Potential Public Health and Economic Impact of the Next-Generation COVID-19 Vaccine mRNA-1283 in The Netherlands
by
, , ,
Simon van der Pol
1,2
,
Ekkehard Beck
3,*
,
Tjalke Westra
4,
Maarten Postma
1,2,5 and
Cornelis Boersma
2,6 1
Department of Health Sciences, University Medical Center Groningen, University of Groningen, 9700RB Groningen, The Netherlands
2
Health-Ecore, 3704HE Zeist, The Netherlands
3
Moderna, Inc., Cambridge, MA 02142, USA
4
Moderna Netherlands, 1082MC Amsterdam, The Netherlands
5
Department of Economics, Econometrics and Finance, University of Groningen, 9747AE Groningen, The Netherlands
6
Department of Management Sciences, Open University, 6401DL Heerlen, The Netherlands
*
Author to whom correspondence should be addressed.
Vaccines 2026, 14(4), 364; https://doi.org/10.3390/vaccines14040364
Submission received: 2 March 2026
/
Revised: 10 April 2026
/
Accepted: 14 April 2026
/
Published: 20 April 2026
(This article belongs to the Section COVID-19 Vaccines and Vaccination)
Abstract
Background: COVID-19 remains a substantial public health challenge in the Netherlands. Next-generation COVID-19 vaccine, mRNA-1283, is approved in the European Union, with potential for higher relative vaccine efficacy compared with originally licensed COVID-19 vaccines. Methods: The potential public health and economic impact of mRNA-1283 in adults ≥ 60 years and high-risk adults aged 18–59 years was modeled versus no vaccination and originally licensed mRNA-1273 and BNT162b2, adapting a published static Markov model with a 1-year time horizon. COVID-19 burden reflected two full post-pandemic seasons. Vaccine efficacy versus mRNA-1273 was based on pivotal phase 3 NextCOVE trial data; efficacy versus BNT162b2 was derived from an indirect treatment comparison. The economically justifiable price (EJP) of mRNA-1283 versus no vaccination and price premiums over existing vaccines were determined at a willingness-to-pay threshold of €50,000/quality-adjusted life-year (QALY) gained. Results: Without COVID-19 vaccination, an estimated 460,000 infections, 23,800 hospitalizations, and 5300 deaths would occur. With current coverage, mRNA-1283 was estimated to prevent 68,000 infections, 5400 hospitalizations, and 1200 deaths, saving 9667 QALYs and over €66.5 million in treatment costs. The EJP was €238 versus no vaccination. Compared with mRNA-1273 and BNT162b2, mRNA-1283 was estimated to prevent additional burden (e.g., 1309 and 1679 hospitalizations, respectively) and was cost-effective at an incremental EJP of €62 versus mRNA-1273 and €80 versus BNT162b2. Conclusions: The results support continued COVID-19 vaccination to mitigate the ongoing health and societal burden of SARS-CoV-2 in the Netherlands. The comparative analyses indicate that mRNA-1283 may be associated with substantial health benefits over originally licensed mRNA vaccines; consequently, its use may further improve health outcomes and economic efficiency within COVID-19 vaccination programs.
Keywords:
cost-effectiveness; COVID-19; economic model; Netherlands; public health; SARS-CoV-2; vaccination1. Introduction
The COVID-19 pandemic has had a profound and sustained impact on population health and patient well-being, placing unprecedented pressure on healthcare systems worldwide. Since the introduction of mRNA COVID-19 vaccines, substantial reductions in severe disease, hospitalizations, and mortality have been observed. These vaccines were developed to provide strong protection against COVID-19, and their high effectiveness has been consistently demonstrated in both clinical trials [1,2,3] and real-world studies [4,5], including evidence from the Netherlands showing robust protection against severe outcomes [6].
In recent years, the Dutch Health Council has narrowed its recommendations for COVID-19 vaccination [7]. Current guidelines recommend vaccination primarily for individuals aged 18 years and older at increased medical risk, adults aged ≥ 60 years, adults aged ≥ 50 years who are also eligible for seasonal influenza vaccination, and healthcare workers [7]. This policy shift reflects a declining annual burden of disease, with reductions in reported cases, hospital admissions, and COVID-19-related deaths [8].
However, COVID-19 continues to pose a substantial public health challenge in the Netherlands. Hospitalizations and mortality attributable to COVID-19 persist, in particular, among those most vulnerable to severe COVID-19 disease, i.e., people with underlying medical conditions and older adults ≥ 60 years of age [7]. Modeling studies, as well as observational data, suggest that in the absence of vaccination, these numbers would be substantially higher [9]. The decreasing trend in vaccination coverage, from around 47% in 2024 to around 42% in 2025 [10], is also a cause for concern. Moreover, COVID-19 has multiple peaks throughout the year, and the largest peak coincides with influenza and respiratory syncytial virus (RSV) circulation during the winter months [7,11]. This temporal overlap increases pressure on healthcare capacity, underscoring the continued importance of effective preventive strategies [8].
A next-generation COVID-19 vaccine, mRNA-1283 (mNEXSPIKE, Moderna, Cambridge, MA, USA), has recently been approved in the European Union [12]. It was developed to focus the immune responses to increase protection against COVID-19 at a lower mRNA dose of 10 μg (e.g., 1/5th of the dose of mRNA-1273 (Spikevax, Moderna [13]), and its innovative design allows for inclusion in respiratory combination vaccines in future further developments. In pivotal phase 3 randomized clinical trials, higher immunogenicity and a higher relative vaccine efficacy (rVE) point estimate were observed with mRNA-1283 versus mRNA-1273, with the highest differences observed in adults ≥ 65 years and those with underlying medical conditions [3,14]. Observational studies and GRADE meta-analyses have shown that mRNA-1273 was more effective than BNT162b2 (Comirnaty, Pfizer-BioNTech, Mainz, Germany and New York, NY, USA) in the real-world setting [15,16,17,18,19]. Building on this evidence, and an indirect treatment comparison suggesting mRNA-1283 may be more effective than BNT162b2 [20], it is essential to understand the potential added clinical and economic value of mRNA-1283 over originally licensed mRNA COVID-19 vaccines.
The objectives of this study were to assess the potential public health and economic impact of mRNA-1283 compared with no COVID-19 vaccination, considering the current endemic and seasonal COVID-19 context. Furthermore, the impact of mRNA-1283 vaccination was compared with mRNA-1273 and BNT162b2.
2. Materials and Methods
The public health impact and economically justifiable price (EJP) of the next-generation mRNA-1283 vaccine versus no vaccination, mRNA-1273, and BNT162b2 were estimated in the Netherlands with three different scenarios based on the post-pandemic epidemiology. A previously published static Markov decision tree model with monthly cycles comparing mRNA-1273 to no vaccination and to BNT162b2 vaccination over a 1-year time horizon in the Netherlands [9] was adapted and updated for this analysis.
2.1. Target Population
The base case target vaccination population included all adults aged ≥ 60 years and high-risk adults aged 18–59 years, defined as individuals at a high medical risk aged 18–49, and the influenza target group aged 50–59 years, according to season 2025/2026 Dutch COVID-19 vaccination recommendations [7].
2.2. Model Structure and Inputs
The model structure and assumptions were previously described for economic analyses in the Netherlands (Zeevat et al. 2025 [9]), the United States (US) [21], and Canada [22] (Figure A1). In summary, individuals had a monthly risk of COVID-19 infection based on Dutch age-specific incidence data. Following infection, the risk of health outcomes was determined by the decision tree. Every month, individuals could receive a COVID-19 vaccine, based on age-specific coverage rates, which reduced the risk of infection and hospitalization following infection, according to each vaccine’s efficacy (Table 1). Following Zeevat et al. 2025 [9], a static model was considered appropriate, though conservative compared with a dynamic modeling approach, due to the restriction of COVID-19 vaccination to high-risk populations in the Netherlands, a short model time horizon, and other endemic setting cost-effectiveness modeling approaches in the US [23] and UK [24].
The model inputs and assumptions (Table A1) were previously described in Zeevat et al. 2025 [9], with updates to input parameters summarized below. All other input parameters follow Zeevat et al. 2025 [9]. Cost estimates, including productivity losses, from Zeevat et al. 2025 were inflated from 2023 to 2025 using the Dutch consumer price index [25].
2.3. Model Input Parameter Updates
As COVID-19 incidence is evolving and remains subject to seasonal fluctuations, the base case was intended to represent a plausible endemic/seasonal steady-state, as is often done for influenza modeling [27], rather than to forecast future epidemic resurgence. Thus, the base case risk of infection assumed the average incidence of symptomatic COVID-19 infections in the 2023/2024 and 2024/2025 seasons in the Netherlands. Specifically, the 2023/2024 season was used to represent a relatively high incidence season and was based on the incidence used in Zeevat et al. 2025 [9], whereas the 2024/2025 season was estimated at 40% of 2023/2024 based on the recently published Netherlands infectious disease report of 2024 [8]. The resulting 0.7 scaling factor, therefore, reflects the mean of a recent higher and lower post-pandemic season, rather than a subjective adjustment. Because future COVID-19 incidence remains unclear and resurgence cannot be excluded, separate low and high incidence scenarios were explored in sensitivity analyses.
The vaccine coverage rate (VCR) for the Dutch campaign, running from September to December, was updated using 2025 observed values [10].
A Dutch observational study found that the risk of developing post-COVID-19 condition has declined during post-pandemic years [28]. However, substantial uncertainty remains regarding the current incidence, duration, and severity of post-COVID-19 condition, as well as heterogeneity in its definition and measurement across studies. Given this uncertainty, the post-COVID-19 condition was not included in the base case analysis, in order to avoid introducing structural uncertainty and potential overestimation of vaccine benefits. Thus, contrary to Zeevat et al. 2025 [9], the post-COVID condition was not considered in the base case analysis as part of the infection consequences tree. To ensure transparency, however, the post-COVID-19 condition was considered in a scenario analysis based on the parameters assumed in Zeevat et al. 2025 [9] due to the substantial level of evidence on the risk of onset of post-COVID-19 condition in people infected with COVID-19, especially those most vulnerable to severe COVID-19 disease. In addition, there is an emerging level of evidence that COVID-19, like seasonal influenza and other respiratory diseases, can trigger and exacerbate chronic conditions following a COVID-19 infection [29,30].
