Evaluation of the public health and economic impact of universal influenza vaccination in Mexico

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Although vaccination is the most effective intervention to mitigate its impact, current strategies offer room for enhancement. This study evaluates the potential health and economic benefits of adopting a Universal Influenza Vaccination (UIV) strategy in Mexico. Methods To evaluate the potential impact of a UIV program during a typical influenza season, we conducted a retrospective analysis applying United States vaccination coverage rates to age groups not currently targeted by Mexico’s national immunization strategy. An epidemiological model was developed to simulate influenza transmission and vaccination effects. Outputs from this model were subsequently integrated into a health economic framework populated with local data. Both deterministic and probabilistic sensitivity analyses were conducted to explore parameter uncertainty and assess the robustness of the results. Results During a typical influenza season, implementation of the UIV strategy was projected to reduce disease burden, with an estimated 57.94% decrease in influenza cases (95% CI: 40.56%–71.21%). This translated into reductions of 57.65% (40.32%–70.93%) fewer medical consultations, 56.23% (39.86%–69.05%) in hospital admissions and 55.53% (39.42%–68.56%) in influenza-attributable mortality. The intervention also yielded notable health benefits, including a 56.36% (40.21%–69.2%) decrease in life-years lost and a 57.3% (40.45%–70.37%) reduction in QALYs lost. These outcomes were observed across both vaccinated and unvaccinated populations, suggesting significant indirect (herd) protection. From an economic standpoint, the strategy was associated with cost savings of USD 321.22 million from the third-party payer perspective and USD 388.96 million from the broader societal perspective. Conclusion Expanding influenza immunization through a UIV program in Mexico may significantly reduce the disease burden and associated healthcare costs. The findings suggest that broader vaccine coverage could be a cost-effective and impactful strategy to improve population health outcomes. Influenza Vaccination Mexico Epidemiological modeling Health economic analysis Public health Figures Figure 1 Figure 2 Introduction Seasonal influenza causes 1 billion cases annually worldwide, of which up to 5 million are severe, and between 291,000 and 645,000 influenza-related deaths [1,2]. Although all individuals are at risk, vaccination recommendations primarily focus on groups with a higher risk of complications [3]. However, many cases occur in healthy, economically active adults, resulting in an average of 175,000 deaths annually from 1999 to 2015[2,4] and causing a significant impact on quality of life and the economy [5]. In Mexico, influenza and pneumonia remain among the ten leading causes of death. Between 2010 and 2019, an estimated 73,459 to 101,114 hospitalizations and 15,620 to 31,081 deaths were reported annually [6,7]. Although influenza circulation decreased during the SARS-CoV-2 pandemic [8], the 2022–2023 season had the highest number of cases since the 2009 pandemic [9]. In Mexico, influenza vaccination is primarily targeted at children aged 6 to 59 months, adults aged 60 years and older, and individuals aged 5 to 59 years who are at high risk for influenza-related complications (approximately 7% of this age group) [10], resulting in an overall vaccine coverage of approximately 25% of the general population, with an estimated 33 to 35 million doses administered each influenza season [11]. however, most hospitalizations and deaths occur in unvaccinated individuals [12,13]. The "Global Influenza Strategy 2019–2030" and its perspective for Latin America emphasize the importance of enhancing influenza prevention, detection, control, and treatment, reinforcing the need to strengthen the epidemiological surveillance and to assess the burden of disease and its economic impact [1,14]. To augment the prevention of influenza, Mexican experts have proposed universal influenza vaccination from 6 months of age [15]. The United States experience and other international studies demonstrate the potential benefits of such an approach [16–19]. Some Mexican studies have identified opportunities to improve protection [20–22], however, these analyses are limited to specific strategies and rely on static models, which do not capture the indirect benefits of vaccination, such as the protection conferred to unvaccinated individuals through reduced transmission [23,24]. From a societal perspective, and