Abstract
Background
Since late 2021, the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has undergone rapid evolutionary diversification, giving rise to successive subvariants with increasing immune escape. In response, coronavirus disease 2019 (COVID-19) vaccination strategies transitioned from ancestral-strain vaccines to variant-adapted formulations. Real-world evidence on the effectiveness and durability of these updated vaccines across the full Omicron evolutionary spectrum remains fragmented.
Objectives
To synthesise real-world evidence on the effectiveness of COVID-19 vaccines against SARS-CoV-2 infection and severe clinical outcomes across successive Omicron subvariants from 2022 to 2025, with particular emphasis on variant-adapted vaccine formulations and waning immunity over time.
Methods
A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines and registered in PROSPERO. MEDLINE (via PubMed), Embase, CINAHL, Scopus, and Web of Science Core Collection were systematically searched for peer-reviewed observational studies published between January 2022 and December 2025. Eligible studies assessed vaccine effectiveness during periods dominated by Omicron subvariants including BA.2, BA.5, XBB, BA.2.86/JN.1, and KP lineages. Findings were synthesised narratively due to substantial heterogeneity.
Results
Thirty observational studies from North America, Europe, and East Asia were included. Across Omicron subvariants, vaccine effectiveness against SARS-CoV-2 infection was generally modest and short-lived, with rapid waning within months after vaccination and estimates frequently approaching null during later subvariant periods. In contrast, updated and variant-adapted vaccines consistently provided meaningful protection against severe COVID-19 outcomes, including hospitalization and death. Protection was highest during BA.4/BA.5 and early XBB-dominant periods and declined with increasing time since vaccination, especially during JN.1- and KP-predominant periods and among the oldest age groups. Importantly, substantial protection against severe outcomes persisted within the first 1–3 months following vaccination, with effectiveness against hospitalization and death generally ≥ 50%, although effectiveness declined over time during later Omicron subvariant periods.
Conclusion
Updated and variant-adapted COVID-19 vaccines continue to confer substantial protection against severe COVID-19 outcomes across successive Omicron subvariants, despite limited and rapidly waning effectiveness against SARS-CoV-2 infection. These findings support prioritisation of periodic booster vaccination for older adults and other high-risk populations, with vaccine performance primarily evaluated using protection against severe clinical outcomes.
Clinical trial number
Not applicable.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12879-026-13281-y.
Keywords: COVID-19, SARS-CoV-2, Vaccine effectiveness, Omicron subvariants, Variant-adapted vaccines, Severe COVID-19 outcomes, COVID-19 booster vaccination, Real-world evidence
Background
Since its emergence in late 2021, the Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has undergone rapid and continuous evolution, giving rise to successive subvariants characterised by increasing transmissibility and immune escape [1, 2]. Early Omicron lineages (BA.1 and BA.2) were quickly replaced by BA.4/BA.5, followed by XBB-lineage variants and, more recently, BA.2.86-derived lineages including JN.1 and KP sublineages [3–7]. These evolutionary changes have posed substantial challenges to the durability of vaccine-induced protection, particularly against SARS-CoV-2 infection, while preserving protection against severe coronavirus disease 2019 (COVID-19) outcomes such as hospitalization and death [3, 5, 8–10]. In parallel, computational and mathematical modelling studies have provided complementary insights into SARS-CoV-2 evolutionary dynamics, immune escape, and the potential impact of variant-adapted vaccination strategies [11, 12].
In response to immune escape observed with earlier Omicron subvariants, vaccination strategies against COVID-19 transitioned from ancestral-strain monovalent vaccines to variant-adapted formulations [3–5]. Bivalent vaccines incorporating Omicron BA.4/BA.5 antigens were introduced in late 2022 [3, 4], followed by monovalent XBB.1.5-adapted vaccines during the 2023–2024 vaccination season [5, 13, 14] and JN.1-adapted vaccines in late 2024 [7, 9, 13]. These updates aimed to restore vaccine effectiveness by improving antigenic match with circulating variants, particularly among older adults and individuals at higher risk of severe disease [3, 5, 9, 13, 15].
Accumulating real-world evidence indicates that while vaccine effectiveness against SARS-CoV-2 infection has been modest and short-lived during Omicron circulation, protection against severe outcomes has remained substantial across successive subvariant waves [3, 5, 10, 16]. Observational studies conducted during BA.4/BA.5-predominant periods demonstrated high short-term effectiveness of bivalent mRNA boosters against COVID-19–related hospitalization and death [4, 8]. During XBB-dominant periods, monovalent XBB.1.5-adapted vaccines continued to provide substantial protection against severe disease, although effectiveness declined with increasing time since vaccination and ongoing antigenic drift [5, 14, 17].
More recent evidence from periods dominated by JN.1 and KP lineages suggests partial attenuation of vaccine effectiveness against severe outcomes, particularly among the oldest age groups and at longer intervals after vaccination [6, 7, 9, 18]. Nonetheless, multiple large, population-based studies from Europe and North America have consistently shown that updated vaccines retain substantial protection against hospitalization and death, reinforcing their role in mitigating health system burden and preventing mortality in high-risk populations [6, 7, 9, 10, 18].
Despite the rapidly expanding literature, evidence remains fragmented across subvariants, vaccine formulations, study designs, and outcome definitions, limiting the ability to draw consistent conclusions across the full Omicron evolutionary spectrum [5, 10]. Many prior reviews have focused on early Omicron periods, infection outcomes, or ancestral and early bivalent vaccines, with limited synthesis of data covering the full Omicron evolutionary spectrum and contemporary variant-adapted vaccines [19–22]. A comprehensive synthesis of real-world vaccine effectiveness across BA.2, BA.5, XBB, JN.1, and KP lineages is therefore essential to inform ongoing vaccination strategies, optimise booster timing, and guide policy decisions in the context of SARS-CoV-2 endemicity.
Accordingly, this systematic review aimed to synthesise real-world evidence on COVID-19 vaccine effectiveness against SARS-CoV-2 infection and severe clinical outcomes across successive Omicron subvariants from 2022 to 2025, with particular emphasis on variant-adapted vaccines and durability of protection over time.
Methods
Protocol and reporting
This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines [23]. The review protocol was registered prospectively in the PROSPERO international prospective register of systematic reviews (registration number: CRD420251273629).
Eligibility criteria
Eligibility criteria were defined using the Population, Intervention, Comparator, Outcomes, and Study design (PICOS) framework (Table 1) [24].
Table 1.
PICOS eligibility criteria
| Component | Description |
|---|---|
| Population | Human participants from the general population (predominantly adults; paediatric populations included only where eligible data were reported within broader population-based studies) |
| Intervention | COVID-19 vaccination (primary series and/or booster doses; monovalent or variant-adapted vaccines) |
| Comparator | Unvaccinated individuals or alternative vaccination status (e.g., different numbers of doses or time since last vaccination) |
| Outcomes | SARS-CoV-2 infection; COVID-19–related hospitalization; intensive care unit (ICU) admission; death |
| Study design | Observational studies (cohort, case–control, test-negative design) |
| Timeframe | January 2022–31 December 2025 |
| Setting | Real-world, population-based settings |
Eligible studies primarily included adult populations (≥ 18 years) from the general population. Paediatric populations were not the primary focus of this review and were included only when eligible data were reported within broader population-based studies and met all other inclusion criteria. Studies restricted exclusively to highly selected clinical populations (e.g., transplant recipients or individuals with specific immunodeficiency conditions) were excluded unless results were reported separately for the general population.
The intervention of interest was COVID-19 vaccination, including primary vaccination series and/or booster doses, using monovalent or variant-adapted vaccine formulations. Comparators included unvaccinated individuals or alternative vaccination statuses (e.g., different numbers of doses or time since last vaccination), as defined within individual studies.
Primary outcomes were vaccine effectiveness against SARS-CoV-2 infection (laboratory-confirmed or symptomatic) and severe COVID-19 outcomes, including COVID-19–related hospitalization, intensive care unit admission, or death. Severe outcomes were prioritised for synthesis and interpretation and were considered the primary outcomes of interest for policy relevance, while infection outcomes were treated as secondary. Secondary outcomes included vaccine effectiveness by time since vaccination, Omicron subvariant, vaccine formulation, and age group, where reported.
Study design and publication criteria
Eligible studies were real-world observational designs, including cohort studies, case–control studies, and test-negative design studies. Randomized controlled trials were excluded, as the objective of this review was to synthesise real-world vaccine effectiveness in routine population settings during evolving Omicron subvariant circulation. Modelling studies, ecological analyses, case reports, case series, non-human studies, and study protocols were also excluded.
Only peer-reviewed articles published in English between January 2022 and 31 December 2025 were eligible. Studies were required to report vaccine effectiveness estimates against clinically relevant COVID-19 outcomes and to provide variant-specific effectiveness estimates or to have been conducted during periods of documented Omicron subvariant dominance, as defined by national or regional genomic surveillance data. Eligible Omicron subvariants included BA.2, BA.5, XBB, BA.2.86/JN.1, and KP lineages.
Preprints, conference abstracts, and non–peer-reviewed surveillance or monitoring reports were excluded from the formal evidence synthesis.
The PRISMA 2020 checklist was used (see Supplementary Materials) [23].
Information sources and search strategy
A comprehensive literature search was conducted in MEDLINE (via PubMed), Embase (via Ovid), CINAHL, Scopus, and the Web of Science Core Collection. Searches were restricted to studies published between January 2022 and 31 December 2025, corresponding to the period of BA.2 and subsequent Omicron subvariant circulation.
Search strategies combined controlled vocabulary terms (e.g., MeSH) and free-text keywords related to COVID-19 vaccination, vaccine effectiveness, Omicron subvariants, and clinical outcomes, using Boolean operators (AND, OR), and were tailored to each database. A representative search strategy (PubMed) is provided below:
(“COVID-19”[Mesh] OR “SARS-CoV-2”[Mesh] OR COVID-19[tiab] OR SARS-CoV-2[tiab]) AND (“Vaccines”[Mesh] OR vaccin*[tiab] OR “vaccine effectiveness”[tiab] OR VE[tiab]) AND (Omicron[tiab] OR BA.2[tiab] OR BA.5[tiab] OR XBB[tiab] OR JN.1[tiab] OR KP[tiab]) AND (effectiveness[tiab] OR “real-world”[tiab] OR observational[tiab])
The full database-specific search strategies are provided in Supplementary Table S1.
All records were imported into EndNote (version 21.2) for de-duplication and subsequently uploaded to Covidence (Veritas Health Innovation, Melbourne, Australia) for screening.
Reference lists of included studies and relevant systematic reviews were hand-searched, and backward and forward citation tracking was performed to identify additional eligible studies.
Study selection
Titles and abstracts were screened independently by three reviewers to identify potentially eligible studies. Full texts of selected articles were then independently assessed against the eligibility criteria. Discrepancies at either stage were resolved through discussion or consultation with a fourth reviewer.
Reasons for exclusion at the full-text stage were recorded and are presented in Supplementary Table S2. The study selection process is summarised in Fig. 1.
Fig. 1.
Flow diagram of studies included in the systematic review
Data extraction
Data were extracted independently by three reviewers using a standardized data extraction form. Discrepancies were resolved through discussion. Extracted information included study design, country and setting, population characteristics, vaccine type and dosing, Omicron subvariant or dominant period, outcome definitions, time since vaccination, adjustment for prior SARS-CoV-2 infection, effect estimates with corresponding confidence intervals, and variables included in multivariable models. Where multiple estimates were reported, the most fully adjusted estimates were extracted. Information on prior vaccination history, including number of doses, vaccine platform, and adjustment for prior SARS-CoV-2 infection, was extracted where reported.
Risk of bias assessment
Risk of bias was assessed independently by two reviewers using the ROBINS-I tool for non-randomized studies of interventions [25]. Domains assessed included bias due to confounding, selection of participants, classification of interventions, deviations from intended interventions, missing data, measurement of outcomes, and selection of the reported result. Disagreements were resolved through discussion or consultation with a third reviewer.
Data synthesis
Findings were synthesised using narrative synthesis and summarised in structured tables stratified by Omicron subvariant and clinical outcome. Absolute vaccine effectiveness estimates comparing vaccinated and unvaccinated individuals were prioritised, while relative vaccine effectiveness estimates were included where effect measures and comparator frameworks were sufficiently comparable across studies.
For interpretative consistency, “substantial protection” was defined as vaccine effectiveness estimates indicating clinically meaningful protection against severe COVID-19 outcomes, generally corresponding to moderate to high effectiveness (approximately ≥ 50%) against hospitalization, ICU admission, or death.
Where numerical confidence intervals were not reported for waning estimates, point estimates were retained and reported as not reported (NR). Formal meta-analysis was not performed because of substantial clinical and methodological heterogeneity across studies, including differences in study design, population characteristics, vaccine formulations, outcome definitions, comparator frameworks, and follow-up duration. Heterogeneity was therefore described qualitatively.
Assessment of publication bias was not performed using formal quantitative methods (e.g., funnel plots or statistical tests), as meta-analysis was not conducted due to substantial clinical and methodological heterogeneity. Instead, potential publication bias was considered qualitatively during interpretation of the findings.
Subgroup analyses
Where data permitted, subgroup analyses were conducted by Omicron subvariant, clinical outcome severity, vaccine type, booster status, time since vaccination, and age group.
Results
Study selection
The database search identified 4,200 potentially relevant records. After removal of duplicates, 1,775 titles and abstracts were screened, of which 1,410 were excluded as clearly irrelevant. Full texts of 365 articles were retrieved and assessed for eligibility. Following detailed review, 335 studies were excluded for the following reasons: outside the prespecified review scope (e.g., early Omicron BA.1/BA.2 periods, ancestral or non–variant-adapted vaccines, or lack of relevant subvariant coverage) (n = 182); no assessment of severe COVID-19 outcomes (hospitalization, ICU admission, or death) (n = 64); ineligible study design (e.g., modelling studies, immunogenicity studies, ecological analyses, case-only designs, or narrative reports) (n = 51); non-comparable vaccine effectiveness frameworks or effect measures (n = 18); restricted or non-generalizable populations (e.g., pediatric-only or highly selected cohorts) (n = 9); conference abstracts or non–peer-reviewed reports (n = 6); and duplicate or overlapping populations (n = 5).