2.4. Vaccine Characteristics
Vaccine effectiveness (VE) inputs against COVID-19 infection and hospitalization were based on the estimates assumed in a cost-effectiveness analysis of mRNA-1283 in the US for 2025/2026 [21]. In short, the absolute VE of mRNA-1283 was estimated considering a risk-ratio-based approach, applying the rVE of mRNA-1283 versus mRNA-1273 (derived from the pivotal phase 3 NextCOVE randomized clinical trial [3] conducted during 2023–2024 using the bivalent original and Omicron BA4/5 strain containing versions of both vaccines) to the VE of mRNA-1273. The latter was derived from a large real-world evidence study of mRNA-1273 VE (targeting the KP.2 variant) against COVID-19-related hospitalizations and medically attended COVID-19 (a proxy for infections) [31] (Table 1). The rVE of mRNA-1283 versus BNT162b2 was based on findings of an indirect treatment comparison (ITC) [20], leading to absolute BNT162b2 VE estimates (Table 1). An ITC (Bucher method) using the NextCOVE trial data and real-world evidence comparing mRNA-1273 with BNT162b2 estimated higher efficacy with mRNA-1283 than BNT162b2, i.e., estimated rVE against symptomatic infection was 15.3% (95% CI 4.7–24.8%) in all adults and 22.8% (95% CI 4.7–24.8%) in those aged ≥ 65 years. Table 1 first presents the mRNA-1273 VE and the rVE of mRNA-1283 versus mRNA-1273 used to estimate the absolute VE of mRNA, and then presents the absolute mRNA-1283 VE and the rVE of mRNA-1283 versus BNT162b2 used to estimate the BNT162b2 VE.
In the base case, the rVE against hospitalization was based on an FDA-defined severe COVID-19 endpoint of the NextCOVE trial [3], assumed as a proxy for rVE against hospitalization [21]. The same monthly VE waning rates were assumed for all vaccines (4.75% against infection [32] and 2.46% against hospitalization [33]). Given that the rVE of mRNA-1283 versus mRNA-1273 was observed over a median follow-up of 8 months, these estimates are likely to reflect any potential differences in waning. Further details of the estimation of VE inputs for mRNA-1283, mRNA-1273, and BNT162b2 are presented in Fust et al. 2026 [21].
Frequencies of reactogenicity grade 3 events for mRNA-1283 and mRNA-1273 were based on the NextCOVE trial data, and grade 3 events were assumed to be the same for mRNA-1273 and BNT162b2 [22]. Rates of myocarditis/pericarditis (0.0008%) associated with all mRNA COVID-19 vaccines were assumed for high-risk adults aged 18–60 years, following estimates provided in the US FDA label [34].
Updates were made to the utility losses associated with some infection-related health states and with adverse events [22].
2.5. Vaccine Unit Costs
COVID-19 vaccine procurement in the Netherlands is conducted through European tenders and commonly includes confidential discounts; thus, net vaccine prices are not publicly disclosed. Consequently, for the economic analysis, the EJP was estimated at a willingness-to-pay (WTP) threshold of €50,000 per QALY gained, based on the proposed WTP threshold in 2024 for public health interventions, including vaccines [9]. In the absence of transparent price data, conventional cost-effectiveness analyses based on fixed vaccine prices would require strong assumptions and may therefore be less appropriate in this context.
2.6. Sensitivity and Scenario Analyses
The robustness of the results was assessed in sensitivity and scenario analyses. In particular, the impact of specific parameter assumptions and modeling settings was assessed on the EJP at a WTP of €50,000/QALY. The VE of mRNA-1283 against infection and hospitalization was varied using the upper and lower bounds of the 95% confidence interval; the rVE against hospitalization was varied by applying the same rVE for mRNA-1283 versus mRNA-1273 for infection to hospitalization. The VCR was also varied by ±20%, and further scenario analyses explored restricting vaccination target populations to all adults aged ≥ 75 years only (n = 1,759,000), and expanding to all 50–59-year-olds (n = 2,465,000), instead of just high-risk 50–59-year-olds (n = 298,000) [35,36]. Lastly, a scenario analysis assessed the burden of the post-COVID-19 condition and the impact of vaccination. As in Zeevat et al. 2025 [9], all COVID-19 survivors were assumed to experience, following the acute COVID-19 infection, healthcare resource use and utility loss, while those with post-COVID-19 condition were assumed to experience productivity losses, to avoid double-counting, and due to a lack of data.
Additionally, deterministic sensitivity analyses (DSA) were performed to assess the impact of varying inputs on the ICER of mRNA-1283 vaccination versus no vaccination. Following Zeevat et al. 2022 [37], the base case EJP at a WTP of €50,000/QALY was considered as the vaccine price for this DSA, and was varied along with other input parameters by ±20% (Zeevat et al. 2025 [9]). The DSA results are presented in a Tornado diagram.
Probabilistic sensitivity analyses (PSA) with n = 1000 simulations were conducted to assess the impact of parameter uncertainty on incremental EJPs of mRNA-1283 versus mRNA-1273 and mRNA-1283 versus BNT162b2 at a WTP threshold of €50,000/QALY following the approaches taken in Zeevat et al. 2025 [9] and Fust et al. 2025 [22] (see Appendix A for details on parameter input estimates). Table A2 and Table A3 specify each parameter considered in the PSA, the point estimate, the distribution assumed, and the standard error/deviation. The PSA results are presented, showing the likelihood of varying incremental EJPs being cost-effective at a WTP threshold of €50,000/QALY.
3. Results
3.1. Base Case Analysis: mRNA-1283 Versus No Vaccination
With no COVID-19 vaccination in the base case, among the 14.8 M adults in the Netherlands, there were an estimated 460,000 symptomatic infections, 24,000 hospitalizations, and 5500 deaths from COVID-19.
In the base case, mRNA-1283 vaccination of adults aged ≥ 60 years and of high-risk adults aged 50–59 years (around 2.1 million individuals vaccinated) was estimated to produce important public health gains. Around 68,000 symptomatic infections, 5400 hospitalizations, and 1200 deaths from COVID-19 were estimated to be prevented, with treatment cost savings exceeding €66.5 million and with 9667 QALYs gained (Table 2). The public health impact was estimated to be between 3000 and 7700 hospitalizations prevented, considering a lower or higher COVID-19 incidence (Table 2).
In the base case, the estimated number needed to vaccinate (NNV) with mRNA-1283 was 31 to prevent a symptomatic infection, 396 for a COVID-19 hospitalization, and 1756 for a COVID-19 death.
Given a base case WTP threshold of €50,000/QALY gained, mRNA-1283 was cost-effective at an EJP of €237.93 compared with no vaccination. When considering a WTP of €20,000/QALY, the average EJP of mRNA-1283 across all three incidence scenarios was €101.57.
Additional Scenario Analyses and DSA Results
Varying the VE of mRNA-1283 against infection and hospitalization, using the lower bounds and upper bounds of the 95% confidence intervals, resulted in 3754–6693 hospitalizations prevented and 846–1508 deaths prevented, with an EJP of €160.70 (using lower bounds) to €301.05 (using upper bounds) (Table 3). Assuming the same rVE of mRNA-1283 against infection as for hospitalization resulted in fewer prevented hospitalizations (4532) and deaths (1021), and a lower EJP (€199.27) versus the base case. Varying the base case VCR by ±20% resulted in 4300–6451 hospitalizations prevented and 969–1453 deaths prevented, but did not impact the EJP, as a static health economic model was applied. Expanding the target population to all 50–59-year-olds prevented slightly more hospitalizations (5481) and deaths (1219) than in the base case and lowered the EJP to €186.54 (at WTP of €50,000/QALY). By contrast, reducing the target population to only adults ≥ 75 years reduced the number of prevented hospitalizations (2779) and deaths (628) considerably, and increased the EJP to €371.03 compared with the base case. The scenario assessing the impact of mRNA-1283 vaccination on post-COVID-19 condition found that mRNA-1283 would prevent an estimated 2265 incident post-COVID-19 condition cases, at an EJP of €241.96. This represents an increase in estimated economic value and QALY gains compared with the base case analysis.
Figure 1 shows the ten parameters with the greatest impact on the incremental cost-effectiveness ratio (ICER) of mRNA-1283 versus no vaccination (at an EJP based on WTP of €50,000/QALY). The most important parameters affecting cost-effectiveness were COVID-19 incidence (a higher incidence led to a lower ICER), VE against hospitalization (a higher VE reduced the ICER), and the hospitalization rate given infection (a higher rate of hospitalization led to a more cost-effective vaccination program).
3.2. Analysis: mRNA-1283 Versus mRNA-1273
Vaccination with mRNA-1283 prevented more symptomatic infections (8931), hospitalizations (1309), and COVID-19 deaths (295) than mRNA-1273, resulting in treatment cost savings (€14,743,901) and QALY gains (2323). As expected, more vaccination gains were predicted in scenarios with a higher COVID-19 incidence and higher mRNA-1283 versus mRNA-1273 rVE (Table 4).
Using the base case incidence and rVE, mRNA-1283 was cost-effective at an incremental EJP of €61.53 over mRNA-1273 (WTP €50,000/QALY) and €28.77 (WTP €20,000/QALY). These values increased as vaccination benefits increased in the higher incidence and high rVE scenarios, and decreased in the lower incidence scenario, with no incremental EJP estimated in the low rVE scenario (Table 4).
In the base case, the incremental NNV, i.e., the additional number of persons to be vaccinated with mRNA-1273 versus mRNA-1283 to prevent one COVID-19 hospitalization, was 127.
With an incremental EJP of €61.53, the probability of mRNA-1283 versus mRNA-1273 being cost-effective at a WTP of €50,000/QALY was 0.44 (Figure 2).
3.3. Analysis: mRNA-1283 Versus BNT162b2
Vaccination with mRNA-1283 prevented more symptomatic infections (16,499), hospitalizations (1679), and COVID-19 deaths (378) than BNT162b2, resulting in treatment cost savings (€19,827,071) and QALY gains (3005). Again, more vaccination gains were predicted in scenarios with a higher COVID-19 incidence and higher rVE (Table 5).
Using the base case incidence and rVE, mRNA-1283 was cost-effective at an incremental EJP of €79.96 over BNT162b2 (WTP €50,000/QALY) and €37.57 (WTP €20,000/QALY). These values increased as vaccination benefits increased in the higher incidence and higher mRNA-1283 versus BNT162b2 rVE scenarios, and decreased in the lower incidence and low rVE scenarios, although they remained positive (Table 5).
