) | 147,943 (24.8) | 0.0410 | 142,791 (24.0) | 143,130 (24.1) | 0.0003 | | Disabilities | 47,395 (7.9) | 44,244 (7.4) | 0.0198 | 45,761 (7.7) | 45,757 (7.7) | 0.0006 | | Heart conditions | 112,438 (18.9) | 122,461 (20.5) | 0.0423 | 117,266 (19.7) | 117,725 (19.8) | 0.0010 | | HIV | 2873 (0.5) | 2299 (0.4) | 0.0147 | 2600 (0.4) | 2579 (0.4) | 0.0007 | | Mental health disorders | 108,069 (18.1) | 109,885 (18.4) | 0.0079 | 108,937 (18.3) | 109,154 (18.3) | 0.0001 | | Neurologic conditions | 20,719 (3.5) | 27,769 (4.7) | 0.0599 | 24,040 (4.0) | 24,296 (4.1) | 0.0018 | | Obesity | 157,058 (26.3) | 162,182 (27.2) | 0.0194 | 159,299 (26.8) | 159,623 (26.8) | 0.0001 | | Primary immunodefciencies | 10,893 (1.8) | 11,770 (2.0) | 0.0108 | 11,322 (1.9) | 11,365 (1.9) | 0.0003 | | Pregnancy and recent pregnancy | 2654 (0.4) | 2829 (0.5) | 0.0043 | 2671 (0.4) | 2692 (0.5) | 0.0004 | | Physical inactivity | 669 (0.1) | 682 (0.1) | 0.0006 | 669 (0.1) | 673 (0.1) | 0.0001 | | Smoking, current and former | 93,102 (15.6) | 102,816 (17.2) | 0.0440 | 97,433 (16.4) | 97,909 (16.5) | 0.0013 | | Solid organ or hematopoietic cell
transplantation | 1759 (0.3) | 1818 (0.3) | 0.0018 | 1797 (0.3) | 1802 (0.3) | 0.0001 | | Tuberculosis | 185 (0.0) | 225 (0.0) | 0.0036 | 206 (0.0) | 207 (0.0) | 0.0001 | | Use of immunosuppressive medica
tions | 36,308 (6.1) | 33,344 (5.6) | 0.0212 | 34,898 (5.9) | 34,902 (5.9) | 0.0004 | | Asthma | 56,520 (9.5) | 53,912 (9.0) | 0.0151 | 55,158 (9.3) | 55,175 (9.3) | 0.0005 | | Time since last COVID monovalent
vaccination | | | 0.1391 | | | 0.0497 | | < = 90 days | 1214 (0.2) | 7243 (1.2) | | 2072 (0.3) | 4229 (0.7) | | | 91–180 day | 14,712 (2.5) | 21,331 (3.6) | | 17,731 (3.0) | 18,026 (3.0) | | | 180+ days | 403,177 (67.6) | 390,122 (65.4) | | 399,162 (67.2) | 398,445 (67.0) | | | Not reported | 177,145 (29.7) | 177,552 (29.8) | | 175,019 (29.5) | 174,378 (29.3) | | | Time since last COVID infection | | | 0.0473 | | | 0.0025 | | < = 120 days | 3847 (0.6) | 3683 (0.6) | | 3752 (0.6) | 3750 (0.6) | | | 121–180 day | 4101 (0.7) | 3483 (0.6) | | 3784 (0.6) | 3772 (0.6) | | | 180+ days | 24,912 (4.2) | 19,879 (3.3) | | 22,296 (3.8) | 22,083 (3.7) | | | Not reported | 563,388 (94.5) | 569,203 (95.5) | | 564,151 (95.0) | 565,474 (95.0) | | | Evidence of COVID vaccination with
prior season's vaccine during the pre
index period | 417,795 (70.1) | 417,795 (70.1) | 0.0000 | 417,848 (70.3) | 419,657 (70.5) | 0.0038 | Table 1 continued | | Pre-weighting | | | Post-weighting | | | |------------------------------------------------------------------|--------------------------|--------------------------|--------|--------------------------|--------------------------|--------| | | Exposed | Unexposed | SMD | Exposed | Unexposed | SMD | | Evidence of infuenza vaccination dur
ing the pre-index period | 457,850 (76.8) | 382,689 (64.2) | 0.2791 | 418,051 (70.4) | 418,466 (70.3) | 0.0013 | | Diagnosis of infuenza during pre
index period | 9189 (1.5) | 9687 (1.6) | 0.0067 | 9399 (1.6) | 9432 (1.6) | 0.0002 | | Week of last healthcare activity before
start of intake | | | 0.0000 | | | 0.0000 | | 0–4 weeks | 525,371 (88.1) | 525,371 (88.1) | | 523,897 (88.2) | 524,986 (88.2) | | | 5–26 weeks | 63,699 (10.7) | 63,699 (10.7) | | 63,033 (10.6) | 63,059 (10.6) | | | 27–52 weeks
> 52 weeks or unknown | 5836 (1.0)
1342 (0.2) | 5836 (1.0)
1342 (0.2) | | 5723 (1.0)
1332 (0.2) | 5707 (1.0)
1327 (0.2) | | *SD* standard deviation, *SMD* standardized mean diference ![](https://assets.reachrx.ai/images/10.1007%E2%98%8Ds40121-025-01292-2/_page_8_Figure_4.jpeg) **Fig. 1** Cumulative incidence curves of days since cohort entry date (CED) in individuals ≥ 18 years to (**a**) COVID-19 related hospitalizations, and (**b**) medically-attended COVID-19, fnal analysis Adjusted overall VE (95% CI) in the interim analysis was 52.8% (34.8%, 65.8%) against COVID-19-related hospitalizations. The VE was sustained throughout the entire study period with a fnal VE of 45.2% (37.7%, 51.8%) (Fig. [2](#page-8-1)). This was also observed in the VE against medically-attended COVID-19 where VE was shown to be 39.4% (35.0%, 43.5%) and 33.1% (30.6–35.4%) in the interim and fnal analysis, respectively. Similar trends were observed in all subpopulations of interest, ≥ 65 years and 18–64 high-risk/≥ 65 years (Supplemental Table 2). ![](https://assets.reachrx.ai/images/10.1007%E2%98%8Ds40121-025-01292-2/_page_8_Figure_7.jpeg) **Fig. 2** Adjusted overall vaccine effectiveness against COVID-19 related hospitalizations, interim and fnal analysis across subpopulations of interest ## DISCUSSION The results of this study show that the mRNA-1273 KP.2 vaccine provided signifcant protection against hospitalizations and medicallyattended COVID-19 in the 2024–2025 season. This VE was sustained throughout the longer median follow-up time. VE against hospitalizations was 52.8% in the interim analysis and was sustained throughout the longer median time with a VE of 45.2%. VE