The study selection process is summarised in Fig. 1, and detailed reasons for exclusion are presented in Supplementary Table S2.
A total of 30 observational studies met the eligibility criteria and were included in the qualitative synthesis [3–10, 13–18, 26–41].
Characteristics of included studies
The characteristics of the included studies are summarised in Table 2. Studies were published between 2022 and 2025 and were conducted across North America, Europe, and East Asia, with the majority originating from high-income countries with established electronic health record or national surveillance systems. The included studies were predominantly conducted in North America (n = 12), Europe (n = 16), and East Asia (n = 2). Notably, none of the included studies were conducted in low- and middle-income countries (0/30, 0%), precluding meaningful stratified synthesis by country income level. This geographic concentration may limit the generalisability of findings, as differences in healthcare infrastructure, vaccine access, prior infection dynamics, and population characteristics may influence vaccine effectiveness estimates. Study designs included test-negative case–control studies, retrospective or prospective cohort studies, and register-based target-trial emulations.
Table 2.
Characteristics of included studies
| First author (year) | Country / region | Study design | Study period | Dominant Omicron subvariant(s) | Population | Sample size | Vaccine type(s) | Outcomes assessed |
|---|---|---|---|---|---|---|---|---|
| Ackerson (2024) [3] | United States (Southern California) | Test-negative case–control | Sep 1, 2022 – Jun 30, 2023 | BA.4/BA.5; XBB-related (incl. XBB.1.5, XBB.1.16, XBB.1.9) | General population aged ≥ 6 months (Kaiser Permanente members) | rVE cohort: 20,966 cases / 62,898 controls; VE cohort: 10,336 cases / 31,008 controls | mRNA-1273 BA.4/BA.5 bivalent (mRNA-1273.222); comparator: ≥2 doses monovalent mRNA vaccines or unvaccinated | SARS-CoV-2 infection; ED/UC encounters; COVID-19 hospitalization; hospital death |
| Andersen (2025) [26] | United States (California, Louisiana) | Retrospective cohort study (linked insurance claims–state immunization registries) | 25 September 2023–31 March 2024 | XBB.1.5-predominant period; co-circulating XBB-lineage subvariants and emerging JN.1 | Immunocompetent, non-pregnant adults aged ≥ 18 years from the general population | 6,344,448 | Monovalent XBB.1.5-adapted mRNA vaccine (BNT162b2 XBB.1.5); comparator: no receipt of any XBB.1.5 vaccine | COVID-19–associated hospitalization; COVID-19–associated ED visit |
| Andersson (2023) [4] | Nordic countries (Denmark, Finland, Norway, Sweden) | Nationwide register-based cohort study (target trial emulation) | 1 July 2022–10 April 2023 | Omicron BA.4/BA.5-predominant period; subsequent circulation of BQ-, BF-, and early XBB-lineage subvariants | Adults aged ≥ 50 years from the general population who had received ≥ 3 COVID-19 vaccine doses | 2,676,323 individuals (1,634,199 received bivalent BA.4/BA.5 booster; 1,042,124 received bivalent BA.1 booster) | Bivalent mRNA booster vaccines as fourth dose (BA.4/BA.5 or BA.1; BNT162b2 [Comirnaty] and mRNA-1273 [Spikevax]) | COVID-19–related hospitalization; COVID-19–related death |
| Andersson (2024) [5] | Nordic countries (Denmark, Finland, Sweden) | Nationwide register-based cohort study (target trial emulation) | 1 October 2023–21 April 2024 | XBB-lineage (predominantly EG.5.1), with subsequent JN.1 predominance | Community-dwelling adults aged ≥ 65 years eligible for autumn/winter 2023–2024 COVID-19 vaccination and with ≥ 4 prior COVID-19 vaccine doses | 3,898,264 eligible individuals; matched cohort: 1,876,282 vaccinated with XBB.1.5-adapted vaccine and 1,876,282 matched non-recipients | Monovalent XBB.1.5-adapted mRNA vaccines (BNT162b2 [Comirnaty]; mRNA-1273 [Spikevax]) | COVID-19–related hospitalization; COVID-19–related death |
| Antunes (2024) [27] | Europe (Spain, Croatia, Ireland, Malta, Navarre [Spain], Portugal) | Multicentre hospital-based test-negative case–control study (VEBIS SARI VE network) | 15 February 2023–31 August 2023 | Omicron XBB-lineage–predominant period (including XBB, XBB.1.5, XBB.1.5 + F456L) | Hospitalized adults aged ≥ 60 years with SARI | 3,788 participants (743 SARS-CoV-2–positive cases; 3,045 test-negative controls) | Adapted bivalent mRNA COVID-19 vaccines (BNT162b2 and mRNA-1273; Original/Omicron BA.1 or BA.4/BA.5); comparator: monovalent vaccination ≥ 6 months before campaign | COVID-19–related hospitalization |
| Antunes (2024) [28] | Europe (Belgium, Croatia, Ireland, Lithuania, Malta, Navarre region [Spain], Spain) | Multicentre hospital-based test-negative case–control study (VEBIS hospital network) | 05 October 2023–14 January 2024 | XBB.1.5-like lineage–predominant period; later JN.1 emergence | Hospitalized adults aged ≥ 18 years with SARI, targeted for vaccination according to national recommendations (older adults and/or individuals with medical risk conditions) | 4,079 participants (622 SARS-CoV-2–positive cases; 3,457 test-negative controls) | Monovalent XBB.1.5-adapted COVID-19 vaccines (BNT162b2 [Comirnaty], mRNA-1273 [Spikevax], NVX-CoV2373 [Nuvaxovid]); comparator: no vaccination during the 2023 autumn campaign (never vaccinated or last dose ≥ 180 days before campaign) | PCR-confirmed COVID-19–related hospitalization |
| Antunes (2025) [6] | Europe (Belgium, Germany, Spain, Hungary, Ireland, Lithuania, Malta, Navarre region [Spain], Portugal) | Multicentre hospital-based test-negative case–control study (VEBIS hospital network) | November 2023 – May 2024 | JN.1–predominant period | Hospitalized adults aged ≥ 65 years with SARI | 8,047 participants (661 SARS-CoV-2–positive cases; 7,386 test-negative controls) | Monovalent XBB.1.5-adapted COVID-19 vaccines (BNT162b2 [Comirnaty], mRNA-1273 [Spikevax], NVX-CoV2373 [Nuvaxovid]); comparator: no vaccination during the 2023/24 vaccination campaign (never vaccinated or last dose ≥ 180 days before campaign) | PCR-confirmed COVID-19–related hospitalization |
| Aziz (2025) [13] | England | Test-negative case–control study (national surveillance data) | Spring 2024 (15 April–30 June 2024) and Autumn 2024 (03 October 2024–31 January 2025); follow-up to 27 April 2025 | Omicron XBB-lineage (spring 2024) and JN.1 and sub-lineages (autumn 2024) | Hospitalized adults targeted for COVID-19 vaccination (spring: adults aged ≥ 75 years and immunosuppressed individuals; autumn: adults aged ≥ 65 years and clinical risk groups) | Spring 2024 analysis: 47,538 eligible tests (8,879 SARS-CoV-2–positive cases; 38,659 test-negative controls); Autumn 2024 analysis: 61,126 eligible tests (4,931 cases; 56,195 controls) | Monovalent mRNA COVID-19 vaccines (XBB.1.5-adapted in spring 2024; JN.1-adapted in autumn 2024; BNT162b2 and mRNA-1273) | COVID-19–related hospitalization |
| Caffrey (2024) [29] | United States (Veterans Affairs Healthcare System) | Nationwide test-negative case–control study (integrated electronic health records) | 25 September 2023–31 January 2024 | Omicron XBB-lineage–predominant period with subsequent XBB/JN.1 co-circulation and JN.1 predominance | Adults aged ≥ 18 years receiving care in the US Veterans Affairs Healthcare System with acute respiratory infection and SARS-CoV-2 testing | 113,174 ARI episodes (20,523 SARS-CoV-2–positive cases; 92,651 test-negative controls) | Monovalent XBB.1.5-adapted mRNA vaccine (BNT162b2); comparator: no receipt of any XBB vaccine | COVID-19–related hospitalization; ED or UC visit; outpatient visit |
| Carazo (2025) [14] | Canada (Quebec) | Population-based test-negative case–control study (provincial administrative and laboratory databases) | October 29, 2023 – August 17, 2024 | XBB/EG.5-predominant period; JN.1-predominant period; KP.2/KP.3-predominant period | Adults aged ≥ 60 years tested in acute-care hospitals for COVID-19–compatible illness | 114,005 SARS-CoV-2 nucleic acid amplification tests (5,532 COVID-19 hospitalized cases; 108,473 test-negative controls) | Monovalent mRNA XBB.1.5-adapted vaccines (BNT162b2; mRNA-1273); comparator: prior monovalent or bivalent vaccination in 2022, non-XBB vaccination, or unvaccinated | COVID-19–related hospitalization |
| Delaunay (2024) [30] | Europe (Croatia, France, Germany, Hungary, Ireland, Netherlands, Portugal, Spain [national + Navarre], Sweden) | Multicentre test-negative case–control study (primary care) | September 2023 – January 2024 | XBB and sublineages, with increasing JN.1 predominance during the later study period | General population aged ≥ 5 years presenting to primary care with acute respiratory infection; restricted to national COVID-19 vaccination target groups (older adults and/or individuals with chronic conditions) | 5,454 participants (1,057 SARS-CoV-2–positive cases; 4,397 test-negative controls) | Updated monovalent XBB.1.5 COVID-19 vaccines (predominantly Comirnaty XBB.1.5) | Laboratory-confirmed, medically attended symptomatic SARS-CoV-2 infection |
| Grewal (2024) [8] | Canada (Ontario) | Test-negative case–control | 19 June 2022–28 January 2023 | BA.4/BA.5; BQ | Community-dwelling adults aged ≥ 50 years | 3,755 Omicron-associated severe outcome cases; 14,338 test-negative controls (16,247 unique individuals) | Monovalent mRNA vaccines (Moderna; Pfizer-BioNTech); bivalent mRNA vaccines (Moderna BA.1; Pfizer-BioNTech BA.4/BA.5) | COVID-19–related hospitalization or death (Omicron-associated severe outcomes) |
| Hansen (2025) [9] | Denmark | Nationwide register-based cohort | Oct 1, 2024 – Jan 31, 2025 | JN.1; KP.3.1.1; XEC | Adults aged ≥ 65 years from the general population | 894,560 | Monovalent JN.1-adapted mRNA vaccines (BNT162b2; mRNA-1273) | COVID-19–associated hospitalization; death |
| Humphreys (2025) [7] | Europe (Belgium, Denmark, Italy, Navarre [Spain], Portugal, Sweden) | Multi-country register-based cohort study (VEBIS electronic health record network) | October 2024 – January 2025 | JN.1 and its descendant lineages, including KP.3, XEC, and emerging LP.8.1 | Community-dwelling adults aged ≥ 65 years eligible for the 2024 autumn COVID-19 vaccination campaign | ≈ 18.6 million individuals (≈ 14.8 million unvaccinated; ≈3.8 million vaccinated by end of follow-up) | Monovalent JN.1-adapted COVID-19 vaccines (predominantly Comirnaty JN.1; minority Spikevax JN.1 and KP.2-adapted vaccines) | COVID-19–related hospitalization; COVID-19–related death |
| Humphreys (2025) [15] | Europe (Belgium, Denmark, Italy, Navarre [Spain], Portugal, Sweden) | Multi-country register-based cohort study (VEBIS electronic health record network) | June 1 – August 25, 2024 | JN.1 lineage with predominance of KP sublineages (KP.2, KP.3) | Community-dwelling adults aged ≥ 65 years eligible for the 2023 autumn COVID-19 vaccination campaign | 19,306,009 individuals (13,264,417 unvaccinated; 6,041,592 vaccinated) | Monovalent XBB.1.5-adapted COVID-19 vaccines (predominantly Comirnaty XBB.1.5; minority Spikevax XBB.1.5 and Nuvaxovid XBB.1.5) | COVID-19–related hospitalization; COVID-19–related death |
| Kirsebom (2024) [17] | England | National test-negative case–control study (linked national surveillance, vaccination, and hospital admission datasets) | 4 September 2023–21 January 2024 | Omicron XBB-related sub-lineages with subsequent emergence and predominance of JN.1 (also including EG.5.1) | Hospitalized adults aged ≥ 65 years eligible for the autumn 2023 COVID-19 vaccination program | 28,916 eligible tests (6,760 SARS-CoV-2–positive hospitalization cases; 22,156 test-negative controls) | Monovalent XBB.1.5-adapted mRNA vaccine and bivalent BA.4/BA.5 mRNA vaccine; comparator: not boosted / prior doses waned | COVID-19–related hospitalization |
| Kopel (2024) [31] | United States | Retrospective cohort study (linked EHR–claims data) | Sep 12 – Dec 31, 2023 | XBB.1.5 (XBB-lineage; emerging JN.1) | Adults aged ≥ 18 years from the general population | 1,718,670 | Monovalent XBB.1.5–adapted mRNA vaccine (mRNA-1273.815) | COVID-19–related hospitalization; medically attended COVID-19 |
| Lee (2024) [32] | South Korea | Test-negative case–control study (hospital-based) | 26 October – 31 December 2023 | Omicron XBB-lineage (EG.5 and HK.3 predominant; emerging JN.1) | Symptomatic adults aged ≥ 18 years presenting to hospital settings | 5,516 (692 XBB.1.5-vaccinated; 4,824 non-XBB.1.5) | Monovalent mRNA XBB.1.5-adapted COVID-19 vaccine (Pfizer or Moderna); comparator: no XBB.1.5 vaccination | Symptomatic SARS-CoV-2 infection; COVID-19–related hospitalization; receipt of oxygen therapy |
| Lee (2025) [16] | Canada (Ontario) | Population-based test-negative case–control study (linked administrative and laboratory databases) | 24 September 2023–1 June 2024 | XBB sublineages initially; subsequent JN/KP predominance | Community-dwelling adults aged ≥ 50 years | 24,498 individuals (4,895 cases with severe outcomes; 23,223 test-negative controls) | Monovalent mRNA XBB.1.5-adapted vaccines (BNT162b2 or mRNA-1273); comparator: ≥2 doses of non-XBB.1.5 vaccines (original monovalent or Omicron-containing bivalent) or unvaccinated | Omicron-associated severe outcomes (COVID-19–related hospitalization or death) |
| Link-Gelles (2025) [10] | United States (VISION Network; 6 health systems, 8 states) | Multicenter test-negative case–control study using EHR data | 21 September 2023–22 August 2024 | XBB-predominant period followed by JN.1-predominant period | Adults aged ≥ 18 years with COVID-19–like illness presenting to ED, urgent care, or hospital settings | 345,639 ED/urgent care encounters and 111,931 hospitalizations | 2023–2024 monovalent XBB.1.5 COVID-19 vaccines (mRNA-1273, BNT162b2, and NVX-CoV2373); comparator: no receipt of a 2023–2024 COVID-19 vaccine | Medically attended COVID-19 (ED/UC); COVID-19–associated hospitalization; critical illness (ICU admission or in-hospital death) |