In the base case, the incremental NNV, i.e., the additional number of persons to be vaccinated with BNT162b2 versus mRNA-1283 to prevent one COVID-19 hospitalization, was 180.
With an incremental EJP of €79.96, the probability of mRNA-1283 versus BNT162b2 being cost-effective at a WTP of €50,000/QALY was 0.45 (Figure 3).
4. Discussion
In the Netherlands, the burden due to COVID-19 remains substantial, especially in those most vulnerable to severe COVID-19 disease. Our results estimated that without vaccination, 460,000 (260,000–660,000) individuals would develop symptomatic COVID-19, leading to 24,000 (13,000–34,000) hospitalizations and 5400 (3000–8000) deaths. Considering the current vaccination coverage and recommended target population, a potential vaccination campaign with mRNA-1283 could prevent 68,000 (39,000–97,000) symptomatic cases, 5400 (3000–8000) hospitalizations, and 1200 (700–1700) deaths compared with no vaccination. These health gains were estimated to lead to 9667 QALYs gained, as well as €66.5 million in cost savings. mRNA-1283 vaccination was estimated to be cost-effective at an EJP of €238 (WTP of €50,000/QALY) and of €102 (WTP of €20,000/QALY).
These model-based estimates, as well as reported surveillance data, suggest that despite widespread population immunity, COVID-19 continues to place a substantial burden on individuals and public health in the Netherlands under current incidence levels. Ongoing transmission results in a large number of symptomatic infections, of which approximately 30% require care from a general practitioner, which can contribute to sustained pressure on primary care services [38]. Importantly, COVID-19 now circulates concurrently with other major respiratory pathogens, including RSV and influenza. The overlapping seasonality of these infections creates a risk of simultaneous epidemic peaks, increasing the likelihood of a so-called “triple endemic” scenario, and increasing the strain on both primary and secondary healthcare capacity. Assuming a COVID-19 hospital length of stay of 8.43 days [39], vaccination with mRNA-1283 could potentially prevent 45,000 hospital bed-days and approximately 17,000 general practitioner visits. Beyond direct healthcare utilization, COVID-19 also imposes a considerable societal burden through productivity losses due to absenteeism and reduced work capacity. Taken together, these factors underline that the current COVID-19 vaccination program remains highly relevant from a public health perspective and from a broader societal standpoint. Maintaining protection against COVID-19 in the working-age population is essential to safeguard workforce availability and ensure the continuity of critical sectors such as healthcare, education, and other essential public services.
Based on pivotal clinical trial data and findings of an indirect treatment comparison, our results estimated that mRNA1283 could provide greater public health benefits than currently available COVID-19 mRNA vaccines, especially in those most vulnerable to severe COVID-19 disease. Compared with mRNA-1273, vaccination with next-generation mRNA-1283 in the base case was estimated to prevent 8900 additional symptomatic COVID-19 infections, 1300 additional hospitalizations, and 295 additional deaths, leading to higher healthcare cost-savings and QALY gains. Even greater health gains and cost-savings were estimated for the comparison of mRNA-1283 versus BNT162b2, the currently used vaccine in the Netherlands [9], in the base case (i.e., preventing around 16,500 additional symptomatic COVID-19 infections, 1700 additional hospitalizations, and 380 additional deaths). Potential vaccination with mRNA-1283 was cost-effective versus mRNA-1273 at an incremental EJP of €62, and versus BNT162b2 at an incremental EJP of €80, considering a WTP of €50,000/QALY for both comparisons. Scenario analyses addressing uncertainty in COVID-19 incidence and the rVE of mRNA-1283 versus mRNA-1273 and mRNA-1283 versus BNT16b2 showed the incremental EJP ranging from 104.65 EUR to 0 EUR and 142.67 EUR to 3.37 EUR when considering a €50,000/QALY WTP threshold. Overall, these findings are in line with other public health and economic evaluations comparing mRNA-1283 vaccination with no vaccination and with existing COVID-19 vaccinations in Canada [22] and the US [21], as well as the previous Dutch evaluation showing the vaccination gains of mRNA-1273 over BNT162b2 [9].
This analysis estimated an EJP of €238 for COVID-19 vaccination. While vaccine prices in the Netherlands are confidential due to tender-based procurement, publicly available information from other European settings provides a useful contextual benchmark. For example, reported list prices for COVID-19 vaccines in countries such as Germany suggest price levels that are substantially below the EJP estimated in this analysis. Although list prices may not reflect actual tender prices, and cross-country comparisons should be interpreted with caution, this observation supports the robustness of our findings. Specifically, it indicates that COVID-19 vaccination is likely to remain cost-effective under a broad range of plausible pricing scenarios. Compared with other preventive interventions for respiratory infectious diseases, such as influenza and RSV vaccination, the COVID-19 EJP seems to be notably higher [9,40,41]. This difference can largely be explained by the substantially higher burden of disease associated with COVID-19 [42,43]. Even in the post-pandemic period, COVID-19 continues to result in a structurally higher number of hospitalizations and deaths than influenza and RSV [42]. As these parameters are key drivers of cost-effectiveness outcomes, these factors directly contribute to the higher health gains and cost offsets achievable with COVID-19 vaccination, and consequently to the higher EJP. Differences in methodological choices across evaluations further contribute to the observed variation in EJPs between respiratory vaccines [9,40,41]. In most recent cost-effectiveness analyses of high-dose influenza vaccination, comparisons were typically made against standard-dose influenza vaccination, capturing only the incremental benefits of switching between vaccine types, rather than the full value of influenza vaccination versus no vaccination [40]. As a result, these analyses typically do not aim to assess the overall value of influenza vaccination programs when compared with evaluations assessing vaccination versus no vaccination, as this COVID-19 analysis has done. As such, the higher EJP estimated for COVID-19 vaccination appears consistent with both the underlying epidemiology and the analytical framework applied, and reflects the persistently higher disease burden of COVID-19 relative to other respiratory infections.
Previously discussed limitations [9,21,22] also apply to this evaluation. Uncertainty around the evolving incidence of COVID-19 was addressed by evaluating vaccination impact under low and high incidence scenarios; however, the true trajectory of COVID-19 incidence will only become clear over time. Our base case analysis was not intended to predict variant-driven resurgence waves, but rather to approximate the value of vaccination in a routine endemic setting. Analyses specifically addressing future resurgence would require alternative assumptions and potentially different modeling approaches that explicitly account for epidemic timing, variant characteristics, and changes in population susceptibility. The number of COVID-19 hospitalizations reported in the Netherlands (average of 2023 and 2024, 19,500 hospitalizations [8,44]) was comparable to the number predicted in the base case model (average of 2023/2024 and 2024/2025, ranging from 18,455 with mRNA1283 to 20,134 with BNT162b2), providing support for the base case incidence assumptions. A static model was used, which does not fully capture transmission dynamics, immunity effects, or indirect protection compared to dynamic transmission models. Fust et al. (2026) [21] found in a scenario analysis that incorporating indirect protection lowered ICER estimates. Therefore, the reported public health impact and cost-effectiveness of mRNA-1283 are likely conservative. Post-COVID-19 condition was not included in the base case analysis due to uncertainty in its current epidemiology and burden in the post-pandemic setting, as well as variability in its definition and measurement. However, scenario analyses including post-COVID-19 condition demonstrated additional health gains and economic value, indicating that the base case results may be considered conservative. The efficacy and safety of mRNA-1283 have not yet been established in the real-world setting. Thus, the rVE of mRNA-1283 versus mRNA-1273 from the NextCOVE trial [3], as well as the results of the indirect treatment comparison of mRNA-1283 and BNT162b2, should be validated and refined with real-world evidence studies. No data for the Netherlands (or Europe) were identified on utility loss associated with COVID-19; thus, the US data were used [9].
There remains a clear need to continue investing in COVID-19 vaccination in the Netherlands. Such programs are still highly relevant, given the ongoing burden of disease, and additionally, new COVID-19 vaccines such as the next-generation mRNA-1283 may provide an opportunity to optimize COVID-19 vaccination programs, especially for populations most vulnerable to severe COVID-19. Although overall incidence has declined since the peak of the pandemic, COVID-19 transmission remains unpredictable, with a persistent risk of renewed increases in incidence. In addition, while vaccination of all adults aged 50–59 years may be perceived as less critical from a public health perspective, it is highly relevant from a broader societal perspective, as preventing COVID-19 and other respiratory infectious diseases in this age group helps reduce productivity losses and work absenteeism, thus providing wider socioeconomic gains.
The findings of this analysis in the Netherlands may have broader relevance for other European settings. The value of COVID-19 vaccination is driven by key parameters, including incidence, risk of severe outcomes, vaccine effectiveness, healthcare costs, and vaccination coverage. Many European countries share similar demographics, such as aging populations, comparable healthcare systems, and seasonal respiratory infection patterns. As such, while absolute estimates of health impact and EJPs may differ across countries, the direction and magnitude of COVID-19 vaccination benefits are likely to be comparable. When interpreting findings in other settings, however, differences in country-specific factors, including healthcare costs, vaccination uptake, population risk profiles, and epidemiological dynamics, should be considered.
5. Conclusions
The findings support continued COVID-19 vaccination as a key public health measure to address the persistent health and societal burden associated with ongoing transmission of SARS-CoV-2. In this setting, optimizing vaccine choice within existing programs becomes increasingly important. The comparative analyses suggest that mRNA-1283 is potentially associated with the greatest health gains, based on evidence of potentially higher efficacy or effectiveness compared with originally licensed mRNA COVID-19 vaccines. Consequently, using mRNA-1283 could further enhance both health outcomes and economic benefits within COVID-19 vaccination programs.
Author Contributions
All authors were involved in the study concept and design. E.B. and T.W. parameterized and programmed the model. All authors were involved in the analyses and interpretation of the data. All authors reviewed the paper critically for intellectual content. All authors have read and agreed to the published version of the manuscript.
Funding
This study was funded by Moderna, Inc.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The data presented in this study are available in this article.
Acknowledgments
Medical writing and editorial assistance were provided by Kavi Littlewood (Littlewood Writing Solutions) in accordance with Good Publication Practice (GPP 2022) guidelines, funded by Moderna, Inc., and under the direction of the authors.
Conflicts of Interest
T.W. and E.B. are employed by Moderna, Inc., and may hold stock/stock options in the company. M.P. and C.B. received grants and honoraria from various pharmaceutical companies, including Moderna, Inc., and others developing, producing, and marketing vaccines. SvdP declares no conflicts of interest. The authors declare that the research was conducted independently and that this relationship did not influence the study design, data collection, analysis, interpretation, or the conclusions presented in this manuscript.