against medicallyattended COVID-19 was 39.4% in the interim analysis, and was also sustained for the entire study period with a VE of 33.1%. Protection was consistently observed across subgroups, including older adults and those with other specifc underlying medical conditions that may increase the risk of severe COVID-19. Given the continual evolution of SARS-CoV-2 and the emergence of new variants, COVID-19 vaccines require updates to ensure alignment with circulating strains. There is a critical need for ongoing collection of real-world evidence each season to assess effectiveness of updated vaccines. This study's fndings show the VE of mRNA-1273 align with previous evaluations of prior years' updated mRNA-1273 COVID-19 vaccines against hospitalization with COVID-19 showing an incremental beneft of vaccinating every year against new VOCs, and therefore reinforcing the continued importance of ongoing COVID-19 vaccinations. Across seasons and formulation, VE in adults aged ≥ 18 years ranged from 51 to 70% against COVID-19-related hospitalization; VE against medically-attended COVID-19 ranged from 24 to 39%. VE estimates of mRNA-1273 were similar across subgroups, which included adults aged ≥ 18 years, adults aged ≥ 65 years, and adults aged ≥ 18 years at high-risk of severe outcomes [[15](#page-12-8), [19,](#page-12-10) [20](#page-12-11)]. Additionally, these fndings are aligned with other published estimates of mRNA COVID-19 VE against hospitalization ranging from 45% (95% CI 36–53%) to 46% (95% CI 26–60%) in immunocompetent adults aged 65 and older in the Center for Disease Control's VISION and IVY networks [[21\]](#page-12-12). These VE estimates underscore the beneft of administering mRNA-1273 KP.2 in the adult population and among those who are at higher risk for COVID-19-related outcomes. In the years since COVID-19 emerged, repeated infections, widespread vaccination efforts, or a combination of both have led most adults to develop a level of immunity against the SARS-CoV-2 virus [\[22](#page-12-13)]. The current study incorporated individuals regardless of their vaccination and infection history through matching factors or covariates. More than 70% of individuals in the study have previously received a 2023–2024 mRNA-1273 vaccine (XBB.1.5 variant). As a result, the study captures the incremental protection the 2025–2025 mRNA-1273 vaccine (KP.2 variant) provides against hospitalizations, regardless of prior exposure and/or vaccination history. As COVID-19 vaccination uptake remains low, it is imperative to communicate the additive protection COVID-19 vaccine provide year after year to reinforce confdence in vaccination among clinicians and the general population. #### **Strengths** This retrospective, observational cohort study implemented multiple analytic approaches to adjust for confounding, specifcally the underlying differences between the unexposed cohort and the cohort who received a vaccination with mRNA-1273 KP.2 in the fall of 2024. Direct matching on clinical and demographic criteria such as age, sex, race, geographic region, and 2023–2024 XBB.1.5 vaccine receipt ensured balance on key confounders. Additionally, individuals were matched on week of last healthcare activity prior to the start of the intake period to mitigate potential surveillance bias by ensuring the groups are similar in terms of how often they engage with the healthcare system. The use of IPTW was able to further mitigate confounding and estimate average treatment effect among the full population; no further adjustment was needed to balance the cohorts. A matched cohort study offers several distinct advantages over other study designs. First, while all data were collected and available at the time of study initiation, the study limits selection bias by identifying individuals' vaccination status reported in the dataset at a date before the date of the outcome of interest, minimizing the impact of unmeasured confounders related to recall of healthcare access and differential testing patterns. Finally, cohort studies allow for stronger inferences by allowing the estimation of incidence rates, which offer crucial context for VE estimates. For instance, the relatively low incidence of COVID-19 hospitalizations in this analysis compared to 2023–24 [\[15](#page-12-8), [23](#page-12-14)] may contribute to the lower VE estimates observed here. Furthermore, by establishing temporality, cohort studies also strengthen causal inferences and allow for the assessment of VE over time. #### **Limitations** As in all observational studies, the exposure was not randomly assigned, so residual confounding remains possible despite adjustment for a wide range of baseline covariates. For example, vaccinated individuals may have had generally healthier behaviors or better underlying health status that were not fully captured in healthcare utilization measures or comorbidity indices, which could contribute to their lower risk of hospitalization