| Ma (2024) [33] | United States (26 hospitals, IVY Network) | Test-negative case–control study | 18 Oct 2023–9 Mar 2024 | XBB lineages; JN.1 lineages | Adults ≥ 18 years hospitalized with COVID-19–like illness | 5,562 (982 cases; 4,580 controls) | Updated 2023–2024 monovalent XBB.1.5 vaccine | COVID-19–associated hospitalization; severe in-hospital outcomes (ICU admission, IMV or death) |
| Monge (2024) [34] | EU/EEA (Belgium, Denmark, Italy, Spain [Navarra], Norway, Portugal, Netherlands) | Retrospective multicountry cohort study (linked EHRs) | October–November 2023 | XBB.1.5-dominant period | Community-dwelling adults aged ≥ 65 years eligible for the 2023 autumn COVID-19 booster | Pooled cohorts across seven countries (person-time analysis) | Monovalent XBB.1.5 COVID-19 vaccine (predominantly BNT162b2; minority mRNA-1273) | COVID-19–related hospitalization; COVID-19–related death |
| Nguyen (2025) [35] | Belgium, Germany, Italy, Spain | Multicentre test-negative case–control study (id.DRIVE platform) | Oct 2, 2023 – Apr 2, 2024 | JN.1-predominant period | Adults aged ≥ 18 years hospitalized with SARI | 1,425 | Monovalent XBB.1.5-adapted mRNA vaccine (BNT162b2) | COVID-19–related hospitalization |
| Nham (2025) [36] | South Korea | Multicentre test-negative case–control study (hospital-based) | November 2023 – August 2024 | EG.5; HK.3; JN.1; KP.2; KP.3 | Adults aged ≥ 19 years presenting for SARS-CoV-2 testing at eight tertiary university hospitals (symptomatic or epidemiologically indicated testing) | 6,198 (Period 1: 1,671; Period 2: 1,811; Period 3: 2,716) | Monovalent XBB.1.5-adapted mRNA vaccines (BNT162b2 XBB.1.5; mRNA-1273 XBB.1.5) | Laboratory-confirmed SARS-CoV-2 infection; COVID-19–related hospitalization; ICU admission and in-hospital death (descriptive) |
| Nunes (2024) [18] | Europe (Belgium, Denmark, Italy, Navarre [Spain], Norway, Portugal, Sweden) | Multi-country register-based historical cohort study (VEBIS-EHR network) | December 2023–25 February 2024 | JN.1 | Community-dwelling adults aged ≥ 65 years eligible for the 2023 autumn COVID-19 vaccination campaign; nursing-home residents excluded | ≈ 20,183,622 individuals (13,729,181 unvaccinated; 6,454,441 vaccinated across seven countries) | Monovalent XBB.1.5-adapted mRNA vaccines (predominantly BNT162b2 XBB.1.5; minority mRNA-1273 XBB.1.5) | COVID-19–related hospitalization; COVID-19–related death |
| Rojas-Benedicto (2025) [37] | Spain | Test-negative case–control study (sentinel surveillance) | Oct 2023 – Sep 2024 (winter and summer waves) | XBB.1.5-dominant; JN.1-dominant; KP.3-dominant periods | Adults ≥ 60 years | 11,073 (2,527 cases; 8,546 controls) | Monovalent XBB.1.5 COVID-19 vaccine (Comirnaty) | Medically attended SARS-CoV-2 infection; COVID-19–related hospitalization |
| Tartof (2024) [38] | United States | Test-negative case–control study | 10 October–10 December 2023 | XBB-predominant period (JN.1 emerging) | Adults ≥ 18 years | 18,199 (2,854 SARS-CoV-2–positive cases; 15,345 test-negative controls) | Monovalent BNT162b2 XBB (XBB.1.5-adapted) COVID-19 vaccine | COVID-19–associated hospitalization; ED/UC encounter |
| Tartof (2024) [39] | United States | Test-negative case–control study | 10 October 2023–29 February 2024 | XBB sublineages; JN.1 sublineages | Adults aged ≥ 18 years presenting with acute respiratory infection and tested for SARS-CoV-2 in hospital, ED, or UC settings | 52,036 encounters (7,572 SARS-CoV-2–positive cases; 44,464 test-negative controls) | Monovalent BNT162b2 XBB.1.5-adapted mRNA COVID-19 vaccine; comparator: no receipt of any XBB vaccine | COVID-19–related hospitalization; ED/UC visit |
| van Werkhoven (2024) [40] | The Netherlands | Observational study using the screening method (population-based vaccine effectiveness analysis) | 9 October 2023–5 December 2023 | XBB-predominant period (XBB.1.5) | Previously vaccinated adults aged ≥ 60 years in the Netherlands, eligible for the 2023 seasonal COVID-19 vaccination program | 2,050 COVID-19 hospitalizations (including 92 ICU admissions) | Monovalent XBB.1.5-adapted mRNA vaccine (BNT162b2, Comirnaty); comparator: not receiving the 2023 seasonal XBB.1.5 vaccine | COVID-19–related hospitalization; admission to ICU |
| Wilson (2025) [41] | United States | Observational matched cohort study using administrative medical and pharmacy claims data (IPTW-adjusted Cox proportional hazards models) | Vaccination from 12 September 2023 to 31 December 2023; follow-up through 26 January 2024 | XBB-predominant period (XBB.1.5; overlap with early JN.1 emergence) | Adults aged ≥ 18 years in an insured US population; includes older adults (≥ 65 years), high-risk individuals, and immunocompromised adults | 2,544,322 individuals (1,272,161 vaccinated with mRNA-1273.815 matched 1:1 to 1,272,161 unvaccinated individuals) | Monovalent XBB.1.5-containing mRNA vaccine (mRNA-1273.815); comparator: no receipt of any 2023–2024 COVID-19 vaccine | COVID-19–related hospitalization (primary); medically attended COVID-19 (secondary) |
Abbreviations: ARI, acute respiratory infection; COVID-19, coronavirus disease 2019; ED, emergency department; EHR, electronic health record; EU/EEA, European Union/European Economic Area; ICU, intensive care unit; IMV, invasive mechanical ventilation; IPTW, inverse probability of treatment weighting; Investigating Respiratory Viruses in the Acutely Ill (IVY) Network; PCR, polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; rVE, relative vaccine effectiveness; SARI, severe acute respiratory infection; UC, urgent care; US, United States; VE, vaccine effectiveness; VEBIS, Vaccine Effectiveness, Burden and Impact Studies; VISION, Virtual SARS-CoV-2, Influenza, and Other Respiratory Viruses Network
Information on prior vaccination history and hybrid immunity was variably reported across studies and was accounted for in adjusted analyses where available
Most studies focused on older adults (≥ 60 or ≥ 65 years) or populations targeted for seasonal COVID-19 vaccination, although several also included adults aged ≥ 18 years. Sample sizes ranged from fewer than 4,000 participants in hospital-based test-negative studies to over 20 million individuals in large, multicountry registry-based cohorts.
Vaccines evaluated included bivalent BA.4/BA.5 mRNA vaccines, monovalent XBB.1.5-adapted mRNA vaccines, and, in more recent studies, JN.1-adapted mRNA vaccines. Comparators varied by study and included unvaccinated individuals, recipients of earlier monovalent or bivalent vaccines, or individuals with waned immunity from prior vaccination.
Vaccine effectiveness against SARS-CoV-2 infection
Tables 3, 4 and 5 summarise vaccine effectiveness against infection, severe outcomes, and waning immunity across Omicron subvariants. This section focuses on vaccine effectiveness against SARS-CoV-2 infection across successive Omicron subvariant periods, with emphasis on differences by variant and time since vaccination. Vaccine effectiveness against infection during Omicron circulation is presented in Table 3. Across studies, effectiveness against infection was modest and short-lived, with substantial variation by subvariant and time since vaccination.
Table 3.
Vaccine effectiveness against SARS-CoV-2 infection by Omicron subvariant
| First author (year) | Subvariant | Vaccine status / comparatora | Outcome definition | VE % (95% CI) | Time since last dose | Adjustment for prior infection |
|---|---|---|---|---|---|---|
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | SARS-CoV-2 infection | 52.7% (46.9–57.8) | 14–60 days | Yes |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | SARS-CoV-2 infection | 39.4% (30.1–47.5) | 61–120 days | Yes |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | SARS-CoV-2 infection | 35.5% (− 2.8–59.5) | 121–180 days | Yes |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | SARS-CoV-2 infection | 48.8% (33.4–60.7) | 14–60 days | Yes |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | SARS-CoV-2 infection | 26% (12.1–37.7) | 61–120 days | Yes |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | SARS-CoV-2 infection | −3.9% (− 18.1–11.3) | 121–180 days | Yes |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | SARS-CoV-2 infection | −18.3% (− 31.3–−2.9) | > 180 days | Yes |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. unvaccinated (VE) | SARS-CoV-2 infection | 29.3% (19.1–38.2) | 14–60 days | Yes |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. unvaccinated (VE) | SARS-CoV-2 infection | 2.8% (− 12.5–17.4) | 61–120 days | Yes |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. unvaccinated (VE) | SARS-CoV-2 infection | −8.8% (− 44.3–33) | 121–180 days | Yes |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. unvaccinated (VE) | SARS-CoV-2 infection | 21.2% (− 4.6–40.7) | 14–60 days | Yes |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. unvaccinated (VE) | SARS-CoV-2 infection | −13.4% (− 28.9–5.2) | 61–120 days | Yes |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. unvaccinated (VE) | SARS-CoV-2 infection | −30% (− 42–−15.5) | 121–180 days | Yes |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. unvaccinated (VE) | SARS-CoV-2 infection | −48.7% (− 58.4–−36.6) | > 180 days | Yes |
| Delaunay (2024) [30] | Any SARS-CoV-2 (XBB-dominant period) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | Medically attended symptomatic SARS-CoV-2 infection | 40% (26–53) | Any (≤ 14 weeks) | No |
| Delaunay (2024) [30] | Any SARS-CoV-2 (XBB-dominant period) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | Medically attended symptomatic SARS-CoV-2 infection | 48% (31–61) | < 6 weeks | No |
| Delaunay (2024) [30] | Any SARS-CoV-2 (XBB-dominant period) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | Medically attended symptomatic SARS-CoV-2 infection | 29% (3–49) | 6–14 weeks | No |
| Delaunay (2024) [30] | XBB and sublineages | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | Medically attended symptomatic SARS-CoV-2 infection | 50% (− 17–82) | Any | No |
| Delaunay (2024) [30] | XBB and sublineages | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | Medically attended symptomatic SARS-CoV-2 infection | 46% (− 32–82) | < 6 weeks | No |
| Kopel (2024) [31] | XBB-lineage (XBB.1.5-dominant; emerging JN.1) | mRNA-1273.815 (XBB.1.5-adapted) vs. no 2023–2024 updated vaccine (VE) | Any medically attended COVID-19 | 33.1% (30.2–35.9) | Median follow-up 63 days (IQR 44–78) | Yes (IPTW-adjusted models including infection history) |
| Lee (2024) [32] | XBB-lineage (EG.5; HK.3; emerging JN.1) | XBB.1.5-adapted mRNA vaccine vs. unvaccinated (VE) | Symptomatic SARS-CoV-2 infection | 65.2% (36.1–81) | Median 33 days since vaccination (IQR 19.5–47) | Yes |
| Lee (2024) [32] | XBB-lineage (EG.5; HK.3; emerging JN.1) | XBB.1.5-adapted mRNA vaccine vs. no XBB.1.5 vaccination (rVE) | Symptomatic SARS-CoV-2 infection | 57.7% (34.7–72.6) | Median 33 days since vaccination (IQR 19.5–47) | Yes |
| Nham (2025) [36] | XBB-lineage (EG.5; HK.3) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | Laboratory-confirmed SARS-CoV-2 infection | 57.1% (38–70.6) | November–December 2023 | Yes |
| Nham (2025) [36] | XBB-lineage / emerging JN.1 (HK.3; JN.1) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | Laboratory-confirmed SARS-CoV-2 infection | 18.8% (− 4.7–37.2) | January–April 2024 | Yes |
| Nham (2025) [36] | KP.2 / KP.3 | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | Laboratory-confirmed SARS-CoV-2 infection | 3.3% (− 15.4–19.1) | July–August 2024 | Yes |
| Rojas-Benedicto (2025) [37] | XBB.1.5-predominant period | Monovalent XBB.1.5 vaccine vs. unvaccinated (VE) | Medically attended SARS-CoV-2 infection | 45% (− 31–80) | Winter wave (October–November 2023) | No |
| Rojas-Benedicto (2025) [37] | JN.1-predominant period | Monovalent XBB.1.5 vaccine vs. unvaccinated (VE) | Medically attended SARS-CoV-2 infection | 26% (− 2–46) | Winter wave (December 2023–January 2024) | No |
| Rojas-Benedicto (2025) [37] | JN.1-predominant period | Monovalent XBB.1.5 vaccine vs. unvaccinated (VE) | Medically attended SARS-CoV-2 infection | 21% (− 11–44) | Summer wave (May–June 2024) | No |
| Rojas-Benedicto (2025) [37] | KP.3-predominant period | Monovalent XBB.1.5 vaccine vs. unvaccinated (VE) | Medically attended SARS-CoV-2 infection | −39% (− 91–−1) | Summer wave (June–July 2024) | No |
aVE denotes absolute vaccine effectiveness compared with unvaccinated individuals; rVE denotes relative vaccine effectiveness compared with ≥ 2 doses of monovalent mRNA vaccines. Infection outcomes include laboratory-confirmed SARS-CoV-2 infection or medically attended COVID-19 (e.g., primary care, emergency department, or outpatient encounters), as defined in the original studies. Estimates were adjusted for demographic and clinical covariates as specified by each study; adjustment for prior SARS-CoV-2 infection was performed in Ackerson (2024) and Kopel (2024) but not in Delaunay (2024)
Abbreviations: CI, confidence interval; IPTW, inverse probability of treatment weighting; IQR, interquartile range; rVE, relative vaccine effectiveness; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; VE, vaccine effectiveness
Information on prior vaccination history and hybrid immunity was variably reported across studies and was accounted for in adjusted analyses where available
Table 4.