Abbreviations
The following abbreviations are used in this manuscript:
| BNT162b2 | Comirnaty, Pfizer-BioNTech |
| CI | Confidence interval |
| DSA | Deterministic sensitivity analysis |
| EJP | Economically justifiable price |
| ICER | Incremental cost-effectiveness ratio |
| ICU | Intensive care unit |
| K | thousands |
| M | million |
| mRNA-1273 | Spikevax, Moderna |
| mRNA-1283 | mNEXSPIKE, Moderna |
| NNV | Number needed to vaccinate |
| PSA | Probabilistic sensitivity analysis |
| QALY | Quality-adjusted life-year |
| rVE | Relative vaccine effectiveness |
| US | United States |
| VCR | Vaccine coverage rate |
| VE | Vaccine effectiveness |
| WTP | Willingness-to-pay |
Appendix A
Figure A1.
Decision tree consequences model (based on [21]). ICU: intensive care unit.
Figure A1.
Decision tree consequences model (based on [21]). ICU: intensive care unit.
Table A1.
Model inputs.
| Population | Source | ||||
|---|---|---|---|---|---|
| Total | 5,922,720 | High-risk | [36] | ||
| 60+ | 4,784,093 | Age-based | |||
| 50–59 | 298,007 | Yes | |||
| 18–49 | 840,620 | Yes | |||
| Incidence COVID-19 symptomatic infection | |||||
| Age- and month-dependent | Table A2 [9] | ||||
| Proportion of infected people seeking care at the general practitioner level | |||||
| 60+ | 28.46% | Age-adjusted [38] | |||
| 50 to 59 | 21.26% | ||||
| 18 to 49 | 19.69% | ||||
| Age-dependent COVID-19 hospitalization risk given COVID-19 symptomatic infection | |||||
| 60+ | 5.89% | Age-adjusted [9] | |||
| 50 to 59 | 0.68% | ||||
| 18 to 49 | 0.26% | ||||
| Percentage Intensive Care Unit (ICU) among hospitalized | |||||
| 60+ | 5.79% | Age-adjusted [9] | |||
| 50 to 59 | 11.72% | ||||
| 18 to 49 | 11.43% | ||||
| In-hospital mortality (no ICU) | |||||
| 60+ | 18.04% | Age-adjusted [9] | |||
| 50 to 59 | 2.10% | ||||
| 18 to 49 | 0.60% | ||||
| In-hospital mortality (ICU) | |||||
| 60+ | 43.68% | Age-adjusted [9] | |||
| 50 to 59 | 15.05% | ||||
| 18 to 49 | 6.74% | ||||
| Hospital readmission rate | 11.70% | [45,46] | |||
| Post-discharge mortality | 3.80% | [46] | |||
| Infection associated myocarditis | |||||
| Female | Male | ||||
| 60+ | 0.0847% | 0.1683% | Age-adjusted [9] | ||
| 50 to 59 | 0.1018% | 0.1881% | |||
| 18 to 49 | 0.0592% | 0.1682% | |||
| Vaccine characteristics | |||||
| Vaccine effectiveness (VE) | Age- and product-dependent | Table 1 (main manuscript) | |||
| Waning of VE (same for all products) | |||||
| Against infection | 4.75% | [32] | |||
| Against hospitalization | 2.46% | [33] | |||
| Vaccine related AEs | |||||
| Probabilities | mRNA-1283 | mRNA-1273 | BNT162b2 | ||
| Grade 3 local | 1.61% | 1.17% | 1.17% | [3] | |
| Grade 3 systemic | 7.16% | 5.77% | 5.77% | ||
| Anaphylaxis | 0.0005% | 0.0005% | 0.0005% | [47] | |
| Myocarditis/pericarditis * | 0.0008% | 0.0008% | 0.0008% | [34] | |
| Vaccination coverage | |||||
| Sep-25 | Oct-25 | Nov-25 | Dec-25 | [10] | |
| 60+ | 1.90% | 19.37% | 35.63% | 41.60% | |
| 50 to 59 | 11.68% | 18.51% | 23.55% | 26.93% | |
| 18 to 49 | 2.93% | 4.65% | 5.91% | 6.76% | |
| Costs (Euro) | |||||
| Vaccine administration cost | 13.67 | [48] inflated to 2025 | |||
| Direct healthcare cost | |||||
| Outpatient care (GP visit) | 43.22 | [49] inflated to 2025 | |||
| Hospital General Ward (same for readmission) | 7051.88 | [50] inflated to 2025 | |||
| Hospitalized—ICU (same for readmission) | 12,650.72 | ||||
| Hospitalization recovery (inpatient follow-up) | 119.20 | [49] inflated to 2025 | |||
| Post-infection period (long-COVID) (scenario) | 1206.29 | [51] inflated to 2025 | |||
| Myocarditis following infection | 3304.61 | Age-adjusted [9] inflated to 2025 | |||
| AEs | |||||
| Grade 3 local | 0.26 | [52] inflated to 2025 | |||
| Grade 3 systemic | 0.26 | ||||
| Anaphylaxis | 339.26 (1 ED visit) | [49] inflated to 2025 | |||
| Myocarditis/pericarditis (5.3 nursing days) | 6119.47 | [42,49] inflated to 2025 | |||
| Indirect costs | |||||
| Percentage in labor force | |||||
| 60+ | 22.5% | [9] | |||
| 50 to 59 | 83.0% | ||||
| 18 to 49 | 85.9% | ||||
| Daily wage | 208.74 | [49,53] inflated to 2025 | |||
| Productivity loss estimates (in days) | |||||
| Vaccine administration | 0.13 | 1 h assumption | |||
| COVID-19 non-hospitalized | 3.5 | [54] | |||
| COVID-19 hospitalized (non ICU) | 8.43 (SD 7.51) | [39] | |||
| COVID-19 hospitalized (ICU) | 16.64 (SD 13.69) | [39] | |||
| Recovery from hospitalization | 27 | [55] | |||
| Post-COVID (scenario) | 11 | [56] | |||
| Myocarditis (infection-induced) | 8.8 | Age-adjusted [9] | |||
| Myocarditis (adverse events) | 3 | [42] | |||
| Anaphylaxis (adverse event) | 1 | [42] | |||
| QALY loss | |||||
| Baseline utility data for each population group: age-dependent | |||||
| Grade 3 local | 0.0004 | [57] | |||
| Grade 3 systemic | 0.0004 | ||||
| Anaphylaxis | 0.02 | ||||
| Myocarditis/pericarditis | 0.0019 | ||||
| COVID-19 Infection related health states (>18 years) | |||||
| No formal care | 0.0046 | Assumed based on [58] (assumed same for readmission) | |||
| Outpatient care | 0.0046 | ||||
| Hospitalized/readmission | |||||
| No ICU | 0.0174 | ||||
| ICU only | 0.0394 | ||||
| Ventilator | 0.0394 | ||||
| Myocarditis (infection) | 0.0188 | Age-adjusted [9] | |||
| Post-COVID (scenario) | |||||
| No formal care | 0.0 | [59] adjusted for outpatient care QALY loss [60] | |||
| Outpatient care | 0.023 | ||||
| Hospitalization | 0.1026 | ||||
* Myocarditis/pericarditis applies to ages 18–60 only; AE rates for BNT162b2 assumed same as mRNA-1273. No Grade 4 event assumed for mRNA-1273 and BNT162b2.
Table A2.
COVID-19 symptomatic infections incidence (%) stratified by age and month.
| Age Group | Sep-25 | Oct -25 | Nov-25 | Dec-25 | Jan -26 | Feb -26 | Mar -26 | Apr -26 | May-26 | Jun -26 | Jul -26 | Aug-26 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 18–49 years | 0.10 | 1.23 | 0.57 | 0.82 | 0.49 | 0.76 | 0.65 | 0.25 | 0.12 | 0.05 | 0.04 | 0.10 |
| 50–59 years | 0.06 | 1.23 | 0.52 | 0.81 | 0.57 | 0.55 | 0.64 | 0.23 | 0.13 | 0.05 | 0.05 | 0.06 |
| 60–100 years | 0.10 | 2.53 | 0.81 | 1.10 | 0.85 | 0.92 | 1.16 | 0.46 | 0.23 | 0.06 | 0.07 | 0.10 |
Table A3.
Probabilistic sensitivity analyses parameters used for comparisons of mRNA-1283 versus mRNA-1273 and mRNA-1283 versus BNT162b2.
Table A3.
Probabilistic sensitivity analyses parameters used for comparisons of mRNA-1283 versus mRNA-1273 and mRNA-1283 versus BNT162b2.