considering US vaccination coverage rates as a possible target for universal influenza vaccination in Mexico, this study aims to estimate, for a typical influenza season, the potential health and economic benefits of transitioning to a universal influenza vaccination strategy, irrespective of vaccine formulation, as the modeling focuses on the overall impact of increased coverage Methods and material Epidemiological Model A dynamic epidemiological, influenza transmission model has been developed to accurately assess the impact of influenza vaccination. It is composed of two sub-models; both split the population into compartments based on their status regarding the disease. Individuals may be either susceptible to infection (S), exposed but not infectious (E), infected and infectious (I) or immune to infection (recovered; R). One sub-model considers the non-vaccinated population, the other the vaccinated one (Supplemental Fig. 1). In addition, the population is stratified into 7 age-groups (0-4yo, 5-19yo, 20-29yo, 30-39yo, 40-49yo, 50–59, 60 and older) derived from the national population database ( Consejo Nacional de Población – CONAPO ) [25]. As the model is age-structured, it uses an age-dependent contact matrix adapted to the given age-groups from the contact matrix for Mexico estimated by Prem et al. [26]. The dynamic transmission model was calibrated to reproduce the yearly influenza incidence under current vaccination coverage levels. To reflect real-world epidemiological variability, we defined three incidence scenarios: a typical season, based on the average annual incidence from 2015 to 2020; a high-incidence season, based on data from 2015–2016; and a low-incidence season, based on 2017–2018. Full details and results for the high- and low-incidence scenarios are provided in Additional file 1. The probability of transmission per contact was adjusted accordingly in each scenario to reflect the observed burden of disease. Probabilities of influenza transmission upon contact are inferred using a Bayesian inference framework (dust, mcstate). Health-Economic model A health economic model was developed to estimate the health and economic outcomes associated with each vaccination strategy, based on the outputs of the epidemiological model. The model is a decision tree structured by age groups, aligned with those described previously. Age-specific influenza cases estimated by the epidemiological model were translated into transition probabilities of general practitioner (GP) consultations, hospitalizations and deaths, and outcomes expressed in terms of life-years lost, and quality-adjusted life-years (QALYs) lost. The model also calculated the direct medical costs related to these outcomes, as well as indirect costs associated with productivity losses due to illness and death. See Supplemental Fig. 2. As this analysis is retrospective in nature, future costs and health outcomes were not projected and therefore were not subjected to discounting. However, consistent with national guidelines, life-years (LYs) and QALYs lost due to influenza-related mortality were discounted at an annual rate of 5% [27]. Influenza incidence Estimating the real burden of influenza is a necessary step before trying to evaluate the performance of strategies aiming at reducing it. In Mexico, influenza epidemiological surveillance mainly relies on the reporting of outpatient cases (10% are sampled for laboratory tests), as well as hospitalizations and deaths who meet the case definition for influenza like illness (ILI) or severe acute respiratory infections (SARI) [28]. But limitations due to the heterogeneity of the healthcare systems (public/private, primary to third care clinics overlapping different pools of potential patients) make estimates of influenza incidence based on this system unreliable. In our analysis, the incidence estimation was based on a previously used methodology [20,29]. that derives average incidence or attack rates based from report of placebo arms of previous clinical trials [30–32]. These estimates can be considered representative of a typical-influenza season. These rates were distributed across the 2015–2020 seasons using a locally derived coefficient, calculated by dividing the number of cases reported in a given season [9] by the average number of cases per season during the modeled period. This method allows the estimation of influenza incidence per season and age-group as given in Table 1 . We then used the weekly proportion of influenza positive tests reported to the national surveillance system of respiratory diseases (SISVEFLU and SISVER by their Spanish acronyms) [12] and