Vaccine effectiveness against severe COVID-19 outcomes
| First author (year) | Subvariant | Vaccine status / comparatora | Severe outcomeb | VE % (95% CI) | Follow-up period |
|---|---|---|---|---|---|
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | Hospitalization | 71.3% (44.9–85.1) | 14–60 days |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. unvaccinated (VE) | Hospitalization | 76.9% (52.7–88.7) | 14–60 days |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | Hospitalization | 87.9% (43.8–97.4) | 14–60 days |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. unvaccinated (VE) | Hospitalization | 93.4% (68.6–98.6) | 14–60 days |
| Andersen (2025) [26] | XBB-lineage (XBB.1.5-dominant; emerging JN.1) | BNT162b2 XBB.1.5–adapted vaccine vs. no receipt of any XBB.1.5 vaccine (VE) | COVID-19–associated hospitalization | 36% (18–50) | Median 3.9 months (IQR 2.2–5.1) |
| Andersen (2025) [26] | XBB-lineage (XBB.1.5-dominant; emerging JN.1) | BNT162b2 XBB.1.5–adapted vaccine vs. no receipt of any XBB.1.5 vaccine (VE) | COVID-19–associated emergency department visit | 45% (34–54) | Median 3.9 months (IQR 2.2–5.1) |
| Andersson (2023) [4] | BA.4/BA.5-predominant period | Bivalent BA.4/BA.5 mRNA booster (fourth dose) vs. three-dose vaccinated (rVE) | COVID-19–related hospitalization | 67.8% (63.1–72.5) | Day 8–90 after vaccination |
| Andersson (2023) [4] | BA.4/BA.5-predominant period | Bivalent BA.1 mRNA booster (fourth dose) vs. three-dose vaccinated (rVE) | COVID-19–related hospitalization | 65.8% (59.1–72.4) | Day 8–90 after vaccination |
| Andersson (2023) [4] | BA.4/BA.5-predominant period | Bivalent BA.4/BA.5 mRNA booster (fourth dose) vs. three-dose vaccinated (rVE) | COVID-19–related death | 69.8% (52.8–86.8) | Day 8–90 after vaccination |
| Andersson (2023) [4] | BA.4/BA.5-predominant period | Bivalent BA.1 mRNA booster (fourth dose) vs. three-dose vaccinated (rVE) | COVID-19–related death | 70% (50.3–89.7) | Day 8–90 after vaccination |
| Andersson (2024) [5] | XBB lineage and JN.1-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. non-recipient (rVE) | COVID-19–related hospitalization | 57.9% (49.9–65.8) | Up to 24 weeks |
| Andersson (2024) [5] | XBB lineage and JN.1-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. non-recipient (rVE) | COVID-19–related death | 75.2% (70.6–79.9) | Up to 24 weeks |
| Andersson (2024) [5] | Any lineage (early season) | Monovalent XBB.1.5-adapted mRNA vaccine vs. non-recipient (rVE) | COVID-19–related hospitalization | 62.1% (51.5–72.7) | 6 weeks |
| Andersson (2024) [5] | Any lineage (early season) | Monovalent XBB.1.5-adapted mRNA vaccine vs. non-recipient (rVE) | COVID-19–related death | 79.8% (76.7–82.9) | 6 weeks |
| Antunes (2024) [28] | XBB.1.5-like lineage–predominant period, with subsequent JN.1 emergence | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. no vaccination during the 2023 autumn campaign (VE) | COVID-19–related hospitalization | 49% (37–58) | Overall study period (05 October 2023–14 January 2024) |
| Antunes (2025) [6] | JN.1–predominant period | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. no vaccination during the 2023/24 vaccination campaign (VE) | COVID-19–related hospitalization | 45% (29–58) | 14–59 days |
| Antunes (2025) [6] | JN.1–predominant period | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. no vaccination during the 2023/24 vaccination campaign (VE) | COVID-19–related hospitalization | 34% (18–47) | 60–119 days |
| Aziz (2025) [13] | XBB.1.5-predominant period (spring 2024) | Monovalent XBB.1.5-adapted mRNA vaccine vs. no vaccination in the spring 2024 campaign (VE) | COVID-19–related hospitalization | 45% (37–52) | 2–4 weeks |
| Aziz (2025) [13] | JN.1-predominant period (autumn 2024) | Monovalent JN.1-adapted mRNA vaccine vs. no vaccination in the autumn 2024 campaign (VE) | COVID-19–related hospitalization | 43% (34–51) | 10–14 weeks |
| Caffrey (2024) [29] | XBB-predominant period | BNT162b2 XBB.1.5-adapted vaccine vs. no XBB vaccine (VE) | COVID-19–related hospitalization | 62% (44–74) | ≤ 60 days since vaccination |
| Caffrey (2024) [29] | JN.1-predominant period | BNT162b2 XBB.1.5-adapted vaccine vs. no XBB vaccine (VE) | COVID-19–related hospitalization | 32% (3–52) | ≤ 60 days since vaccination |
| Carazo (2025) [14] | XBB/EG.5-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. prior monovalent or bivalent vaccination in 2022 (rVE) | COVID-19–related hospitalization | 54% (46–62) | Any time since vaccination (global estimate) |
| Carazo (2025) [14] | JN.1-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. prior monovalent or bivalent vaccination in 2022 (rVE) | COVID-19–related hospitalization | 23% (13–32) | Any time since vaccination (global estimate) |
| Carazo (2025) [14] | KP.2/KP.3-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. prior monovalent or bivalent vaccination in 2022 (rVE) | COVID-19–related hospitalization | 0% (− 18–15) | Any time since vaccination (global estimate) |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Moderna BA.1 bivalent vs. unvaccinated (VE) | Hospitalization or death | 86% (82–90) | 7–29 days |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Moderna BA.1 bivalent vs. unvaccinated (VE) | Hospitalization or death | 76% (66–83) | 90–119 days |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Pfizer-BioNTech BA.4/BA.5 bivalent vs. unvaccinated (VE) | Hospitalization or death | 83% (77–88) | 7–29 days |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Pfizer-BioNTech BA.4/BA.5 bivalent vs. unvaccinated (VE) | Hospitalization or death | 81% (72–87) | 60–89 days |
| Hansen (2025) [9] | Any lineage (JN.1-era) | BNT162b2 JN.1 vs. unvaccinated (VE) | Hospitalization | 70.2% (62–76.6) | 14–122 days |
| Hansen (2025) [9] | Any lineage (JN.1-era) | BNT162b2 JN.1 vs. unvaccinated (VE) | Death | 76.2% (63.4–84.5) | 14–122 days |
| Hansen (2025) [9] | Any lineage (JN.1-era) | mRNA-1273 JN.1 vs. unvaccinated (VE) | Hospitalization | 84.9% (70.9–92.2) | 14–122 days |
| Hansen (2025) [9] | Any lineage (JN.1-era) | mRNA-1273 JN.1 vs. unvaccinated (VE) | Death | 95.8% (69.2–99.4) | 14–122 days |
| Hansen (2025) [9] | KP.3.1.1 | BNT162b2 JN.1 vs. unvaccinated (VE) | Hospitalization | 71.7% (44.4–85.6) | 14–122 days |
| Hansen (2025) [9] | KP.3.1.1 | BNT162b2 JN.1 vs. unvaccinated (VE) | Death | 90.9% (67.4–97.5) | 14–122 days |
| Hansen (2025) [9] | XEC | BNT162b2 JN.1 vs. unvaccinated (VE) | Hospitalization | 76.8% (59–86.9) | 14–122 days |
| Hansen (2025) [9] | XEC | BNT162b2 JN.1 vs. unvaccinated (VE) | Death | 76.3% (24.7–92.6) | 14–122 days |
| Humphreys (2025) [7] | JN.1-predominant period (autumn 2024/25 campaign) | Monovalent JN.1-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization (65–79 years) | 60% (48–70) | ≥ 14 days post-vaccination (overall) |
| Humphreys (2025) [7] | JN.1-predominant period (autumn 2024/25 campaign) | Monovalent JN.1-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization (≥ 80 years) | 58% (48–66) | ≥ 14 days post-vaccination (overall) |
| Humphreys (2025) [7] | JN.1-predominant period (autumn 2024/25 campaign) | Monovalent JN.1-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related death (65–79 years) | 78% (64–87) | ≥ 14 days post-vaccination (overall) |
| Humphreys (2025) [7] | JN.1-predominant period (autumn 2024/25 campaign) | Monovalent JN.1-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related death (≥ 80 years) | 62% (32–79) | ≥ 14 days post-vaccination (overall) |
| Humphreys (2025) [15] | JN.1 with KP sublineages (KP.2, KP.3) | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization (65–79 years) | 13% (− 12–33) | June–August 2024 (≥ 6 months post vaccination) |
| Humphreys (2025) [15] | JN.1 with KP sublineages (KP.2, KP.3) | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization (≥ 80 years) | 7% (− 7–19) | June–August 2024 (≥ 6 months post vaccination) |
| Humphreys (2025) [15] | JN.1 with KP sublineages (KP.2, KP.3) | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related death (65–79 years) | 39% (− 7–65) | June–August 2024 (≥ 6 months post vaccination) |
| Humphreys (2025) [15] | JN.1 with KP sublineages (KP.2, KP.3) | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related death (≥ 80 years) | 3% (− 23–23) | June–August 2024 (≥ 6 months post vaccination) |
| Kirsebom (2024) [17] | XBB-related sub-lineages (autumn 2023 period) | Monovalent XBB.1.5-adapted mRNA vaccine vs. not boosted / prior doses waned (VE) | COVID-19–related hospitalization | 50.6% (44.2–56.3) | 2–4 weeks |
| Kirsebom (2024) [17] | EG.5.1-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. not boosted / prior doses waned (VE) | COVID-19–related hospitalization | 44.5% (20.2–61.4) | 2–4 weeks |
| Kirsebom (2024) [17] | JN.1-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. not boosted / prior doses waned (VE) | COVID-19–related hospitalization | 26.4% (− 3.4–47.6) | 5–9 weeks |
| Kopel (2024) [31] | XBB-lineage (XBB.1.5-dominant; emerging JN.1) | mRNA-1273.815 (XBB.1.5-adapted) vs. no 2023–2024 updated vaccine (VE) | COVID-19–related hospitalization | 60.2% (53.4–66) | Median 63 days (IQR 44–78) |
| Lee (2024) [32] | XBB-lineage (EG.5; HK.3; emerging JN.1) | XBB.1.5-adapted mRNA vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization | 77.3% (51.1–89.5) | Median 33 days (IQR 19.5–47) |
| Lee (2024) [32] | XBB-lineage (EG.5; HK.3; emerging JN.1) | XBB.1.5-adapted mRNA vaccine vs. unvaccinated (VE) | Receipt of oxygen therapy | 85.3% (57.8–94.9) | Median 33 days (IQR 19.5–47) |
| Lee (2024) [32] | XBB-lineage (EG.5; HK.3; emerging JN.1) | XBB.1.5-adapted mRNA vaccine vs. no XBB.1.5 vaccination (rVE) | COVID-19–related hospitalization | 64.3% (35.9–80.2) | Median 33 days (IQR 19.5–47) |
| Lee (2024) [32] | XBB-lineage (EG.5; HK.3; emerging JN.1) | XBB.1.5-adapted mRNA vaccine vs. no XBB.1.5 vaccination (rVE) | Receipt of oxygen therapy | 65.5% (27–83.7) | Median 33 days (IQR 19.5–47) |
| Lee (2025) [16] | XBB-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. ≥ 2 doses of non-XBB.1.5 vaccines (rVE) | Hospitalization or death | 64% (57–69) | 0–<3 months since vaccination |
| Lee (2025) [16] | JN/KP-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. ≥ 2 doses of non-XBB.1.5 vaccines (rVE) | Hospitalization or death | 57% (48–64) | 0–<3 months since vaccination |
| Link-Gelles (2025) [10] | XBB-predominant period | 2023–2024 monovalent XBB.1.5 vaccine vs. no 2023–2024 COVID-19 vaccine (VE) | COVID-19–associated hospitalization | 54% (48–59) | 7–93 days |
| Link-Gelles (2025) [10] | JN.1-predominant period | 2023–2024 monovalent XBB.1.5 vaccine vs. no 2023–2024 COVID-19 vaccine (VE) | COVID-19–associated hospitalization | 41% (34–47) | 7–93 days |
| Link-Gelles (2025) [10] | XBB-predominant period | 2023–2024 monovalent XBB.1.5 vaccine vs. no 2023–2024 COVID-19 vaccine (VE) | COVID-19–associated critical illness (ICU admission or in-hospital death) | 73% (61–82) | 7–93 days |
| Link-Gelles (2025) [10] | JN.1-predominant period | 2023–2024 monovalent XBB.1.5 vaccine vs. no 2023–2024 COVID-19 vaccine (VE) | COVID-19–associated critical illness (ICU admission or in-hospital death) | 54% (40–65) | 7–93 days |
| Monge (2024) [34] | XBB.1.5-dominant period | Monovalent XBB.1.5 COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization | 67% (58–74) | October–November 2023 |
| Monge (2024) [34] | XBB.1.5-dominant period | Monovalent XBB.1.5 COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related death | 67% (42–81) | October–November 2023 |
| Monge (2024) [34] | XBB.1.5-dominant period | Monovalent XBB.1.5 COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization (65–79 years) | 67% (58–74) | October–November 2023 |
| Monge (2024) [34] | XBB.1.5-dominant period | Monovalent XBB.1.5 COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization (≥ 80 years) | 66% (57–73) | October–November 2023 |
| Monge (2024) [34] | XBB.1.5-dominant period | Monovalent XBB.1.5 COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related death (65–79 years) | 67% (42–81) | October–November 2023 |
| Monge (2024) [34] | XBB.1.5-dominant period | Monovalent XBB.1.5 COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related death (≥ 80 years) | 72% (51–85) | October–November 2023 |