| Variable | Age Group | Point Estimate | Distribution | SE | Details |
|---|---|---|---|---|---|
| COVID incidence rates | All age groups | Age- and month-specific | Normal | 10% | Multiplier applied to all incidence rates to vary them all up or down for a certain percentage. A multiplier of 1.0 represents the base case values. 0.10 or 10% of the multiplier was used as the SE for the multiplier to vary incidence rates in the PSA. |
| Vaccine Waning (intervention): Infections | 18–100 years | 0.048 | N/A | N/A | Set equal to vaccine waning for comparator. Varies as the waning of the comparator varies following [21] |
| Vaccine Waning (intervention): Hospitalizations | 18–100 years | 0.025 | N/A | N/A | Set equal to vaccine waning for comparator. Varies as the waning of the comparator varies following [21] |
| Hospitalization rates | 18–49 years | 0.255% | Beta | 0.0002552 | SE estimated as 10% of the mean. |
| 50–59 years | 0.68% | Beta | 0.00068 | ||
| 60–100 years | 5.89% | Beta | 0.0059 | ||
| Proportion No formal care | NFC: 18–49 years | 80.0% | Beta | 0.0800 | SE estimated as 10% of the mean. |
| NFC: 50–59 years | 78.1% | Beta | 0.0781 | ||
| NFC: 60–100 years | 64.5% | Beta | 0.0645 | ||
| Proportion Outpatient care | OP: 18–49 years | 19.7% | N/A | Calculated as 1- Hospitalization rates—proportion outpatient care. | |
| OP: 50–64 years | 21.3% | N/A | |||
| OP: 65–100 years | 29.6% | N/A | |||
| In-Hospital Level of Care: No ICU or Ventilator, ICU including ICU only and ICU with Ventilator | ICU: 18–49 years | 11.3% | Dirichlet | Alpha = mean × 100 beta = 1 Gamma distribution used to select values for each of the 3 inputs across each age group and then converted to probabilities. Inputs for each age group add to 100%. | |
| ICU: 50–59 years | 11.72% | Dirichlet | |||
| ICU: 60–100 years | 5.79% | Dirichlet | |||
| No ICU or Vent: 18–49 years | 88.57% | Dirichlet | |||
| No ICU or Vent: 50–59 years | 88.28% | Dirichlet | |||
| No ICU or Vent: 60–100 years | 94.21% | Dirichlet | |||
| Probability Readmission | All age groups and level of care | 11.7% | Beta | 0.0117 | SE estimated as 10% of the mean |
| In-hospital mortality: ICU including ICU only and ICU with ventilator | 18–49 years | 0.067 | Dirichlet | alpha = mean × 100 beta = 1 Gamma distribution used to select values for each of the 2 inputs (in hospital mortality and no readmission) across an age group and level of care, then converted to probabilities in conjunction with the rate of readmission to add to 100%. These two probabilities will combine to represent 100%—% readmission. | |
| 50–59 years | 0.151 | Dirichlet | |||
| 60–100 years | 0.437 | Dirichlet | |||
| No readmission or mortality: ICU including ICU only and ICU with ventilator | 18–49 years | 0.816 | Dirichlet | ||
| 50–59 years | 0.733 | Dirichlet | |||
| 60–100 years | 0.446 | Dirichlet | |||
| In-hospital mortality: No ICU or ventilator | 18–49 years | 0.006 | Dirichlet | ||
| 50–59 years | 0.021 | Dirichlet | |||
| 60–100 years | 0.18 | Dirichlet | |||
| No readmission or mortality: No ICU or ventilator | 18–49 years | 0.877 | Dirichlet | ||
| 50–59 years | 0.862 | Dirichlet | |||
| 60–100 years | 0.703 | Dirichlet | |||
| Post-discharge mortality | All age groups and levels of care | 3.80% | Beta | 0.0039% | SE estimated from the upper and lower bounds of the 95%CI (approximated +/−20% of base case) and assuming an approximate normal distribution. |
| Vaccine administration cost | All age groups | €13.67 | Gamma | €1.367 | SE estimated as 10% of the mean. |
| AE related costs | All age groups | €0.26 | Gamma | €0.026 | SE estimated as 10% of the mean. |
| Grade 3 local | €0.26 | €0.026 | |||
| Grade 3 systemic | €339.30 | €33.93 | |||
| Anaphylaxis | €3304.6 | €330.46 | |||
| Myocarditis/Pericarditis | 0 | ||||
| COVID-19 caused myocarditis | All age groups | €6119.5 | Gamma | €611.95 | SE estimated as 10% of the mean. |
| Outpatient care costs | All age group: physician costs | €43.20 | Gamma | €4.32 | SE estimated as 10% of the mean. |
| Hospitalization costs | All age groups: No ICU or Vent | €7052 | Gamma | €705.20 | SE estimated as 10% of the mean. |
| All age groups: ICU including ICU only and ICU with ventilator | €12,650.70 | Gamma | €1260.51 | ||
| Time loss Adverse events (days) | All ages: Any Grade 3 local adverse events | 0 | N/A | 0 | N/A SE estimated as 10% of the mean. |
| All ages: Any Grade 3 systemic adverse events | 0 | N/A | 0 | ||
| All ages: Anaphylaxis | 1 | Gamma | 0.1 | ||
| All ages: Myocarditis/Pericarditis | 3 | Gamma | 0.3 | ||
| Time loss for Acute COVID phase (days) | All ages: Outpatient and not seeking care | 3.5 | Gamma | 0.035 | SE estimated as 10% of the mean. |
| All ages: Symptoms prior to hospitalization | 3.5 | Gamma | 0.035 | ||
| All ages: In hospital stay | 8.43 (no ICU) 16.64 (ICU) | Gamma | 0.0843 (no ICU) 1.664 (ICU) | ||
| All ages: Recovery | 27.0 | Gamma | 2.7 | ||
| All ages: Readmission | 8.43 (no ICU) 16.64 (ICU) | Gamma | 0.843 (no ICU) 1.664 (ICU) | ||
| Time loss due to COVID-19 caused myocarditis | All age groups | 8.82 days | Gamma | 0.882 | SE estimated as 10% of the mean. |
| Daily wage | €208.7 | All ages | Gamma | €20.87 | |
| QALY loss Adverse events | All ages: Any Grade 3 local adverse events | 0.0004 | Beta | 0.00004 | SE estimated as 10% of the mean. |
| All ages: Any Grade 4 local adverse events | 0.0019 | Beta | 0.00019 | ||
| All ages: Any Grade 3 systemic adverse events | 0.0004 | Beta | 0.00004 | ||
| All ages: Any Grade 4 systemic adverse events | 0.0019 | Beta | 0.00019 | ||
| All ages: Anaphylaxis | 0.0019 | Beta | 0.00019 | ||
| All ages: Myocarditis/Pericarditis | 0.0006 | Beta | 0.00006 | ||
| QALY lossCOVID-19 associated myocarditis | All ages | 0.02 | Beta | 0.0002 | SE estimated as 10% of the mean. |
| Non hospitalized patients QALY (18+) | 18+: No formal care | 0.0046 | Beta | 0.00046 | SE estimated as 10% of the mean. |
| 18+: Outpatient care | 0.0046 | Beta | 0.00046 | ||
| Hospitalization QALY losses (18+) | 18+: No ICU or Vent (Symptoms prior to hosp) | 0.000 | Beta | 0.000 | SE estimated as 10% of the mean. |
| 18+: ICU only (Symptoms prior to hosp) | 0.000 | Beta | 0.000 | ||
| 18+: Vent (Symptoms prior to hosp) | 0.000 | Beta | 0.000 | ||
| 18+: No ICU or Vent (In-hospital) | 0.017 | Beta | 0.031 | ||
| 18+: ICU only (In hospital) | 0.039 | Beta | 0.058 | ||
| 18+: Vent (In hospital) | 0.039 | Beta | 0.058 | ||
| Readmission QALY losses (18+) | 18+: No ICU or Vent | 0.0174 | Beta | 0.00174 | SE estimated as 10% of the mean. |
| 18+: ICU only | 0.0394 | Beta | 0.00394 | ||
| 18+: Vent | 0.0394 | Beta | 0.00394 |
CI: confidence interval; hosp: hospitalization; ICU: intensive care unit; N/A, not applicable; QALY: quality-adjusted life-year; SE: standard error.
Table A4.
Probabilistic sensitivity analyses parameters for vaccine effectiveness and vaccine acquisition cost for mRNA-1283 versus mRNA-1273 and mRNA-1283 versus BNT162b2.
Table A4.
Probabilistic sensitivity analyses parameters for vaccine effectiveness and vaccine acquisition cost for mRNA-1283 versus mRNA-1273 and mRNA-1283 versus BNT162b2.
| Scenario: mRNA-1273 Versus mRNA-1283 | |||||
| rVE: Infections | 18–49 years | 0.163 | Beta | 0.0686 | SE estimated from the upper and lower bounds of the 95%CI (including negative estimates for LB) and assuming an approximate normal distribution. |
| 50–59 years | 0.163 | Beta | 0.0686 | ||
| 60–100 years | 0.135 | Beta | 0.0977 | ||
| rVE: Hospitalizations | 18–49 years | 0.381 | Beta | 0.1804 | SE estimated from the upper and lower bounds of the 95%CI (including negative estimates for LB) and assuming an approximate normal distribution. |
| 50–59 years | 0.381 | Beta | 0.1804 | ||
| 60–100 years | 0.381 | Beta | 0.1804 | ||
| 1283 Vaccine Effectiveness: Infections | 18–49 years | 0.566 | N/A | N/A | Calculated based on comparator (i.e., mRNA-1273) VE and rVE selection. Varies as other values vary. Maximum value of 0.99 included in calculations. |
| 50–59 years | 0.566 | ||||
| 60–100 years | 0.607 | ||||
| 1283 Vaccine Effectiveness: Hospitalizations | 18–49 years | 0.694 | N/A | N/A | Calculated based on comparator (i.e., mRNA-1273) VE and rVE selection. Varies as other values vary. Maximum value of 0.99 included in calculations. |
| 50–59 years | 0.694 | ||||
| 60–100 years | 0.735 | ||||
| Scenario: mRNA-1283 versus BNT162b2 | |||||
| rVE: Infections | 18–49 years | 0.190 | Beta | 0.0190 | SE estimated as 10% of the mean. |
| 50–59 years | 0.190 | Beta | 0.0190 | ||
| 60–100 years | 0.228 | Beta | 0.0228 | ||
| rVE: Hospitalizations | 18–49 years | 0.441 | Beta | 0.0441 | SE estimated as 10% of the mean. |
| 50–59 years | 0.441 | Beta | 0.0441 | ||
| 60–100 years | 0.441 | Beta | 0.0441 | ||
| BNT162b2 Vaccine Effectiveness: Infections | 18–49 years | 0.465 | N/A | N/A | Calculated based on comparator (i.e., mRNA-1283) VE and rVE selection. Varies as other values vary. Maximum value of 0.99 included in calculations. |
| 50–59 years | 0.465 | ||||
| 60–100 years | 0.490 | ||||
| BNT162b2 Vaccine Effectiveness: Hospitalizations | 18–49 years | 0.452 | N/A | N/A | Calculated based on comparator (i.e., mRNA-1283) VE and rVE selection. Varies as other values vary. Maximum value of 0.99 included in calculations. |
| 50–59 years | 0.452 | ||||
| 60–100 years | 0.526 | ||||
CI: Confidence interval; N/A, Not applicable; SE: Standard error.