combined it with the yearly incidence estimated previously to compute the weekly incidence over the period. Table 1 Estimations of symptomatic influenza incidence by age-groups and influenza season in Mexico. Average* Cases reported by season Season severity coefficient ≤ 4 years 5–19 years 20–29 years 30–39 years 40–49 years 50–59 years ≥ 60 years 6675 1.00 20.71% 15.92% 2.68% 2.68% 2.68% 2.68% 5.44% 2015–2016 9641 1.44 29.92% 23.00% 3.86% 3.86% 3.86% 3.86% 7.85% 2016–2017 6371 0.95 19.77% 15.20% 2.55% 2.55% 2.55% 2.55% 5.19% 2017–2018 3692 0.55 11.46% 8.81% 1.48% 1.48% 1.48% 1.48% 3.01% 2018–2019 7467 1.12 23.17% 17.81% 2.99% 2.99% 2.99% 2.99% 6.08% 2019–2020 6205 0.93 19.25% 14.80% 2.49% 2.49% 2.49% 2.49% 5.05% 2020–2021 7 0.00 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2021–2022 3176 0.52 10.80% 8.30% 1.39% 1.39% 1.39% 1.39% 2.83% * 2020 to 2022 seasons were excluded from the analysis to avoid biasing the results due to the uncommon nature of influenza circulation during COVID-19 pandemic Vaccination efficacy and coverage rates scenarios Historical vaccine coverage rates (VCRs) were estimated using official records of influenza vaccine doses administered, as reported by national health authorities [11], in combination with demographic data from the National Population Council (CONAPO) database [25]. To estimate age-specific coverage among high-risk populations, administered doses were proportionally distributed by age group based on population size and the estimated prevalence of high-risk conditions, following the methodology outlined by Tapia-Conyer et al., [33]. Table 2 presents the average VCRs across the seasons analyzed for both the base case (reflecting historical vaccination practices) and the proposed universal vaccination strategy. The universal vaccination scenario assumes current VCRs for the youngest (6 months to 4 years) and oldest (≥ 60 years) age groups and extrapolates coverage for other age cohorts using data from the U.S. CDC’s National Immunization Survey-Flu for the 2022–2023 season. Specifically, data included individuals from birth up to 17 years of age, with coverage rates for those aged 6 months to 17 years derived from pediatric estimates [34], while adult coverage was based on reported uptake among those aged 18–49 and 50–64 years [35]. Coverage rates are reported as the percentage of the target population who completed the full vaccination schedule. Table 2 VCRs average across influenza seasons by age group Age group (years) 6 months – 4 y 5–19 20–29 30–39 40–49 50–59 60 + General population Base case scenario 80.23% 5.25% 7.40% 8.68% 13.52% 26.16% 90.93% 24.13% Universal Vaccination 80.23% 55.10% 36.20% 36.20% 36.20% 51.80% 90.93% 52.09% In our analysis we assume that vaccination campaigns start every year on week 40 and that 80% of the targeted population is vaccinated at the end of December (week 52), then the rest (20%) vaccinated from January to March. Age-specific influenza vaccine efficacy estimates were obtained from Clements et al. assuming overall efficacy in the absence of B-lineage mismatch. Reported efficacy values were 60% for children under 5 years, 64% for individuals aged 5–49 years, 63% for those aged 50–64 years, and 60% for adults aged 65 years and older [36]. Health-economic model inputs Probabilities of General Practitioner (GP) visits, hospitalizations, and deaths related to influenza were estimated using data from the US population [37], due to the lack of publicly available data for Mexico. GP visit probabilities were adjusted to reflect Mexico’s lower doctor visit rate per capita compared to the U.S., based on 2021 national statistics [38]. Hospitalization and mortality rates were not adjusted, under the assumption that these outcomes are comparable between countries. In the absence of disaggregated data, these estimates were also applied to high-risk populations as a conservative approach (see Table 3 for details). These epidemiological probabilities constitute key drivers of the economic model, as they determine the expected number of healthcare events attributable to influenza in each age group. When combined with unit costs (GP visits, hospitalizations, productivity losses) and health utility parameters (baseline QALYs and QALY losses per episode), they allow estimation of total direct medical costs, indirect costs, and quality-adjusted life years (QALYs) lost. All cost estimates are expressed in 2023 U.S. dollars (USD), reflecting a typical influenza season from a retrospective perspective. Unit costs for GP consultations and hospitalizations were sourced from public social security institutions in Mexico [39]. Hospitalization costs were calculated based on unitary costs and the average length of stay for influenza cases by age group, using discharge data from 2008 to 2021 [7]. The cost of workdays lost was valued using the average daily wage in Mexico between January and August 2023, as reported by the Ministry of Labor and Social Welfare, and was applied only to individuals of working age [40]. An average exchange rate for the second quarter of 2023 (1 USD = 17.07 MXN) was applied to convert all costs from Mexican pesos to U.S. dollars [41]. Model estimates that include vaccine acquisition and administration costs are reported separately in Supplemental Table 2. These figures are based on assumptions due to confidential pricing agreements established through a public-private partnership in Mexico and therefore may not reflect actual market conditions [42]. Workdays lost consider the absenteeism and presenteeism reported by Zumofen et al., including the missed days of caregivers for caring sick children [4], these days were adjusted by work effectiveness during presenteeism [43] and age-specific economic activity rates from the 2022 National Survey of Occupation and Employment [44]. Finally utility measures for the general population specific to Mexico are taken from GBD database [45] and Influenza-related QALY lost estimates in our model are derived from a Spanish longitudinal study by Hollmann et al., which used EQ-5D scores to measure health-related quality of life (HRQL) in hospitalized and ambulatory patients with influenza (H1N1) 2009. The study calculated “disutility” as the difference between pre-episode and during-episode EQ-5D utility indices and converted these into QALYs lost by incorporating the LYs factor in this context, the duration of the episode in days, using the formula DQ = Du × d / 365. Mean disutility was 0.58 for hospitalized and 0.43 for ambulatory patients, corresponding to QALYs lost of 0.031 and 0.009, respectively [46]. Table 3 Health Economic Model Input Values Variable Age group Value Min Max Distribution Reference Probability of a GP visit per flu case 0-4y 0.32632 -20% + 20% Beta [43], [44] 5-19y 0.22758 20-29y 0.22448 30-39y 0.22448 40-49y 0.22448 50-59y 0.22448 60p 0.37433 Probability of hospitalization per flu infection 0-4y 0.01410 [43] 5-19y 0.00109 20-29y 0.00420 30-39y 0.00420 40-49y 0.00420 50-59y 0.01930 60p 0.03482 Probability of death per flu infection 0-4y 0.00004 5-19y 0.00002 20-29y 0.00009 30-39y 0.00009 40-49y 0.00009 50-59y 0.00134 60p 0.00839 Cost (USD) per GP visits* All age-groups $ 74.55 -20% + 20% Lognormal [45], [53] Cost (USD) per Hosp visits 0-4y $ 3,899.24 -30% + 30% Lognormal [45], [7] 5-19y $ 3,015.40 20-29y $ 3,304.45 30-39y $ 4,637.50 40-49y $ 5,068.48 50-59y $ 5,435.15 60p $ 5,030.99 Work day cost All age-groups $ 28.04 -20% + 20% Lognormal [46] Workday loss per symptomatic influenza episode 0-4y 1.06 0.5 3.7 Lognormal [4], [49], [50]. 5-19y 1.06 0.5 3.7 20-29y 1.96 0.5 5.3 30-39y 2.29 0.5 5.3 40-49y 2.30 0.5 5.3 50-59y 2.08 0.5 5.3 60p 1.00 0.5 2 Baseline utility (QALYs) 0-4y 75.35 -20% + 20% Lognormal [51], [54] 5-19y 66.07 20-29y 52.49 30-39y 42.63 40-49y 33.31 50-59y 24.62 60p 11.40 QALY lost per medically-attended influenza episode Inpatients. All age-groups 0.031 0.0025 0.037 Lognormal [52] Outpatients. All age-groups 0.009 0.007 0.011 Lognormal * The GP costs also consider a treatment with oseltamivir according to National Guidelines of flu treatment [47]. An average cost of $ 10.81 USD in line with prices of national consolidated purchases [53] was added on top of GP visit cost. Sensitivity analysis We conducted univariate sensitivity analyses on key clinical and economic parameters detailed in Table 3 , with results presented as Tornado diagrams. Variables with no impact on the economic outcomes, such as mortality-related parameters and quality of life losses, were excluded from this analysis. In addition, alternative vaccine coverage levels were explored to assess their impact on model results. Vaccine effectiveness (VE) was not varied independently in the univariate sensitivity analysis because it was embedded within the transmission dynamics and model calibration process to reproduce observed epidemiological patterns. Varying VE in isolation would disrupt the internally calibrated relationship between transmission parameters and observed incidence. Therefore, uncertainty related to VE is reflected indirectly through the model’s probabilistic structure and calibration framework. Finally, Additional file 1 provides: Results from two targeted vaccination strategies focused on specific age groups, as a potential