| Nguyen (2025) [35] | JN.1-predominant period | BNT162b2 XBB.1.5-adapted vs. no COVID-19 vaccination in 2023–2024 season (VE) | COVID-19–related hospitalization (SARI) | 53.8% (38.4–65.4) | Median 63 days (IQR 48–79) |
| Nham (2025) [36] | XBB-lineage (EG.5; HK.3) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization | 74% (40.7–78.6) | November–December 2023c |
| Nham (2025) [36] | XBB-lineage / emerging JN.1 (HK.3; JN.1) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization | 34.2% (− 6.8–46.4) | January–April 2024c |
| Nham (2025) [36] | KP.2 / KP.3 | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization | 26.1% (4.7–42.8) | July–August 2024c |
| Nunes (2024) [18] | JN.1–predominant period | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization (65–79 years) | 50% (45–55) | JN.1 predominance period (December 2023 – February 2024)ᶜ |
| Nunes (2024) [18] | JN.1–predominant period | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization (≥ 80 years) | 41% (35–46) | JN.1 predominance period (December 2023 – February 2024)ᶜ |
| Nunes (2024) [18] | JN.1–predominant period | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | COVID-19–related death (65–79 years) | 58% (42–69) | JN.1 predominance period (December 2023 – February 2024)ᶜ |
| Nunes (2024) [18] | JN.1–predominant period | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | COVID-19–related death (≥ 80 years) | 48% (38–57) | JN.1 predominance period (December 2023 – February 2024)ᶜ |
| Rojas-Benedicto (2025) [37] | XBB.1.5-predominant period | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization | 73% (41–89) | Winter wave (October–November 2023) |
| Rojas-Benedicto (2025) [37] | JN.1-predominant period | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization | 34% (17–48) | Winter wave (December 2023 – January 2024) |
| Rojas-Benedicto (2025) [37] | JN.1-predominant period | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization | 8% (− 20–30) | Summer wave (May–June 2024) |
| Rojas-Benedicto (2025) [37] | KP.3-predominant period | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | COVID-19–related hospitalization | −3% (− 35–21) | Summer wave (June–July 2024) |
| Tartof (2024) [38] | XBB-predominant period (JN.1 emerging) | BNT162b2 XBB vaccine vs. no XBB vaccine of any kind (VE) | COVID-19–associated hospitalization | 62% (32–79) | Median 34 days since vaccination |
| Tartof (2024) [38] | XBB-predominant period (JN.1 emerging) | BNT162b2 XBB vaccine vs. no XBB vaccine of any kind (VE) | COVID-19–associated ED/UC encounter | 58% (48–67) | Median 34 days since vaccination |
| Tartof (2024) [39] | XBB sublineages | Monovalent BNT162b2 XBB.1.5-adapted mRNA vaccine vs. no XBB vaccine | COVID-19–related hospitalization | 65% (41–79) | 10 October 2023–29 February 2024 |
| Tartof (2024) [39] | JN.1 sublineages | Monovalent BNT162b2 XBB.1.5-adapted mRNA vaccine vs. no XBB vaccine | COVID-19–related hospitalization | 54% (33–69) | 10 October 2023–29 February 2024 |
| Tartof (2024) [39] | XBB sublineages | Monovalent BNT162b2 XBB.1.5-adapted mRNA vaccine vs. no XBB vaccine | ED/UC visit | 55% (45–64) | 10 October 2023–29 February 2024 |
| Tartof (2024) [39] | JN.1 sublineages | Monovalent BNT162b2 XBB.1.5-adapted mRNA vaccine vs. no XBB vaccine | ED/UC visit | 41% (32–49) | 10 October 2023–29 February 2024 |
| van Werkhoven (2024) [40] | XBB-predominant period (XBB.1.5) | Monovalent XBB.1.5-adapted mRNA vaccine (BNT162b2) vs. no 2023 seasonal XBB.1.5 vaccine | COVID-19–related hospitalization | 70.7% (66.6–74.3) | 9 October 2023–5 December 2023 |
| van Werkhoven (2024) [40] | XBB-predominant period (XBB.1.5) | Monovalent XBB.1.5-adapted mRNA vaccine (BNT162b2) vs. no 2023 seasonal XBB.1.5 vaccine | ICU admission | 73.3% (42.2–87.6) | 9 October 2023–5 December 2023 |
| Wilson (2025) [41] | XBB-predominant period (XBB.1.5; overlap with early JN.1 emergence) | Monovalent XBB.1.5-containing mRNA vaccine (mRNA-1273.815) vs. no 2023–2024 COVID-19 vaccine | COVID-19–related hospitalization | 51% (48–54) | September 2023 – January 2024 |
aVE denotes absolute vaccine effectiveness compared with unvaccinated individuals; rVE denotes relative vaccine effectiveness compared with ≥ 2 doses of monovalent mRNA vaccines
bSevere outcomes included COVID-19–related hospitalization, emergency department or urgent care encounters, and death, defined according to study-specific criteria. Hospitalization generally required inpatient admission for COVID-19–associated illness; emergency department or urgent care encounters reflected medically attended COVID-19 without inpatient admission; and death was defined as COVID-19–related death or death occurring within a specified period after laboratory-confirmed SARS-CoV-2 infection. Estimates were adjusted for demographic and clinical covariates, with adjustment for prior infection varying by study
cFor studies in which vaccine effectiveness against hospitalization or medically attended severe outcomes was reported by dominant Omicron subvariant period rather than by time since vaccination, the corresponding study period is shown in the follow-up column
Abbreviations: CI, confidence interval; ED, emergency department; ICU, intensive care unit; IQR, interquartile range; rVE, relative vaccine effectiveness; SARI, severe acute respiratory infection; UC, urgent care; VE, vaccine effectiveness
Information on prior vaccination history and hybrid immunity was variably reported across studies and was accounted for in adjusted analyses where available
Table 5.
Effect of time since vaccination (waning immunity)
| First author (year) | Subvariant | Vaccine status / comparatora | Time since vaccination | VE % (95% CI) |
|---|---|---|---|---|
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | 14–60 days | 52.7% (46.9–57.8) |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | 61–120 days | 39.4% (30.1–47.5) |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | 121–180 days | 35.5% (− 2.8–59.5) |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | 14–60 days | 48.8% (33.4–60.7) |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | 61–120 days | 26% (12.1–37.7) |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | 121–180 days | −3.9% (− 18.1–11.3) |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. ≥ 2 monovalent mRNA (rVE) | > 180 days | −18.3% (− 31.3–−2.9) |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. unvaccinated (VE) | 14–60 days | 29.3% (19.1–38.2) |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. unvaccinated (VE) | 61–120 days | 2.8% (− 12.5–17.4) |
| Ackerson (2024) [3] | BA.4/BA.5 | Bivalent mRNA-1273 vs. unvaccinated (VE) | 121–180 days | −8.8% (− 44.3–33) |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. unvaccinated (VE) | 14–60 days | 21.2% (− 4.6–40.7) |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. unvaccinated (VE) | 61–120 days | −13.4% (− 28.9–5.2) |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. unvaccinated (VE) | 121–180 days | −30% (− 42–−15.5) |
| Ackerson (2024) [3] | XBB | Bivalent mRNA-1273 vs. unvaccinated (VE) | > 180 days | −48.7% (− 58.4–−36.6) |
| Andersson (2023) [4] | BA.4/BA.5-predominant period | Bivalent BA.4/BA.5 mRNA booster vs. three-dose vaccinated (rVE) | Day 8–90 | 67.8% (63.1–72.5) |
| Andersson (2023) [4] | BA.4/BA.5-predominant period | Bivalent BA.4/BA.5 mRNA booster vs. three-dose vaccinated (rVE) | Up to 180 days | 54.9% (49–60.8) |
| Andersson (2023) [4] | BA.4/BA.5-predominant period | Bivalent BA.1 mRNA booster vs. three-dose vaccinated (rVE) | Day 8–90 | 65.8% (59.1–72.4) |
| Andersson (2023) [4] | BA.4/BA.5-predominant period | Bivalent BA.1 mRNA booster vs. three-dose vaccinated (rVE) | Up to 180 days | 63.5% (49.5–77.5) |
| Andersson (2024) [5] | XBB lineage, followed by a JN.1-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. non-recipient (rVE) | 6 weeks | 62.1% (51.5–72.7) |
| Andersson (2024) [5] | XBB lineage, followed by a JN.1-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. non-recipient (rVE) | 24 weeks | 57.9% (49.9–65.8) |
| Antunes (2024) [27] | XBB-lineage–predominant period (XBB, XBB.1.5, XBB.1.5 + F456L) | Adapted bivalent mRNA vaccine vs. monovalent vaccination ≥ 6 months before campaign (rVE) | 14–89 days | 80% (50–94) |
| Antunes (2024) [27] | XBB-lineage–predominant period (XBB, XBB.1.5, XBB.1.5 + F456L) | Adapted bivalent mRNA vaccine vs. monovalent vaccination ≥ 6 months before campaign (rVE) | 90–179 days | 15% (− 12–35) |
| Antunes (2024) [27] | XBB-lineage–predominant period (XBB, XBB.1.5, XBB.1.5 + F456L) | Adapted bivalent mRNA vaccine vs. monovalent vaccination ≥ 6 months before campaign (rVE) | 180–269 days | 8% (− 19–28) |
| Antunes (2024) [27] | XBB-lineage–predominant period (XBB, XBB.1.5, XBB.1.5 + F456L) | Adapted bivalent mRNA vaccine vs. monovalent vaccination ≥ 6 months before campaign (rVE) | 270–359 days | 0% (− 47–31) |
| Antunes (2024) [28] | XBB.1.5-like lineage–predominant period, with subsequent JN.1 emergence | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. no vaccination during the 2023 autumn campaign (VE) | 14–29 days | 69% (50–82) |
| Antunes (2024) [28] | XBB.1.5-like lineage–predominant period, with subsequent JN.1 emergence | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. no vaccination during the 2023 autumn campaign (VE) | 30–59 days | 46% (29–59) |
| Antunes (2024) [28] | XBB.1.5-like lineage–predominant period, with subsequent JN.1 emergence | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. no vaccination during the 2023 autumn campaign (VE) | 60–105 days | 40% (19–55) |
| Antunes (2025) [6] | JN.1–predominant period | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. no vaccination during the 2023/24 vaccination campaign (VE) | 14–59 days | 45% (29–58) |
| Antunes (2025) [6] | JN.1–predominant period | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. no vaccination during the 2023/24 vaccination campaign (VE) | 60–119 days | 34% (18–47) |
| Antunes (2025) [6] | JN.1–predominant period | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. no vaccination during the 2023/24 vaccination campaign (VE) | ≥ 120 days | −10% (− 58–24) |
| Aziz (2025) [13] | XBB.1.5-predominant period (spring 2024) | Monovalent XBB.1.5-adapted mRNA vaccine vs. no vaccination during the spring 2024 campaign (VE) | 2–4 weeks | 45% (37–52) |
| Aziz (2025) [13] | XBB.1.5-predominant period (spring 2024) | Monovalent XBB.1.5-adapted mRNA vaccine vs. no vaccination during the spring 2024 campaign (VE) | 25–29 weeks | 6% (− 11–21) |
| Aziz (2025) [13] | JN.1-predominant period (autumn 2024) | Monovalent JN.1-adapted mRNA vaccine vs. no vaccination during the autumn 2024 campaign (VE) | 10–14 weeks | 43% (34–51) |
| Aziz (2025) [13] | JN.1-predominant period (autumn 2024) | Monovalent JN.1-adapted mRNA vaccine vs. no vaccination during the autumn 2024 campaign (VE) | ≥ 20 weeks | 34% (22–44) |
| Caffrey (2024) [29] | Likely XBB-predominant period | BNT162b2 XBB.1.5-adapted vaccine vs. no XBB vaccine (VE) | ≤ 60 days | 62% (44–74) |
| Caffrey (2024) [29] | Likely JN.1-predominant period | BNT162b2 XBB.1.5-adapted vaccine vs. no XBB vaccine (VE) | ≤ 60 days | 32% (3–52) |
| Caffrey (2024) [29] | Likely JN.1-predominant period | BNT162b2 XBB.1.5-adapted vaccine vs. no XBB vaccine (VE) | 61–133 days | 37% (19–51) |
| Carazo (2025) [14] | XBB/EG.5-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. prior monovalent or bivalent vaccination in 2022 (rVE) | 1–2 months | 55% (46–62) |
| Carazo (2025) [14] | JN.1-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. prior monovalent or bivalent vaccination in 2022 (rVE) | 1–2 months | 23% (9–36) |
| Carazo (2025) [14] | JN.1-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. prior monovalent or bivalent vaccination in 2022 (rVE) | 3–4 months | 18% (− 9–36) |
| Carazo (2025) [14] | KP.2/KP.3-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. prior monovalent or bivalent vaccination in 2022 (rVE) | 1–2 months | 60% (39–74) |
| Carazo (2025) [14] | KP.2/KP.3-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. prior monovalent or bivalent vaccination in 2022 (rVE) | 7–8 months | 3% (− 18–21) |
| Delaunay (2024) [30] | Any SARS-CoV-2 (XBB-dominant period) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | < 6 weeks | 48% (31–61) |