References
- Baden, L.R.; El Sahly, H.M.; Essink, B.; Kotloff, K.; Frey, S.; Novak, R.; Diemert, D.; Spector, S.A.; Rouphael, N.; Creech, C.B.; et al. Efficacy and Safety of the mRNA-1273 SARS-CoV-2 Vaccine. N. Engl. J. Med. 2021, 384, 403–416. [Google Scholar] [CrossRef]
- Polack, F.P.; Thomas, S.J.; Kitchin, N.; Absalon, J.; Gurtman, A.; Lockhart, S.; Perez, J.L.; Pérez Marc, G.; Moreira, E.D.; Zerbini, C.; et al. Safety and Efficacy of the BNT162b2 mRNA COVID-19 Vaccine. N. Engl. J. Med. 2020, 383, 2603–2615. [Google Scholar] [CrossRef]
- Chalkias, S.; Dennis, P.; Petersen, D.; Radhakrishnan, K.; Vaughan, L.; Handforth, R.; Rossi, A.; Wahid, R.; Edwards, D.K.; Feng, J.; et al. Efficacy, immunogenicity, and safety of a next-generation mRNA-1283 COVID-19 vaccine compared with the mRNA-1273 vaccine (NextCOVE): Results from a phase 3, randomised, observer-blind, active-controlled trial. Lancet Infect. Dis. 2025, 25, 1230–1242. [Google Scholar] [CrossRef]
- Scott, J.; Abers, M.S.; Marwah, H.K.; McCann, N.C.; Meyerowitz, E.A.; Richterman, A.; Fleming, D.F.; Holmes, E.J.; Moat, L.E.; Redepenning, S.G.; et al. Updated Evidence for Covid-19, RSV, and Influenza Vaccines for 2025–2026. N. Engl. J. Med. 2025, 393, 2221–2242. [Google Scholar] [CrossRef] [PubMed]
- Zhou, G.; Dael, N.; Verweij, S.; Balafas, S.; Mubarik, S.; Oude Rengerink, K.; Pasmooij, A.M.G.; van Baarle, D.; Mol, P.G.M.; de Bock, G.H.; et al. Effectiveness of COVID-19 vaccines against SARS-CoV-2 infection and severe outcomes in adults: A systematic review and meta-analysis of European studies published up to 22 January 2024. Eur. Respir. Rev. 2025, 34, 240222. [Google Scholar] [CrossRef]
- van Werkhoven, C.H.; Valk, A.W.; Smagge, B.; de Melker, H.E.; Knol, M.J.; Hahné, S.J.; van den Hof, S.; de Gier, B. Early COVID-19 vaccine effectiveness of XBB.1.5 vaccine against hospitalisation and admission to intensive care, the Netherlands, 9 October to 5 December 2023. Eurosurveillance 2024, 29, 2300703. [Google Scholar] [CrossRef] [PubMed]
- Gezondheidsraad. COVID-19-Vaccinatie in 2025. Available online: https://www.gezondheidsraad.nl/site/binaries/site-content/collections/documents/2025/03/27/advies-covid-19-vaccinatie-in-2025/COVID-19-vaccinatie-in-2025-advies.pdf (accessed on 29 January 2026).
- Rijksinstituut voor Volksgezondheid en Milieu (RIVM). Staat van Infectieziekten in Nederland, 2024. RIVM Rapport 2025-0123. Available online: https://www.rivm.nl/bibliotheek/rapporten/2025-0123.pdf (accessed on 29 January 2026).
- Zeevat, F.; van der Pol, S.; Westra, T.; Beck, E.; Postma, M.J.; Boersma, C. Cost-effectiveness Analysis of COVID-19 mRNA XBB.1.5 Fall 2023 Vaccination in the Netherlands. Adv. Ther. 2025, 42, 1550–1569. [Google Scholar] [CrossRef] [PubMed]
- Rijksinstituut voor Volksgezondheid en Milieu (RIVM). Deelname COVID-19-Vaccinatie in Nederland. Available online: https://www.rivm.nl/sites/default/files/2025-12/Deelname-COVID-19-vaccinatie-in-Nederland_20251208.pdf (accessed on 29 January 2026).
- Rijksinstituut voor Volksgezondheid en Milieu (RIVM). Infectie Radar. Available online: https://www.infectieradar.nl/ (accessed on 2 February 2026).
- European Medicines Agency (EMA). mNexspike. Available online: https://www.ema.europa.eu/en/medicines/human/EPAR/mnexspike#overview (accessed on 13 February 2026).
- European Medicines Agency (EMA). Spikevax: Summary of Product Characteristics. Available online: https://www.ema.europa.eu/en/medicines/human/EPAR/spikevax#product-info (accessed on 2 February 2026).
- Food & Drug Administration (FDA). MNEXSPIKE—Package Insert. Available online: https://www.fda.gov/media/186738/download?attachment (accessed on 2 February 2026).
- Kopel, H.; Nguyen, V.H.; Boileau, C.; Bogdanov, A.; Winer, I.; Ducruet, T.; Zeng, N.; Bonafede, M.; Esposito, D.B.; Martin, D.; et al. Comparative Effectiveness of Bivalent (Original/Omicron BA.4/BA.5) COVID-19 Vaccines in Adults. Vaccines 2023, 11, 1711. [Google Scholar] [CrossRef]
- Dickerman, B.A.; Gerlovin, H.; Madenci, A.L.; Kurgansky, K.E.; Ferolito, B.R.; Figueroa Muñiz, M.J.; Gagnon, D.R.; Gaziano, J.M.; Cho, K.; Casas, J.P.; et al. Comparative Effectiveness of BNT162b2 and mRNA-1273 Vaccines in U.S. Veterans. N. Engl. J. Med. 2022, 386, 105–115. [Google Scholar] [CrossRef]
- Dickerman, B.A.; Madenci, A.L.; Gerlovin, H.; Kurgansky, K.E.; Wise, J.K.; Figueroa Muñiz, M.J.; Ferolito, B.R.; Gagnon, D.R.; Gaziano, J.M.; Cho, K.; et al. Comparative Safety of BNT162b2 and mRNA-1273 Vaccines in a Nationwide Cohort of US Veterans. JAMA Intern. Med. 2022, 182, 739–746. [Google Scholar] [CrossRef]
- Kavikondala, S.; Haeussler, K.; Wang, X.; Bausch-Jurken, M.T.; Nassim, M.; Mishra, N.K.; Malmenäs, M.; Sharma, P.; Van de Velde, N.; Green, N.; et al. Comparative Effectiveness of mRNA-1273 and BNT162b2 COVID-19 Vaccines Among Older Adults: Systematic Literature Review and Meta-Analysis Using the GRADE Framework. Infect. Dis. Ther. 2024, 13, 779–811. [Google Scholar] [CrossRef]
- Wang, X.; Pahwa, A.; Bausch-Jurken, M.T.; Chitkara, A.; Sharma, P.; Malmenäs, M.; Vats, S.; Whitfield, M.G.; Lai, K.Z.H.; Dasari, P.; et al. Comparative Effectiveness of mRNA-1273 and BNT162b2 COVID-19 Vaccines Among Adults with Underlying Medical Conditions: Systematic Literature Review and Pairwise Meta-Analysis Using GRADE. Adv. Ther. 2025, 42, 2040–2077. [Google Scholar] [CrossRef]
- Beck, E.; Georgieva, M.; Wang, W.J.; Gomez-Lievano, A.; Wang, H.; Gao, Y.; Kopel, H.; Bausch-Jurken, M.; Patterson-Lomba, O.; Mu, F.; et al. Indirect comparison of the relative vaccine effectiveness of mRNA-1283 vs. BNT162b2 vaccines against symptomatic COVID-19 among US adults. Curr. Med. Res. Opin. 2025, 41, 721–732. [Google Scholar] [CrossRef]
- Fust, K.; Kohli, M.; Joshi, K.; Cartier, S.; Lee, A.; Van de Velde, N.; Weinstein, M.; Beck, E. Modeling the Cost-Effectiveness of the Next-Generation COVID-19 mRNA-1283 vaccine in the United States. J. Med. Econ. 2026, 29, 574–593. [Google Scholar] [CrossRef]
- Fust, K.; Kohli, M.; Cartier, S.; Joshi, K.; Van de Velde, N.; Beck, E.; Blake, M. The potential impact of the next-generation COVID-19 mRNA-1283 vaccine in Canada. J. Med. Econ. 2025, 28, 1440–1450. [Google Scholar] [CrossRef]
- University of Michigan COVID-19 Vaccination Modeling Team. Economic Analysis of an Additional Dose of the 2024–2025 COVID-19 Vaccine. Available online: https://www.cdc.gov/acip/downloads/slides-2024-10-23-24/05-COVID-Prosser-508.pdf (accessed on 7 April 2026).
- Keeling, M.J.; Hill, E.M.; Petrou, S.; Tran, P.B.; Png, M.E.; Staniszewska, S.; Clark, C.; Hassel, K.; Stowe, J.; Andrews, N. Cost-effectiveness of routine COVID-19 adult vaccination programmes in England. Vaccine 2025, 53, 126948. [Google Scholar] [CrossRef]
- Centraal Bureau voor de Statistiek (CBS). Inflation. Available online: https://www.cbs.nl/nl-nl/visualisaties/dashboard-consumentenprijzen (accessed on 2 February 2026).
- Geuzinge, H.A.; El Alili, M.; Enzing, J.J.; Huis In ‘t Veld, L.M.; Knies, S.; de Wit, G.A. The New Dutch Guideline for Economic Evaluations in Healthcare: Taking the Societal Perspective to the Next Level. Value Health 2025, 28, 930–935. [Google Scholar] [CrossRef]
- Kim DeLuca, E.; Gebremariam, A.; Rose, A.; Biggerstaff, M.; Meltzer, M.I.; Prosser, L.A. Cost-effectiveness of routine annual influenza vaccination by age and risk status. Vaccine 2023, 41, 4239–4248. [Google Scholar] [CrossRef] [PubMed]
- de Bruijn, S.; Huiberts, A.J.; Andeweg, S.P.; Hoeve, C.E.; Schipper, M.; Grobbee, D.E.; de Melker, H.E.; van de Wijgert, J.; van den Hof, S.; Knol, M.J.; et al. Post-COVID-19 condition in individuals infected with SARS-CoV-2 in autumn 2023 in the Netherlands: A prospective cohort study with pre- and post-infection data. Lancet Reg. Health–Eur. 2025, 59, 101472. [Google Scholar] [CrossRef] [PubMed]
- Kawai, K.; Muhere, C.F.; Lemos, E.V.; Francis, J.M. Viral Infections and Risk of Cardiovascular Disease: Systematic Review and Meta-Analysis. J. Am. Heart Assoc. 2025, 14, e042670. [Google Scholar] [CrossRef] [PubMed]
- Xie, Y.; Choi, T.; Al-Aly, Z. Long-term outcomes following hospital admission for COVID-19 versus seasonal influenza: A cohort study. Lancet Infect. Dis. 2024, 24, 239–255. [Google Scholar] [CrossRef]
- Vicic, N.; Bogdanov, A.; Zheng, Z.; Ryan, T.; Zeng, N.; Joshi, K.; Lu, T.; Bonafede, M.; Araujo, A.B.; Wilson, A. Evaluating the Effectiveness of 2024–2025 Seasonal mRNA-1273 Vaccination Against COVID-19-Related Hospitalizations and Medically Attended COVID-19 Among Adults Aged ≥ 18 years in the United States: An Observational Matched Cohort Study. Infect. Dis. Ther. 2026, 15, 701–714. [Google Scholar] [CrossRef]
- Higdon, M.M.; Baidya, A.; Walter, K.K.; Patel, M.K.; Issa, H.; Espié, E.; Feikin, D.R.; Knoll, M.D. Duration of effectiveness of vaccination against COVID-19 caused by the omicron variant. Lancet Infect. Dis. 2022, 22, 1114–1116. [Google Scholar] [CrossRef]
- Andersson, N.W.; Thiesson, E.M.; Pihlström, N.; Perälä, J.; Faksová, K.; Gram, M.A.; Poukka, E.; Leino, T.; Ljung, R.; Hviid, A. Comparative effectiveness of monovalent XBB.1.5 containing covid-19 mRNA vaccines in Denmark, Finland, and Sweden: Target trial emulation based on registry data. BMJ Med. 2024, 3, e001074. [Google Scholar] [CrossRef]
- US Food & Drug Administration (FDA). Letters for Myocarditis. Available online: https://www.fda.gov/vaccines-blood-biologics/safety-availability-biologics/fda-approves-required-updated-warning-labeling-mrna-covid-19-vaccines-regarding-myocarditis-and (accessed on 29 January 2026).