with COVID-19. In addition, the study population consisted of individuals who were engaged with the healthcare system. As a result, people who experience barriers to care such as limited access, lower socioeconomic status, or lack of trust in healthcare institutions may be underrepresented. To partially mitigate this concern, we focused on hospitalization with COVID-19 as the primary outcome, reasoning that a severe event is less subject to differential healthcare-seeking behavior and other subjective infuences. As with all analyses based on claims and/or EHR data, undercapture of vaccination is likely. Incomplete recording of vaccination status would tend to bias VE estimates toward the null, potentially underestimating the true VE. Misclassifcation of both exposure and outcome is also possible, as diagnostic and procedure codes used to defne vaccination and COVID-19-related hospitalizations may be inaccurate, leading to incorrect classifcation of some individuals. Moreover, not all hospitalizations may be observed in these data, particularly among uninsured persons, underrepresented groups, or individuals receiving care outside the contributing insurance networks. Nonetheless, a validation study by Kadri et al. [[24](#page-13-0)] reported a positive predictive value of 98% for the U07.1 diagnosis code for COVID-19 compared against clinical documentation and laboratory results, supporting the validity of our outcome defnition. The incidence of hospitalization with COVID-19 in this study was lower than in earlier periods of the pandemic, a pattern consistent with other data sources [\[10](#page-12-15)]. The study had suffcient power for the observed incidence; however, the estimated reduction in risk of hospitalization after vaccination should be interpreted in the context of the generally lower burden of COVID-19-related hospitalization during the study season compared with previous years. Deaths were not available in the dataset due to the statistical certifcation for de-identifcation, which prohibited linkage to mortality data. Finally, vaccine effectiveness by individual high-risk conditions, including those immunocompromised, were not available as the current study presented was not designed nor powered to appropriately match for these conditions; future studies could help address this question. ## CONCLUSION The updated 2024–2025 mRNA-1273 KP.2 vaccine demonstrated substantial and incremental protection against hospitalization and medically-attended COVID-19 during the 2024/2025 respiratory virus season in the US. VE was sustained over longer median follow-up times. These fndings support continued annual vaccination efforts to reduce the burden of COVID-19, particularly among older adults and highrisk populations. These data support programs to improve COVID-19 vaccination coverage among these at-risk populations. *Medical Writing/Editorial Assistance.* The authors acknowledge that artifcial intelligence was used in the drafting of the manuscript. All text was checked and revised by authors. All AI software fees was funded by Moderna. *Author Contributions.* All authors contributed to the study and meet ICMJE guidelines. Nevena Vicic, Alina Bogdanov, Zhe Zheng, Taylor Ryan, Ni Zeng, Keya Joshi, Tianyi Lu, Machaon Bonafede, Andre B. Araujo, Amanda Wilson contributed to the concept and design, statistical analysis, interpretation of the data, and drafting of the manuscript. *Funding.* This work was supported by Moderna Inc. The journal's Rapid Service Fee was funded by Moderna. *Data Availability.* Individual-level data reported in this study are not publicly shared. Upon request, and subject to review, Moderna may provide the de-identifed aggregate-level data that support the findings of this study. Deidentifed data (including participant data as applicable) may be shared upon approval of an analysis proposal and a signed data access agreement. ### *Declarations* *Conflicts of Interest.* Amanda Wilson, Andre B. Araujo, Keya Joshi, Nevena Vicic, Tianyi Lu, and Zhe Zheng are employees and stockholders of Moderna, Inc. Alina Bogdanov, Machaon Bonafede, Ni Zeng, and Taylor Ryan are employees of Veradigm Inc. Veradigm was contracted by Moderna and received fees for study design, data management, and statistical analyses. *Ethical Approval.* This study was conducted in accordance with the Declaration of Helsinki and relevant guidelines for observational studies. The research involved de-identifed claims data and did not require direct patient involvement. Therefore, specifc ethics approval and informed consent were not needed, as the data were anonymized and complied with patient privacy regulations. Access to the data was provided under agreements with the data provider, which ensured adherence to ethical standards, including the protection of patient confdentiality. *Open Access.* This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. 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