| Delaunay (2024) [30] | Any SARS-CoV-2 (XBB-dominant period) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | 6–14 weeks | 29% (3–49) |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Moderna BA.1 bivalent vs. unvaccinated (VE) | 7–29 days | 86% (82–90) |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Moderna BA.1 bivalent vs. unvaccinated (VE) | 30–59 days | 91% (88–93) |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Moderna BA.1 bivalent vs. unvaccinated (VE) | 60–89 days | 86% (80–89) |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Moderna BA.1 bivalent vs. unvaccinated (VE) | 90–119 days | 76% (66–83) |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Pfizer-BioNTech BA.4/BA.5 bivalent vs. unvaccinated (VE) | 7–29 days | 83% (77–88) |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Pfizer-BioNTech BA.4/BA.5 bivalent vs. unvaccinated (VE) | 30–59 days | 83% (77–87) |
| Grewal (2024) [8] | BA.4/BA.5– and BQ-dominant periods | Pfizer-BioNTech BA.4/BA.5 bivalent vs. unvaccinated (VE) | 60–89 days | 81% (72–87) |
| Hansen (2025) [9] | Any lineage (JN.1-era) | BNT162b2 JN.1 vs. unvaccinated (VE) | 14–30 days | 67.4% (54–76.9) |
| Hansen (2025) [9] | Any lineage (JN.1-era) | BNT162b2 JN.1 vs. unvaccinated (VE) | 31–60 days | 71.7% (60.9–79.5) |
| Hansen (2025) [9] | Any lineage (JN.1-era) | BNT162b2 JN.1 vs. unvaccinated (VE) | 61–90 days | 74.7% (63.5–82.5) |
| Hansen (2025) [9] | Any lineage (JN.1-era) | BNT162b2 JN.1 vs. unvaccinated (VE) | ≥ 91 days | 61.1% (33.7–77.2) |
| Hansen (2025) [9] | KP.3.1.1 | BNT162b2 JN.1 vs. unvaccinated (VE) | 14–30 days | 71.6% (34.1–87.7) |
| Hansen (2025) [9] | KP.3.1.1 | BNT162b2 JN.1 vs. unvaccinated (VE) | 31–60 days | 68.8% (16.6–88.3) |
| Hansen (2025) [9] | KP.3.1.1 | BNT162b2 JN.1 vs. unvaccinated (VE) | 61–90 days | 74.4% (17.2–92.1) |
| Hansen (2025) [9] | XEC | BNT162b2 JN.1 vs. unvaccinated (VE) | 14–30 days | 73.8% (35.4–89.4) |
| Hansen (2025) [9] | XEC | BNT162b2 JN.1 vs. unvaccinated (VE) | 31–60 days | 77.7% (53.3–89.3) |
| Hansen (2025) [9] | XEC | BNT162b2 JN.1 vs. unvaccinated (VE) | 61–90 days | 82.3% (58–92.5) |
| Hansen (2025) [9] | XEC | BNT162b2 JN.1 vs. unvaccinated (VE) | ≥ 91 days | 63.4% (–20.5–88.9) |
| Humphreys (2025) [7] | JN.1-predominant period (autumn 2024/25 campaign) | Monovalent JN.1-adapted COVID-19 vaccine vs. unvaccinated (VE) | 14–59 days | 59% (51–66) |
| Humphreys (2025) [7] | JN.1-predominant period (autumn 2024/25 campaign) | Monovalent JN.1-adapted COVID-19 vaccine vs. unvaccinated (VE) | 60–119 days | 59% (− 13–85) |
| Humphreys (2025) [15] | JN.1 with KP sublineages (KP.2, KP.3) | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | 90–179 days | 16% (− 52–54) |
| Humphreys (2025) [15] | JN.1 with KP sublineages (KP.2, KP.3) | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | ≥ 180 days | 13% (− 12–33) |
| Humphreys (2025) [15] | JN.1 with KP sublineages (KP.2, KP.3) | Monovalent XBB.1.5-adapted COVID-19 vaccine vs. unvaccinated (VE) | ≥ 180 days | 39% (− 7–65) |
| Kirsebom (2024) [17] | XBB-related sub-lineages | Monovalent XBB.1.5-adapted mRNA vaccine vs. not boosted / prior doses waned (VE) | 2–4 weeks | 50.6% (44.2–56.3) |
| Kirsebom (2024) [17] | XBB-related sub-lineages | Monovalent XBB.1.5-adapted mRNA vaccine vs. not boosted / prior doses waned (VE) | 5–9 weeks | 45.7% (39.4–51.3) |
| Kirsebom (2024) [17] | XBB-related sub-lineages | Monovalent XBB.1.5-adapted mRNA vaccine vs. not boosted / prior doses waned (VE) | 10–14 weeks | 36.5% (28.8–43.4) |
| Kirsebom (2024) [17] | XBB-related sub-lineages | Monovalent XBB.1.5-adapted mRNA vaccine vs. not boosted / prior doses waned (VE) | ≥ 15 weeks | 13.6% (− 11.7–33.2) |
| Lee (2025) [16] | XBB-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. ≥ 2 doses of non-XBB.1.5 vaccines (rVE) | 0–<3 months | 64% (57–69) |
| Lee (2025) [16] | JN/KP-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. ≥ 2 doses of non-XBB.1.5 vaccines (rVE) | 0–<3 months | 57% (48–64) |
| Lee (2025) [16] | JN/KP-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. ≥ 2 doses of non-XBB.1.5 vaccines (rVE) | 3–<6 months | 44% (32–54) |
| Lee (2025) [16] | JN/KP-predominant period | Monovalent XBB.1.5-adapted mRNA vaccine vs. ≥ 2 doses of non-XBB.1.5 vaccines (rVE) | 6–<9 months | 21% (− 15–46) |
| Link-Gelles (2025) [10] | XBB-predominant period | 2023–2024 monovalent XBB.1.5 vaccine vs. no 2023–2024 COVID-19 vaccine (VE) | 7–59 days | 54% (48–59) |
| Link-Gelles (2025) [10] | JN.1-predominant period | 2023–2024 monovalent XBB.1.5 vaccine vs. no 2023–2024 COVID-19 vaccine (VE) | 7–59 days | 41% (34–47) |
| Link-Gelles (2025) [10] | JN.1-predominant period | 2023–2024 monovalent XBB.1.5 vaccine vs. no 2023–2024 COVID-19 vaccine (VE) | 60–119 days | 36% (30–42) |
| Link-Gelles (2025) [10] | JN.1-predominant period | 2023–2024 monovalent XBB.1.5 vaccine vs. no 2023–2024 COVID-19 vaccine (VE) | 180–299 days | −4% (− 14–5) |
| Ma (2024) [33] | XBB lineages | Updated 2023–2024 monovalent XBB.1.5 vaccine vs. no updated dose | 7–89 days | 54.2% (36.1–67.1) |
| Ma (2024) [33] | JN.1 lineages | Updated 2023–2024 monovalent XBB.1.5 vaccine vs. no updated dose | 7–89 days | 32.7% (1.9–53.8) |
| Ma (2024) [33] | JN.1 lineages | Updated 2023–2024 monovalent XBB.1.5 vaccine vs. no updated dose | 90–179 days | 23.4% (− 11.8–47.6) |
| Nguyen (2025) [35] | JN.1-predominant period | BNT162b2 XBB.1.5 vs. no vaccination this season (VE) | 2 to < 4 weeks | 52.2% (41.3–61.1) |
| Nguyen (2025) [35] | JN.1-predominant period | BNT162b2 XBB.1.5 vs. no vaccination this season (VE) | 4 to < 8 weeks | 48.9% (17.9–68.2) |
| Nguyen (2025) [35] | JN.1-predominant period | BNT162b2 XBB.1.5 vs. no vaccination this season (VE) | 8 to < 12 weeks | 56.9% (39.5–69.2) |
| Nguyen (2025) [35] | JN.1-predominant period | BNT162b2 XBB.1.5 vs. no vaccination this season (VE) | 12 to < 16 weeks | 54.6% (50.2–58.5) |
| Nguyen (2025) [35] | JN.1-predominant period | BNT162b2 XBB.1.5 vs. no vaccination this season (VE) | 16 to < 22 weeks | 59.5% (21.4–79.1) |
| Nham (2025) [36] | XBB-lineage (EG.5; HK.3) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | November–December 2023 | 57.1% (38–70.6) |
| Nham (2025) [36] | XBB-lineage / emerging JN.1 (HK.3; JN.1) | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | January–April 2024 | 18.8% (− 4.7–37.2) |
| Nham (2025) [36] | KP.2 / KP.3 | XBB.1.5-adapted vaccine vs. unvaccinated (VE) | July–August 2024 | 3.3% (− 15.4–19.1) |
| Tartof (2024) [39] | XBB sublineages | Monovalent BNT162b2 XBB.1.5-adapted mRNA vaccine vs. no XBB vaccine | < 60 days | 74% (49–87) |
| Tartof (2024) [39] | XBB sublineages | Monovalent BNT162b2 XBB.1.5-adapted mRNA vaccine vs. no XBB vaccine | 60–128 days | 39% (10–59) |
| Tartof (2024) [39] | JN.1 sublineages | Monovalent BNT162b2 XBB.1.5-adapted mRNA vaccine vs. no XBB vaccine | < 60 days | 50% (15–71) |
| Tartof (2024) [39] | JN.1 sublineages | Monovalent BNT162b2 XBB.1.5-adapted mRNA vaccine vs. no XBB vaccine | 60–156 days | 57% (30–73) |
| Wilson (2025) [41] | XBB-predominant period (XBB.1.5; overlap with early JN.1 emergence) | Monovalent XBB.1.5-containing mRNA vaccine (mRNA-1273.815) vs. no 2023–2024 COVID-19 vaccine | ≤ 58 days | 52% (49–55) |
| Wilson (2025) [41] | XBB-predominant period (XBB.1.5; overlap with early JN.1 emergence) | Monovalent XBB.1.5-containing mRNA vaccine (mRNA-1273.815) vs. no 2023–2024 COVID-19 vaccine | 59–84 days | 41% (NR) |
| Wilson (2025) [41] | XBB-predominant period (XBB.1.5; overlap with early JN.1 emergence) | Monovalent XBB.1.5-containing mRNA vaccine (mRNA-1273.815) vs. no 2023–2024 COVID-19 vaccine | 85–101 days | 29% (NR) |
| Wilson (2025) [41] | XBB-predominant period (XBB.1.5; overlap with early JN.1 emergence) | Monovalent XBB.1.5-containing mRNA vaccine (mRNA-1273.815) vs. no 2023–2024 COVID-19 vaccine | ≥ 102 days | 32% (5–52) |
aVE denotes absolute vaccine effectiveness compared with unvaccinated individuals; rVE denotes relative vaccine effectiveness compared with ≥ 2 doses of monovalent mRNA vaccines. Unless otherwise specified, VE estimates reflect COVID-19–related hospitalization. Studies reporting VE against SARS-CoV-2 infection are Ackerson (2024), Delaunay (2024), and Nham (2025), as defined in the original publications. Waning estimates reflect time since last vaccine dose or, where reported, dominant Omicron subvariant period. For some studies, point estimates are reported without numerical 95% confidence intervals (NR), as these were not provided in the original publications
Abbreviations: CI, confidence interval; NR, not reported; rVE, relative vaccine effectiveness; VE, vaccine effectiveness
Information on prior vaccination history and hybrid immunity was variably reported across studies and was accounted for in adjusted analyses where available
During BA.4/BA.5-predominant periods, bivalent BA.4/BA.5 mRNA vaccines demonstrated moderate short-term protection against infection, which declined substantially within three to six months. During XBB-dominant periods, both absolute and relative vaccine effectiveness against infection were generally lower and declined rapidly, with several studies reporting minimal or negative effectiveness beyond 3–6 months after vaccination.
Effectiveness against infection during JN.1 and KP lineage–predominant periods was limited, with point estimates frequently close to zero and wide confidence intervals, reflecting immune escape and limited durability of protection against infection.
Vaccine effectiveness against severe COVID-19 outcomes
This section presents vaccine effectiveness estimates against severe COVID-19 outcomes, including hospitalization, critical illness, and death, across successive Omicron subvariant periods. Vaccine effectiveness against severe COVID-19 outcomes is summarised in Table 4. Across all Omicron subvariant periods, vaccines consistently provided substantial protection against hospitalization, critical illness, and death, although effectiveness varied by subvariant and time since vaccination.
During BA.4/BA.5-predominant periods, bivalent mRNA vaccines were associated with high effectiveness against COVID-19–related hospitalization and death, particularly within the first three months following vaccination. During XBB-dominant periods, monovalent XBB.1.5-adapted vaccines retained moderate to high effectiveness against hospitalization and critical illness, with generally higher protection against death than against hospital admission.
During JN.1-predominant periods, vaccine effectiveness against severe outcomes remained evident but was attenuated compared with earlier Omicron phases. Several large registry-based studies nonetheless demonstrated substantial protection against hospitalization and death, particularly among older adults and within the early months after vaccination.
Waning immunity over time
This section examines the durability of vaccine-induced protection over time, with a focus on waning effectiveness by vaccine formulation, Omicron subvariant, and time since vaccination. Waning of vaccine effectiveness over time is detailed in Table 5. Across vaccine formulations and Omicron subvariants, effectiveness against SARS-CoV-2 infection declined rapidly, often within weeks to a few months after vaccination. In contrast, protection against severe COVID-19 outcomes waned more gradually, with clinically relevant effectiveness generally preserved for several months.
For XBB.1.5-adapted vaccines, effectiveness against hospitalization was highest within the first 1–3 months after vaccination and declined thereafter, with some studies reporting markedly reduced or non-significant protection beyond 6 months, particularly during periods dominated by JN.1 or KP sublineages.
Subgroup analyses
This section reports subgroup-specific vaccine effectiveness estimates, including analyses stratified by age group, Omicron subvariant, and clinical outcome severity, where data were available. Subgroup analyses are presented in Table 6. Most studies reported higher vaccine effectiveness against severe outcomes among older adults, particularly those aged 65–79 years, compared with younger adults. Protection against death was consistently higher than protection against hospitalization across age groups.
Table 6.