- Pijpers, J.; van Roon, A.; van Roekel, C.; Labuschagne, L.; Smagge, B.; Ferreira, J.A.; de Melker, H.; Hahné, S. Determinants of COVID-19 Vaccine Uptake in The Netherlands: A Nationwide Registry-Based Study. Vaccines 2023, 11, 1409. [Google Scholar] [CrossRef] [PubMed]
- Centraal Bureau voor de Statistiek (CBS). Bevolking. Available online: https://www.cbs.nl/nl-nl/visualisaties/dashboard-bevolking (accessed on 2 February 2026).
- Zeevat, F.; Luttjeboer, J.; Paulissen, J.H.J.; van der Schans, J.; Beutels, P.; Boersma, C.; Postma, M.J. Exploratory Analysis of the Economically Justifiable Price of a Hypothetical RSV Vaccine for Older Adults in the Netherlands and the United Kingdom. J. Infect. Dis. 2022, 226, S102–S109. [Google Scholar] [CrossRef] [PubMed]
- Friesema, I.H.; Koppeschaar, C.E.; Donker, G.A.; Dijkstra, F.; van Noort, S.P.; Smallenburg, R.; van der Hoek, W.; van der Sande, M.A. Internet-based monitoring of influenza-like illness in the general population: Experience of five influenza seasons in the Netherlands. Vaccine 2009, 27, 6353–6357. [Google Scholar] [CrossRef]
- Bekker, R.; Uit Het Broek, M.; Koole, G. Modeling COVID-19 hospital admissions and occupancy in the Netherlands. Eur. J. Oper. Res. 2023, 304, 207–218. [Google Scholar] [CrossRef]
- van der Pol, S.; Zeevat, F.; Postma, M.J.; Boersma, C. Cost-effectiveness of high-dose influenza vaccination in the Netherlands: Incorporating the impact on both respiratory and cardiovascular hospitalizations. Vaccine 2024, 42, 3429–3436. [Google Scholar] [CrossRef] [PubMed]
- Zeevat, F.; Luttjeboer, J.; Korsten, K.; van Boven, M.; Postma, M.J.; van der Pol, S.; Boersma, C. Evaluating cost-effectiveness of RSV vaccination strategies for older adults in the Netherlands. Vaccine 2025, 65, 127735. [Google Scholar] [CrossRef]
- StatLine Opendata.CBS.NL. Ziekenhuisopnamen en-Patiënten; Diagnose-Indeling ICD-10 (3-Teken Niveau). Available online: https://opendata.cbs.nl/#/CBS/nl/dataset/84069NED/table?ts=1767789775076 (accessed on 29 January 2026).
- Gezondheidsraad. RSV-Vaccinatie Voor Ouderen. Available online: https://www.gezondheidsraad.nl/site/binaries/site-content/collections/documents/2025/03/27/advies-rsv-vaccinatie-voor-ouderen/RSV-vaccinatie-voor-ouderen_advies.pdf (accessed on 5 February 2026).
- Rijksinstituut voor Volksgezondheid en Milieu (RIVM). Staat van Infectieziekten in Nederland, 2023. RIVM-Rapport 2024-0135. Available online: https://www.rivm.nl/bibliotheek/rapporten/2024-0135.pdf (accessed on 5 February 2026).
- Leijte, W.; Wagemaker, N.M.M.; van Kraaij, T.D.A.; de Kruif, M.D.; Mostard, G.J.M. Sterfte en heropname na ziekenhuisopname met covid-19. Ned. Tijdschr. Geneeskd. 2020, 164, D5423. [Google Scholar]
- Ramzi, Z.S. Hospital readmissions and post-discharge all-cause mortality in COVID-19 recovered patients; A systematic review and meta-analysis. Am. J. Emerg. Med. 2022, 51, 267–279. [Google Scholar] [CrossRef] [PubMed]
- Klein, N. Rapid Cycle Analysis to Monitor the Safety of COVID-19 Vaccines in Near Real-Time Within the Vaccine Safety Datalink: Myocarditis and Anaphylaxis. Presentation to the Advisory Committee on Immunization Practices. Available online: https://stacks.cdc.gov/view/cdc/109493 (accessed on 2 February 2026).
- SNPG.nl. Vergoeding. Available online: https://www.snpg.nl/article/griep-ha-afronden/declareren-griepvaccinaties/vergoeding/ (accessed on 10 April 2026).
- Nederland, Z. Richtlijn voor Het Uitvoeren van Economische Evaluaties in de Gezondheidszorg. Available online: https://www.zorginstituutnederland.nl/documenten/2024/01/16/richtlijn-voor-het-uitvoeren-van-economische-evaluaties-in-de-gezondheidszorg (accessed on 20 June 2023).
- Rozenbaum, M.H.; Mangen, M.J.; Huijts, S.M.; van der Werf, T.S.; Postma, M.J. Incidence, direct costs and duration of hospitalization of patients hospitalized with community acquired pneumonia: A nationwide retrospective claims database analysis. Vaccine 2015, 33, 3193–3199. [Google Scholar] [CrossRef]
- Dagblad van het Noorden. Veel Mensen Die Ziek Zijn Door Post-COVID Gaan Gewoon Naar Hun Werk. Vooral Vrouwen en Hoogopgeleiden. Zo Zit Dat. Available online: https://dvhn.nl/meer/gezond/Een-op-vijf-pati%C3%ABnten-werkt-door-met-post-covid-blijkt-uit-Gronings-onderzoek.-Gezond-is-dat-niet.-Vooral-vrouwen-en-hogeropgeleiden-werken-met-klachten.-Hoe-kan-dat-43254815.html (accessed on 10 April 2026).
- Medicijnkosten.nl. Tramadol HCL/Paracetam Aur Tab Filmomh 37.5/325 mg. Available online: https://www.medicijnkosten.nl/medicijn?artikel=TRAMADOL+HCL%2FPARACETAM+AUR+TAB+FILMOMH+37%2C5%2F325MG&id=07d21c743d7c5877b89d9ef18330e005 (accessed on 10 April 2026).
- StatLine Opendata CBS NL. Werkzame Beroepsbevolking; Arbeidsduur, 2003–2022. Available online: https://opendata.cbs.nl/#/CBS/nl/dataset/82647NED/table (accessed on 10 April 2026).
- Postma, M.J.; Jansema, P.; Scheijbeler, H.W.; van Genugten, M.L. Scenarios on costs and savings of influenza treatment and prevention for Dutch healthy working adults. Vaccine 2005, 23, 5365–5371. [Google Scholar] [CrossRef]
- Chopra, V.; Flanders, S.A.; O’Malley, M.; Malani, A.N.; Prescott, H.C. Sixty-Day Outcomes Among Patients Hospitalized With COVID-19. Ann. Intern. Med. 2021, 174, 576–578. [Google Scholar] [CrossRef] [PubMed]
- van Zon, S. Presentation at ACTION Conference April 13, 2023. Werkfunctioneren en Ziekteverzuim Bij Post-COVID-Syndroom. Available online: https://www.actioncovid.nl/werkfunctioneren (accessed on 10 April 2026).
- Walter, E.B.; Schlaudecker, E.P.; Talaat, K.R.; Rountree, W.; Broder, K.R.; Duffy, J.; Grohskopf, L.A.; Poniewierski, M.S.; Spreng, R.L.; Staat, M.A.; et al. Safety of Simultaneous vs. Sequential mRNA COVID-19 and Inactivated Influenza Vaccines: A Randomized Clinical Trial. JAMA Netw. Open 2024, 7, e2443166. [Google Scholar] [CrossRef] [PubMed]
- University of Michigan COVID-19 Vaccination Modeling Team. Economic Analysis of COVID-19 Vaccination. Available online: https://www.cdc.gov/acip/downloads/slides-2024-06-26-28/05-COVID-Prosser-508.pdf (accessed on 2 February 2026).
- Sandmann, F.G.; Tessier, E.; Lacy, J.; Kall, M.; Van Leeuwen, E.; Charlett, A.; Eggo, R.M.; Dabrera, G.; Edmunds, W.J.; Ramsay, M.; et al. Long-Term Health-Related Quality of Life in Non-Hospitalized Coronavirus Disease 2019 (COVID-19) Cases with Confirmed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection in England: Longitudinal Analysis and Cross-Sectional Comparison with Controls. Clin. Infect. Dis. 2022, 75, e962–e973. [Google Scholar] [CrossRef]
- PHOSP-COVID Collaborative Group. Clinical characteristics with inflammation profiling of long COVID and association with 1-year recovery following hospitalisation in the UK: A prospective observational study. Lancet Respir. Med. 2022, 10, 761–775. [Google Scholar] [CrossRef]
Figure 1.
DSA results for mRNA-1283 versus no vaccination. ICER: incremental cost-effectiveness ratio; VE: vaccine efficacy.