Subgroup analyses
| First author (year) | Subgroup | Subvariant | Outcome | VE % (95% CI)a |
|---|---|---|---|---|
| Ackerson (2024) [3] | ≥ 65 years | BA.4/BA.5 | Hospitalization | 68.1% (44.1–81.8) |
| Ackerson (2024) [3] | ≥ 65 years | XBB | Hospitalization | 53.8% (25.2–71.5) |
| Ackerson (2024) [3] | ≥ 65 years | BA.4/BA.5 | Hospitalization (rVE) | 71% (53.7–81.9) |
| Ackerson (2024) [3] | ≥ 65 years | XBB | Hospitalization (rVE) | 53.8% (25.2–71.5) |
| Andersen (2025) [26] | ≥ 65 years | XBB-lineage (XBB.1.5-dominant; emerging JN.1) | COVID-19–associated hospitalization | 47% (28–61) |
| Andersen (2025) [26] | ≥ 65 years | XBB-lineage (XBB.1.5-dominant; emerging JN.1) | COVID-19–associated emergency department visit | 48% (33–60) |
| Andersson (2023) [4] | ≥ 70 years | BA.4/BA.5-predominant period | COVID-19–related hospitalization | 67.4% (61.8–73.1) |
| Andersson (2023) [4] | ≥ 70 years | BA.4/BA.5-predominant period | COVID-19–related death | 74.4% (58.4–90.3) |
| Andersson (2024) [5] | ≥ 75 years | XBB lineage, followed by a JN.1–predominant period | COVID-19–related hospitalization | 57.6% (47.8–67.5) |
| Andersson (2024) [5] | ≥ 75 years | XBB lineage, followed by a JN.1–predominant period | COVID-19–related death | 76% (70.4–81.5) |
| Antunes (2024) [28] | ≥ 65 years | XBB.1.5-like lineage–predominant period, with subsequent JN.1 emergence | COVID-19–related hospitalization | 50% (38–60) |
| Antunes (2024) [28] | ≥ 80 years | XBB.1.5-like lineage–predominant period, with subsequent JN.1 emergence | COVID-19–related hospitalization | 52% (36–64) |
| Antunes (2025) [6] | 65–79 years | JN.1–predominant period | COVID-19–related hospitalization | 47% (22–65) |
| Antunes (2025) [6] | ≥ 80 years | JN.1–predominant period | COVID-19–related hospitalization | 45% (22–61) |
| Caffrey (2024) [29] | ≥ 65 years | XBB/JN.1 period (overall) | COVID-19–related hospitalization | 41% (32–50) |
| Caffrey (2024) [29] | < 65 years | XBB/JN.1 period (overall) | COVID-19–related hospitalization | 58% (33–73) |
| Carazo (2025) [14] | 70–79 years | XBB/EG.5-predominant period | COVID-19–related hospitalization | 56.1% (40.6–67.6) |
| Carazo (2025) [14] | ≥ 80 years | XBB/EG.5-predominant period | COVID-19–related hospitalization | 54.9% (43.3–64.1) |
| Hansen 2025 [9] | ≥ 65 years | Any lineage (JN.1-era) | Hospitalization | 70.2% (62–76.6) |
| Hansen 2025 [9] | ≥ 65 years | Any lineage (JN.1-era) | Death | 76.2% (63.4–84.5) |
| Hansen 2025 [9] | ≥ 65 years | KP.3.1.1 | Hospitalization | 71.7% (44.4–85.6) |
| Hansen 2025 [9] | ≥ 65 years | KP.3.1.1 | Death | 90.9% (67.4–97.5) |
| Hansen 2025 [9] | ≥ 65 years | XEC | Hospitalization | 76.8% (59–86.9) |
| Hansen 2025 [9] | ≥ 65 years | XEC | Death | 76.3% (24.7–92.6) |
| Hansen 2025 [9] | ≥ 65 years – BNT162b2 JN.1 | Any lineage | Hospitalization | 70.2% (62–76.6) |
| Hansen (2025) [9] | ≥ 65 years – BNT162b2 JN.1 | Any lineage | Death | 76.2% (63.4–84.5) |
| Hansen (2025) [9] | ≥ 65 years – mRNA-1273 JN.1 | Any lineage | Hospitalization | 84.9% (70.9–92.2) |
| Hansen (2025) [9] | ≥ 65 years – mRNA-1273 JN.1 | Any lineage | Death | 95.8% (69.2–99.4) |
| Humphreys (2025) [7] | 65–79 years | JN.1-predominant period (autumn 2024/25 campaign) | COVID-19–related hospitalization | 60% (48–70) |
| Humphreys (2025) [7] | ≥ 80 years | JN.1-predominant period (autumn 2024/25 campaign) | COVID-19–related hospitalization | 58% (48–66) |
| Humphreys (2025) [7] | 65–79 years | JN.1-predominant period (autumn 2024/25 campaign) | COVID-19–related death | 78% (64–87) |
| Humphreys (2025) [7] | ≥ 80 years | JN.1-predominant period (autumn 2024/25 campaign) | COVID-19–related death | 62% (32–79) |
| Humphreys (2025) [15] | 65–79 years | JN.1 with KP sublineages (KP.2, KP.3) | COVID-19–related hospitalization | 13% (− 12–33) |
| Humphreys (2025) [15] | ≥ 80 years | JN.1 with KP sublineages (KP.2, KP.3) | COVID-19–related hospitalization | 7% (− 7–19) |
| Humphreys (2025) [15] | 65–79 years | JN.1 with KP sublineages (KP.2, KP.3) | COVID-19–related death | 39% (− 7–65) |
| Humphreys (2025) [15] | ≥ 80 years | JN.1 with KP sublineages (KP.2, KP.3) | COVID-19–related death | 3% (− 23–23) |
| Kirsebom (2024) [17] | ≥ 75 years | XBB-related sub-lineages (autumn 2023 period) | COVID-19–related hospitalization | 49.6% (42.3–56) |
| Kirsebom (2024) [17] | 18–64 years (clinical risk group) | XBB-related sub-lineages (autumn 2023 period) | COVID-19–related hospitalization | 41.5% (16.8–58.9) |
| Kopel (2024) [31] | ≥ 50 years | XBB-lineage (XBB.1.5-dominant; emerging JN.1) | COVID-19–related hospitalization | 61.1% (54.3–66.9) |
| Kopel (2024) [31] | ≥ 65 years | XBB-lineage (XBB.1.5-dominant; emerging JN.1) | COVID-19–related hospitalization | 60.5% (53.3–66.6) |
| Kopel (2024) [31] | ≥ 18 years with ≥ 1 underlying medical condition | XBB-lineage (XBB.1.5-dominant; emerging JN.1) | COVID-19–related hospitalization | 58.7% (51.3–65) |
| Lee (2024) [32] | ≥ 65 years | XBB-lineage (EG.5; HK.3; emerging JN.1) | Symptomatic SARS-CoV-2 infection | 67.2% (34.3–83.6) |
| Lee (2024) [32] | ≥ 65 years | XBB-lineage (EG.5; HK.3; emerging JN.1) | COVID-19–related hospitalization | 72.8% (37.3–88.2) |
| Lee (2024) [32] | ≥ 65 years | XBB-lineage (EG.5; HK.3; emerging JN.1) | Receipt of oxygen therapy | 78.7% (38.9–92.6) |
| Lee (2025) [16] | ≥ 65 years | XBB-predominant period | Hospitalization or death | 68% (62–73) |
| Lee (2025) [16] | 50–64 years | XBB-predominant period | Hospitalization or death | 56% (25–74) |
| Lee (2025) [16] | ≥ 65 years | JN/KP-predominant period | Hospitalization or death | 60% (52–67) |
| Lee (2025) [16] | 50–64 years | JN/KP-predominant period | Hospitalization or death | 58% (14–80) |
| Link-Gelles (2025) [10] | ≥ 65 years | XBB-predominant period | COVID-19–associated hospitalization | 54% (49–59) |
| Link-Gelles (2025) [10] | 18–64 years | XBB-predominant period | COVID-19–associated hospitalization | 31% (10–47) |
| Link-Gelles (2025) [10] | ≥ 65 years | JN.1-predominant period | COVID-19–associated hospitalization | 41% (34–47) |
| Link-Gelles (2025) [10] | ≥ 65 years | XBB-predominant period | COVID-19–associated critical illness (ICU admission or in-hospital death) | 73% (61–82) |
| Link-Gelles (2025) [10] | ≥ 65 years | JN.1-predominant period | COVID-19–associated critical illness (ICU admission or in-hospital death) | 54% (40–65) |
| Ma (2024) [33] | All adults hospitalized with COVID-19 | JN vs. XBB | ICU admission | aOR 0.80 (95% CI 0.46–1.38) |
| Ma (2024) [33] | All adults hospitalized with COVID-19 | JN vs. XBB | IMV or death | aOR 0.69 (0.34–1.40) |
| Monge (2024) [34] | 65–79 years | XBB.1.5-dominant period | COVID-19–related hospitalization | 67% (58–74) |
| Monge (2024) [34] | ≥ 80 years | XBB.1.5-dominant period | COVID-19–related hospitalization | 66% (57–73) |
| Monge (2024) [34] | 65–79 years | XBB.1.5-dominant period | COVID-19–related death | 67% (42–81) |
| Monge (2024) [34] | ≥ 80 years | XBB.1.5-dominant period | COVID-19–related death | 72% (51–85) |
| Nguyen (2025) [35] | 18–64 years | JN.1-predominant period | COVID-19–related hospitalization | 56.5% (18.6–76.8) |
| Nguyen (2025) [35] | 65–79 years | JN.1-predominant period | COVID-19–related hospitalization | 62.5% (40–76.6) |
| Nguyen (2025) [35] | ≥ 80 years | JN.1-predominant period | COVID-19–related hospitalization | 48.8% (36.9–58.5) |
| Nguyen (2025) [35] | Prior SARS-CoV-2 infection | JN.1-predominant period | COVID-19–related hospitalization | 58.2% (34–73.5) |
| Nguyen (2025) [35] | No documented prior infection | JN.1-predominant period | COVID-19–related hospitalization | 53.9% (27.5–70.7) |
| Nunes (2024) [18] | 65–79 years | JN.1-predominant period | COVID-19–related hospitalization | 50% (45–55) |
| Nunes (2024) [18] | ≥ 80 years | JN.1-predominant period | COVID-19–related hospitalization | 41% (35–46) |
| Nunes (2024) [18] | 65–79 years | JN.1-predominant period | COVID-19–related death | 58% (42–69) |
| Nunes (2024) [18] | ≥ 80 years | JN.1-predominant period | COVID-19–related death | 48% (38–57) |
| Rojas-Benedicto (2025) [37] | Winter wave | XBB.1.5-predominant period | COVID-19–related hospitalization | 73% (41–89) |
| Rojas-Benedicto (2025) [37] | Winter wave | JN.1-predominant period | COVID-19–related hospitalization | 34% (17–48) |
| Rojas-Benedicto (2025) [37] | Summer wave | JN.1-predominant period | COVID-19–related hospitalization | 8% (− 20–30) |
| Rojas-Benedicto (2025) [37] | Summer wave | KP.3-predominant period | COVID-19–related hospitalization | −3% (− 35–21) |
| Tartof (2024) [38] | ≥ 65 years | XBB-predominant period (JN.1 emerging) | COVID-19–associated hospitalization | 63% (30–80) |
| Tartof (2024) [38] | 18–64 years | XBB-predominant period (JN.1 emerging) | COVID-19–associated hospitalization | 65% (− 173–96) |
| Tartof (2024) [38] | ≥ 65 years | XBB-predominant period (JN.1 emerging) | COVID-19–associated ED/UC encounter | 56% (42–66) |
| Tartof (2024) [38] | 18–64 years | XBB-predominant period (JN.1 emerging) | COVID-19–associated ED/UC encounter | 64% (46–76) |
| Wilson (2025) [41] | Adults aged ≥ 65 years | XBB-predominant period (XBB.1.5; overlap with early JN.1 emergence) | COVID-19–related hospitalization | 56% (51–61) |
| Wilson (2025) [41] | Immunocompromised adults (≥ 18 years) | XBB-predominant period (XBB.1.5; overlap with early JN.1 emergence) | COVID-19–related hospitalization | 46% (39–52) |
aVE denotes absolute vaccine effectiveness compared with unvaccinated individuals; rVE denotes relative vaccine effectiveness compared with ≥ 2 doses of monovalent mRNA vaccines. For studies where vaccine effectiveness was not estimable, adjusted odds ratios (aORs) for severe outcomes are reported instead. Subgroup analyses were derived from adjusted models accounting for demographic and clinical covariates, with adjustment for prior SARS-CoV-2 infection varying by study, as described in the original publications. Only subgroup-specific estimates reported in the original studies are shown
Abbreviations: aOR, adjusted odds ratio; CI, confidence interval; ED, emergency department; ICU, intensive care unit; IMV, invasive mechanical ventilation; rVE, relative vaccine effectiveness; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; UC, urgent care; VE, vaccine effectiveness
Several studies reported reduced effectiveness among the oldest age groups (≥ 80 years) and during later Omicron subvariant periods. Where examined, effectiveness estimates were broadly similar between individuals with and without documented prior SARS-CoV-2 infection, although confidence intervals were wide in many subgroup analyses.
Risk of bias assessment
Risk of bias assessment using the ROBINS-I tool is summarised in Table 7. Overall risk of bias was judged as moderate for the majority of included studies. Residual confounding, particularly related to health-seeking behaviour and undocumented prior SARS-CoV-2 infection, was the most common reason for moderate risk judgments. Bias due to outcome measurement, intervention classification, and deviations from intended interventions was generally low. One study was judged to be at serious risk of bias due to confounding and selection concerns.
Table 7.
Risk of bias assessment (ROBINS-I). a
| First author (year) | Confounding | Selection of participants | Classification of interventions | Deviations from intended interventions | Missing data | Measurement of outcomes | Selection of reported result | Overall risk |
|---|---|---|---|---|---|---|---|---|
| Ackerson (2024) [3] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Andersen (2025) [26] | Moderate | Low | Low | Low | Low | Moderate | Low | Moderate |
| Andersson (2023) [4] | Moderate | Low | Low | Low | Low | Moderate | Low | Moderate |
| Andersson (2024) [5] | Moderate | Low | Low | Low | Low | Moderate | Low | Moderate |
| Antunes (2024) [27] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Antunes (2024) [28] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Antunes (2025) [6] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Aziz (2025) [13] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Caffrey (2024) [29] | Moderate | Low | Low | Low | Moderate | Moderate | Low | Moderate |
| Carazo (2025) [14] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Delaunay (2024) [30] | Serious | Low | Low | Low | Low | Low | Low | Serious |
| Grewal (2024) [8] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Hansen (2025) [9] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Humphreys (2025) [7] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Humphreys (2025) [15] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Kirsebom (2024) [17] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Kopel (2024) [31] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Lee (2024) [32] | Moderate | Moderate | Low | Low | Moderate | Low | Low | Moderate |
| Lee (2025) [16] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Link-Gelles (2025) [10] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Ma (2024) [33] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Monge (2024) [34] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Nguyen (2025) [35] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Nham (2025) [36] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Nunes (2024) [18] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Rojas-Benedicto (2025) [37] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Tartof (2024) [38] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| Tartof (2024) [39] | Moderate | Low | Low | Low | Low | Low | Low | Moderate |
| van Werkhoven (2024) [40] | Moderate | Low | Low | Low | Moderate | Low | Low | Moderate |
| Wilson (2025) [41] | Moderate | Low | Low | Low | Low | Moderate | Low | Moderate |
aROBINS-I domains: bias due to confounding; selection of participants; classification of interventions; deviations from intended interventions; missing data; measurement of outcomes; selection of the reported result. Overall risk corresponds to the highest risk of bias judgment across domains
Discussion
This systematic review synthesised real-world evidence on COVID-19 vaccine effectiveness across the Omicron evolutionary spectrum, spanning BA.2, BA.5, XBB, JN.1, and KP lineages, using observational studies published between 2022 and 2025 [1, 2, 22]. Across diverse geographic settings and study designs, a consistent pattern emerged: while vaccine effectiveness against SARS-CoV-2 infection was modest and waned rapidly [3, 30, 36], protection against severe COVID-19 outcomes, particularly hospitalization and death, remained substantial [4, 5, 8, 10] following receipt of updated, variant-adapted vaccines [3, 5–7].
For contextual interpretation, it is important to consider vaccine effectiveness during Omicron circulation relative to earlier pandemic phases dominated by ancestral and pre-Omicron variants. During these earlier periods, vaccine effectiveness against SARS-CoV-2 infection was generally higher and more durable, reflecting a closer antigenic match between circulating strains and vaccine formulations. In contrast, the Omicron era has been characterised by reduced and more rapidly waning protection against infection, largely driven by increased immune escape. However, protection against severe COVID-19 outcomes, including hospitalization and death, has remained comparatively more preserved across variants, although some attenuation has been observed during later Omicron subvariant periods and with increasing time since vaccination [2, 22].
Across Omicron subvariant periods, a consistent divergence was observed between vaccine effectiveness against SARS-CoV-2 infection and severe clinical outcomes. Protection against infection was modest and declined rapidly over time, whereas protection against severe outcomes, including hospitalization and death, was more durable, although it gradually waned [3, 5, 10, 22]. This pattern likely reflects ongoing immune escape driven by antigenic evolution of Omicron subvariants, which reduces neutralising antibody-mediated protection against infection, while cell-mediated and memory immune responses remain relatively preserved, thereby sustaining protection against severe disease, particularly hospitalization and death [1, 2, 22].
Interpretation of these findings should consider methodological heterogeneity across included studies. In addition to clinical and epidemiological differences, variation in study design likely contributed to differences in reported vaccine effectiveness estimates. Test-negative case–control studies, which constituted a substantial proportion of included studies, may be influenced by healthcare-seeking behaviour, testing availability, and case ascertainment, particularly for infection outcomes [21, 22]. In contrast, large population-based cohort studies and register-based target trial emulations may provide more stable estimates for severe outcomes, such as hospitalization and death, but remain susceptible to residual confounding related to population structure, prior infection, and healthcare utilisation [22, 25]. In particular, incomplete ascertainment of prior SARS-CoV-2 infection may result in misclassification of baseline immunity, potentially biasing vaccine effectiveness estimates in either direction [21, 22], while differences in healthcare-seeking behaviour may influence testing patterns and case detection, particularly in test-negative designs, thereby affecting observed effectiveness against infection outcomes [21, 22].
Furthermore, differences in comparator frameworks, such as comparisons with unvaccinated individuals versus previously vaccinated populations with waned immunity, as well as variation in follow-up periods and outcome definitions, may have contributed to heterogeneity in point estimates across Omicron subvariant periods. These methodological considerations should be taken into account when interpreting differences in vaccine effectiveness across studies and settings [22].
Interpretation of these findings should also consider the influence of prior immunisation history across included studies. Differences in vaccine platform, including mRNA, viral vector, and inactivated vaccines, as well as variation in the number of doses received, may have contributed to heterogeneity in vaccine effectiveness estimates. In addition, hybrid immunity resulting from prior SARS-CoV-2 infection combined with vaccination may enhance both the magnitude and durability of protection, particularly against severe outcomes. However, reporting of prior vaccination history and hybrid immunity was inconsistent across studies, and adjustment for these factors varied, which may have influenced comparability of effect estimates across settings and subvariant periods [21, 22].
During BA.4/BA.5-predominant periods, bivalent mRNA vaccines demonstrated high short-term effectiveness against severe outcomes, with most studies reporting protection exceeding 70% against hospitalization and death within the first three months after vaccination [3, 4, 8]. These findings are concordant with early post-deployment evaluations of bivalent boosters and reinforce their role in mitigating healthcare burden during late-2022 Omicron waves [4, 8, 19]. Importantly, the magnitude of protection against death was consistently higher than that against hospital admission, highlighting preserved vaccine impact on the most severe clinical endpoints despite immune escape at the infection level [3–5, 8, 10, 30].
As the Omicron lineage diversified further, particularly during XBB-dominant periods, monovalent XBB.1.5-adapted vaccines continued to provide substantial protection against severe disease [5, 10, 14, 26]. Large registry-based cohort studies and test-negative analyses from Europe and North America demonstrated moderate to high effectiveness against hospitalization and death, especially within the first two to three months following vaccination [5, 10, 14, 34]. However, waning immunity was evident over time, with reduced effectiveness observed beyond four to six months, underscoring the time-limited nature of protection and the importance of booster timing in high-risk populations [14–16, 18].
More recent evidence from JN.1- and KP-predominant periods suggests partial attenuation of vaccine effectiveness against severe outcomes [6, 15, 18]. Although point estimates were generally lower than those observed during earlier Omicron phases, most studies continued to demonstrate statistically significant and meaningful protection against hospitalization and death, particularly among adults aged 65–79 years [6, 7, 18]. Effectiveness was more variable in the oldest age groups (≥ 80 years), likely reflecting, at least in part, immunosenescence, higher baseline frailty, and competing risks of hospitalization [7, 18]. These findings align with accumulating evidence that updated vaccines retain public-health value even in the face of ongoing viral evolution, albeit with diminishing returns over time [5, 10, 19].
Across all Omicron phases, effectiveness against SARS-CoV-2 infection was consistently lower and declined rapidly, often approaching null or negative estimates beyond three to six months after vaccination [3, 30, 36, 37]. This pattern reflects the pronounced immune escape characteristics of Omicron subvariants and highlights the limited and time-dependent role of current vaccines in preventing infection or transmission [1, 2, 22]. Consequently, infection-based outcomes should be interpreted cautiously when evaluating vaccine performance, and severe clinical outcomes remain the most appropriate metrics for assessing real-world vaccine impact in the endemic phase of SARS-CoV-2 circulation [10, 19, 22].
Subgroup analyses reinforced several key observations. Vaccine effectiveness against severe outcomes was generally higher in adults aged 65–79 years than in those aged ≥ 80 years, and protection against death consistently exceeded protection against hospitalization across age strata [4, 7, 10, 18]. Where examined, effectiveness estimates were broadly similar among individuals with and without documented prior SARS-CoV-2 infection, although residual confounding and incomplete ascertainment of infection history may have influenced these findings [10, 16, 35]. Collectively, these results support continued prioritisation of updated booster vaccination for older adults and other high-risk groups during periods of ongoing Omicron circulation [5, 7, 10]. From a public health perspective, they further reinforce a risk-based booster strategy in which vaccine performance is evaluated primarily using protection against severe clinical outcomes rather than infection alone.
From a policy perspective, these findings support a risk-based booster vaccination strategy that prioritises individuals at highest risk of severe outcomes, particularly older adults and those with underlying conditions. The consistently higher effectiveness against death compared with hospitalization underscores the importance of preventing the most severe and resource-intensive outcomes. In addition, the observed pattern of peak protection within the first 1–3 months following vaccination, followed by gradual waning, suggests that booster timing should be strategically aligned with anticipated periods of increased transmission or variant emergence to maximise clinical benefit. Such targeted approaches are likely to enhance cost-effectiveness by concentrating vaccination efforts on populations most likely to benefit, while avoiding unnecessary frequent boosting in lower-risk groups [10, 22].
Strengths and limitations
This review has several important strengths. First, it provides a comprehensive synthesis of real-world vaccine effectiveness evidence across the full Omicron evolutionary spectrum, including the most recent JN.1 and KP lineages, which have not been systematically evaluated in prior reviews. Second, the focus on severe clinical outcomes enhances the clinical and policy relevance of the findings, particularly in the context of SARS-CoV-2 endemicity. Third, inclusion was restricted to peer-reviewed observational studies with clearly defined outcome measures, improving methodological robustness and reducing the risk of bias associated with interim surveillance reports or modelling studies.
Nevertheless, several limitations should be acknowledged. Considerable heterogeneity existed across included studies with respect to study design, comparator definitions, follow-up duration, outcome ascertainment, and adjustment for prior SARS-CoV-2 infection. Although this heterogeneity precluded quantitative meta-analysis, it reflects real-world variation in vaccination programs and surveillance systems. Publication bias could not be formally assessed due to the absence of meta-analysis and the heterogeneity of included studies. Therefore, the possibility that studies reporting higher vaccine effectiveness estimates were more likely to be published cannot be excluded. Residual confounding remains a concern in observational vaccine-effectiveness studies, particularly related to health-seeking behaviour, frailty, and undocumented prior infection. A further limitation is the geographic concentration of included studies, which were predominantly conducted in North America, Europe, and East Asia, with no representation from low- and middle-income settings. This may affect the generalisability of findings, as vaccine effectiveness can vary according to healthcare infrastructure, vaccine availability, prior infection dynamics, and population characteristics. Finally, evidence for the most recent Omicron subvariants remains relatively limited, and estimates for later follow-up periods were often imprecise, highlighting the need for ongoing evaluation.
Conclusion
In this systematic review of observational studies published between 2022 and 2025, updated and variant-adapted COVID-19 vaccines consistently provided substantial protection against severe COVID-19 outcomes across the Omicron evolutionary spectrum, despite limited and short-lived effectiveness against SARS-CoV-2 infection. Although protection against hospitalization and death declined with increasing time since vaccination and during later Omicron-dominant periods, clinically meaningful protection persisted, particularly among adults aged 65–79 years.
Taken together, these findings highlight the impact of ongoing SARS-CoV-2 evolutionary diversification and immune escape shape the real-world clinical impact of vaccination, particularly with respect to protection against severe disease and mortality. As SARS-CoV-2 transitions toward endemic circulation, these results underscore the importance of interpreting vaccine performance in the context of continued viral evolution, with severe clinical outcomes providing the most informative measures of real-world vaccine impact.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We would like to thank authors and their colleagues who contributed to the availability of evidence needed to compile this article. We would also like to thank the reviewers for very helpful and valuable comments and suggestions for improving the paper.
Abbreviations
- ARI
Acute respiratory infection
- BA
Omicron sublineage BA
- CI
Confidence interval
- COVID-19
Coronavirus disease 2019;
- ED
Emergency department
- EHR
Electronic health record
- ICU
Intensive care unit
- IMV
Invasive mechanical ventilation
- IPTW
Inverse probability of treatment weighting
- JN
Omicron BA.2.86-derived lineage JN
- KP
Omicron BA.2.86-derived KP lineage
- NR
Not reported
- PCR
Polymerase chain reaction
- rVE
relative vaccine effectiveness
- SARS-CoV-2
Severe acute respiratory syndrome coronavirus 2
- SARI
Severe acute respiratory infection
- UC
Urgent care
- VE
Vaccine effectiveness
- VEBIS
Vaccine Effectiveness, Burden and Impact Studies
- VISION
Virtual SARS-CoV-2, Influenza, and Other Respiratory Viruses Network
Author contributions
Conceptualisation, S.A.; methodology, S.A., O.A., A.S.A., N.A.D., N.E., and R.A.M.; protocol development and eligibility criteria, S.A., O.A., A.S.A., and N.A.D.; literature search and study se-lection, S.A., O.A., A.S.A., N.A.D., N.E., R.A.M., J.A.T., and S.M.A.; data extraction and data curation, S.A., O.A., A.S.A., N.A.D., N.E., R.A.M., and J.A.T.; risk of bias assessment, S.A., O.A., A.S.A., and N.A.D.; formal analysis and data synthesis, S.A.; interpretation of findings, S.A., O.A., N.A.D., N.E., R.A.M., and J.A.T.; writing—original draft preparation, S.A.; writing—review and editing, S.A., O.A., A.S.A., N.A.D., N.E., R.A.M., J.A.T., S.M.A., H.A.A.S., A.A., A.H.A. (Ali Hussain Alahmed), S.A.A., M.B.A., M.J.A., M.S.A. (Muath Saleh Almubarak), H.A.-H., A.J.A., H.A.A., A.A.A., A.H.A. (Ahmed H Aldera), F.M.A., N.A., M.S.A. (Murtadha Sameer Alsulaiman), Z.A.A., and H.A.A.G.; visualisation (tables and figures), S.A.; supervision, S.A.; project administration, S.A.; funding acquisition, not applicable. All authors have read and agreed to the published version of the manuscript.
Funding
None.
Data availability
All data generated or analyzed during this study are included in this published article.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Supplementary Materials
Data Availability Statement
All data generated or analyzed during this study are included in this published article.