Figure 1.
DSA results for mRNA-1283 versus no vaccination. ICER: incremental cost-effectiveness ratio; VE: vaccine efficacy.
Figure 2.
Cost-effectiveness acceptability curve for mRNA-1283 versus mRNA-1273.
Figure 3.
Cost-effectiveness acceptability curve for mRNA-1283 versus BNT162b2.
Table 1.
Vaccine efficacy of mRNA-1283, mRNA-1273, and BNT162b2 [21].
Table 1.
Vaccine efficacy of mRNA-1283, mRNA-1273, and BNT162b2 [21].
| Age Group (Years) | Comparison of mRNA-1273 & mRNA-1283 | Comparison of mRNA-1283 & BNT162b2 | ||||
|---|---|---|---|---|---|---|
| 2024/25 mRNA-1273 VE | rVE of mRNA-1283 vs mRNA-1273 (95% CI) | mRNA-1283 VE (Range) | mRNA-1283 VE | rVE of mRNA-1283 vs BNT162b2 (95% CI) | BNT162b2 VE (Range) | |
| Symptomatic Infection | ||||||
| 18–59 high-risk | 48.2% | 16.3% (1.8–28.7%) | 56.6% (49.1–63.0%) | 56.6% | 19.0% (4.9–31.0%) | 46.5% (37.2–54.4%) |
| ≥60 | 54.5% | 13.5% (−7.7–30.6%) | 60.7% (50.8–68.4%) | 60.7% | 22.8% (3.7–38.1%) | 49.0% (36.5–59.2%) |
| Hospitalization † | ||||||
| 18–59 high-risk | 50.5% | 38.1% (−6.6–64.1%) | 69.4% (46.3–82.2%) | 69.4% | 44.1% (3.2–67.7%) | 45.2% (5.1–68.3%) |
| ≥60 | 57.2% | 38.1% (−6.6–64.1%) | 73.5% (53.3–84.6%) | 73.5% | 44.1% (3.2–67.7%) | 52.6% (17.9–72.6%) |
† If VE against hospitalization is lower than VE against infection, the incremental protection against the probability of hospitalization given infection is set to 0. This assumption is aligned with Fust et al. 2026 [21], and is based on the observation that mRNA COVID-19 vaccines showed consistently higher protection against severe COVID-19 disease (i.e., hospitalization and death) than against COVID-19 infection. CI: confidence interval; rVE: relative vaccine effectiveness; VE: vaccine effectiveness; vs: versus.
Table 2.
Impact of mRNA-1283 versus no vaccination.
| Base Case | High Incidence | Low Incidence | ||||
|---|---|---|---|---|---|---|
| No Vaccine | mRNA-1283 | No Vaccine | mRNA-1283 | No Vaccine | mRNA-1283 | |
| Symptomatic infections | 459,068 | 391,139 | 655,697 | 558,682 | 262,371 | 223,543 |
| Averted | 67,929 | 97,015 | 38,828 | |||
| Hospitalizations | 23,830 | 18,455 | 34,037 | 26,359 | 13,620 | 10,548 |
| Averted | 5375 | 7677 | 3072 | |||
| Deaths | 5348 | 4137 | 7638 | 5908 | 3057 | 2364 |
| Averted | 1211 | 1730 | 692 | |||
| Treatment costs (€) | 346,486,776 | 279,941,386 | 494,893,571 | 399,850,768 | 198,027,466 | 159,992,774 |
| Averted | 66,545,390 | 95,042,961 | 38,034,692 | |||
| QALY loss | 43,921 | 34,254 | 62,732 | 48,890 | 25,103 | 19,613 |
| QALY gain | 9667 | 13,842 | 5490 | |||
| EJP (WTP €50k) | €237.93 | €349.47 | €126.34 | |||
EJP: economically justifiable price; k: thousand; QALY: quality-adjusted life-year; WTP: willingness-to-pay.
Table 3.
Additional scenario analyses of mRNA-1283 versus no vaccination.
| Hospitalizations Averted | Deaths Averted | EJP (WTP €50,000/QALY) | |
|---|---|---|---|
| Base case | 5375 | 1211 | 237.93 |
| VE infection and hospitalization 95% CI lower bound | 3754 | 846 | 160.70 |
| VE infection and hospitalization 95% CI upper bound | 6693 | 1508 | 301.05 |
| rVE hospitalization = rVE infection | 4532 | 1021 | 199.27 |
| VCR − 20% | 4300 | 969 | 237.93 |
| VCR + 20% | 6451 | 1453 | 237.93 |
| Expand to all 50–59-year-olds | 5481 | 1219 | 186.54 |
| ≥75 years only | 2779 | 628 | 371.03 |
| Post-COVID-19 condition | Additional 2265 post-COVID-19 condition cases prevented | 241.96 | |
EJP: economically justifiable price; QALY: quality-adjusted life-year; WTP: willingness-to-pay.
Table 4.
Impact of mRNA-1283 versus mRNA-1273.
| Base c. | High Incidence | Low Incidence | Lower Bound rVE | Upper Bound rVE | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| mRNA-1273 | mRNA-1283 | mRNA-1273 | mRNA-1283 | mRNA-1273 | mRNA-1283 | mRNA-1273 | mRNA-1283 | mRNA-1273 | mRNA-1283 | |
| Symptomatic infections | 400,070 | 391,139 | 571,437 | 558,682 | 228,648 | 223,543 | 400,070 | 405,036 | 400,070 | 380,290 |
| Averted | 8931 | 12,755 | 5105 | −4966 | 19,780 | |||||
| Hospitalizations | 19,764 | 18,455 | 28,230 | 26,359 | 11,296 | 10,548 | 19,764 | 20,077 | 19,764 | 17,563 |
| Averted | 1309 | 1871 | 748 | −312 | 2201 | |||||
| Deaths | 4432 | 4137 | 6330 | 5908 | 2533 | 2364 | 4432 | 4502 | 4432 | 3936 |
| Averted | 295 | 422 | 169 | −70 | 496 | |||||
| Treatment costs | 294,856,989 | 280,113,088 | 421,155,221 | 400,096,059 | 168,517,334 | 160,090,990 | 294,856,989 | 298,821,108 | 294,856,989 | 269,157,438 |
| Averted | 14,743,901 | 21,059,162 | 8,426,344 | −3,964,119 | 25,699,552 | |||||
| QALY loss | 36,571 | 34,248 | 52,206 | 45,787 | 20,930 | 19,609 | 36,571 | 37,159 | 36,571 | 32,633 |
| QALY gain | 2323 | 3325 | 1321 | −588 | 3938 | |||||
| Incremental EJP (WTP 50k) | €61.53 | €88.06 | €35.00 | NA | €104.65 | |||||
| Incremental EJP (WTP 20k) | €28.77 | €41.16 | €16.37 | NA | €49.11 | |||||
EJP: economically justifiable price; k: thousand; NA: indicates negative incremental EJP of mRNA-1283 over mRNA-1273; QALY: quality-adjusted life-year; rVE: relative vaccine efficacy; WTP: willingness-to-pay.
Table 5.
Impact of mRNA-1283 versus BNT162b2.
| Base Case | High Incidence | Low Incidence | Lower Bound rVE | Upper Bound rVE | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| BNT162b2 | mRNA-1283 | BNT162b2 | mRNA-1283 | BNT162b2 | mRNA-1283 | BNT162b2 | mRNA-1283 | BNT162b2 | mRNA-1283 | |
| Symptomatic infections | 407,637 | 391,139 | 582,245 | 558,682 | 232,973 | 223,543 | 393,312 | 391,139 | 424,954 | 391,139 |
| Averted | 16,499 | 23,563 | 9430 | 2173 | 33,815 | |||||
| Hospitalizations | 20,134 | 18,455 | 28,757 | 26,359 | 11,507 | 10,548 | 18,527 | 18,455 | 21,424 | 18,455 |
| Averted | 1679 | 2398 | 959 | 72 | 2969 | |||||
| Deaths | 4515 | 4137 | 6448 | 5908 | 2580 | 2364 | 4153 | 4137 | 4806 | 4137 |
| Averted | 378 | 540 | 216 | 16 | 669 | |||||
| Treatment costs | 299,940,303 | 280,113,232 | 428,415,830 | 400,096,059 | 171,422,591 | 160,090,990 | 281,291,036 | 280,113,232 | 316,075,383 | 280,113,232 |
| Averted | €19,827,071 | €28,319,771 | €11,331,602 | €1,177,805 | €35,962,152 | |||||
| QALY loss | 37,253 | 34,248 | 53,181 | 48,881 | 21,319 | 19,609 | 34,368 | 34,248 | 39,598 | 34,248 |
| QALY gain | 3005 | 4300 | 1710 | 120 | 5350 | |||||
| Incremental EJP (WTP 50k) | €79.96 | €114.38 | €45.52 | €3.37 | €142.67 | |||||
| Incremental EJP (WTP 20k) | €37.57 | €53.74 | €21.40 | €1.68 | €67.21 | |||||
EJP: economically justifiable price; k: thousand; QALY: quality-adjusted life-year; rVE: relative.
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MDPI and ACS Style
van der Pol, S.; Beck, E.; Westra, T.; Postma, M.; Boersma, C. Potential Public Health and Economic Impact of the Next-Generation COVID-19 Vaccine mRNA-1283 in The Netherlands. Vaccines 2026, 14, 364. https://doi.org/10.3390/vaccines14040364
AMA Style
van der Pol S, Beck E, Westra T, Postma M, Boersma C. Potential Public Health and Economic Impact of the Next-Generation COVID-19 Vaccine mRNA-1283 in The Netherlands. Vaccines. 2026; 14(4):364. https://doi.org/10.3390/vaccines14040364
Chicago/Turabian Stylevan der Pol, Simon, Ekkehard Beck, Tjalke Westra, Maarten Postma, and Cornelis Boersma. 2026. "Potential Public Health and Economic Impact of the Next-Generation COVID-19 Vaccine mRNA-1283 in The Netherlands" Vaccines 14, no. 4: 364. https://doi.org/10.3390/vaccines14040364
APA Stylevan der Pol, S., Beck, E., Westra, T., Postma, M., & Boersma, C. (2026). Potential Public Health and Economic Impact of the Next-Generation COVID-19 Vaccine mRNA-1283 in The Netherlands. Vaccines, 14(4), 364. https://doi.org/10.3390/vaccines14040364
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