stepwise approach toward universal vaccination. Scenario analyses for influenza seasons with lower and higher incidence, corresponding respectively to the 2017–2018 and 2015–2016 seasons. Results Model calibration for the study period. As illustrated in Fig. 1 . Cumulative incidence of symptomatic Influenza cases by season per age-group and for all age groups., the influenza transmission model accurately reproduced age-specific influenza incidence across multiple seasons included in the analysis. However, the complex and variable epidemiological patterns observed in tropical settings, particularly the occurrence of multiple peaks within a single year, led to some degree of under or overestimation in certain age groups and seasons. The overall mean absolute error (MAE), which quantifies the average discrepancy between model predictions and observed data, was highest among children aged 0–4 years and adults aged 40–49 years (MAE: 8%), and lowest in the ≥ 60-year age group (MAE: 1.13%). When averaged across all age groups and seasons, the MAE was 2.75%, indicating good model fit. *The black dots correspond to observed symptomatic influenza incidence, while the bars stand for the incidence estimated by the model. Impact of Universal Vaccination on Health Outcomes The implementation of a UIV program led to substantial and consistent reductions in the overall burden of disease, highlighting its potential as a transformative public health intervention as shown in Table 4 . The model estimated a reduction of 7.68 million symptomatic cases (95% CI: 5.33–8.32 million), corresponding to a 58.72% decrease (95% CI: 26.88%–109.22%) compared to current coverage levels. This reduction was observed across all age groups and was particularly pronounced among individuals aged 5–19 and 40–49 years, two demographic groups characterized by high social mobility and contact rates that may contribute substantially to viral transmission. Although the upper bound of the 95% confidence interval for the relative reduction exceeded 100%, this reflects the probabilistic structure of the model and variability in simulated incidence scenarios rather than a literal reduction beyond the total number of cases. Across all simulations, the effect consistently favored universal vaccination. These findings indicate both direct protection among vaccinated individuals and indirect (herd) effects that enhance population-level impact. The model estimated a reduction of 7.68 million symptomatic cases (95% CI: 5.33–8.32 million), which translates into a 58.72% (95% CI: 26.88%-109.22%) decrease compared to current coverage levels. This significant drop in incidence was observed across all age groups, suggesting a strong population-wide effect. This effect was particularly notable among individuals aged 5–19 and 40–49 years; two demographic groups with high social mobility and contact rates, which may act as key transmitters of the virus. The reductions in healthcare utilization further underscore the potential system-level benefits. A decrease of 1.85 million general practitioner (GP) consultations (95% CI: 1.28–2.02 million) and 41,000 hospitalizations (95% CI: 27,000–49,000). In terms of severe outcomes, the prevention of approximately 3,050 deaths (95% CI: 2,000–3,700) is a critical finding. While influenza-related mortality disproportionately affects older adults and individuals with comorbidities, the overall decline suggests that broader coverage could significantly mitigate the risk of fatal outcomes across the population. Reductions in years of LY lost (48,000; CI: 32,000–58,000) and QALY lost (109,000; 95% CI: 74,000–123,000) further illustrate the health gains from a universal approach. From a societal perspective, the avoidance of 2.63 million workdays lost (95% CI: 1.79–2.92 million) reveals the far-reaching economic implications of the intervention. Table 4 Predicted outcomes of Universal Influenza Vaccination Outcome Universal influenza vaccination Base case scenario (current coverage) Difference Relative reduction Symptomatic 0–4 y 635000 [254000 ; 1466000] 1364000 [739000 ; 2337000] 738000 [478000 ; 897000] 54.11% [20.49%; 121.39%] 5–19 y 2742000 [1136000 ; 5581000] 6708000 [4104000 ; 9413000] 3928000 [2936000 ; 4143000] 58.56% [31.20%; 71.46% 20–29 y 423000 [166000 ; 992000] 1061000 [565000 ; 1823000] 644000 [394000 ; 848000] 60.70% [22.03%; 150.09%] 30–39 y 498000 [197000 ; 1124000] 1204000 [665000 ; 1960000] 712000 [463000 ; 854000] 59.14% [23.60%; 91.73%] 40–49 y 697000 [281000 ; 1502000] 1619000 [935000 ; 2474000] 933000 [645000 ; 1e + 06] 57.63% [26.09% ; 42.78%] 50–59 y 258000 [102000 ; 592000] 639000 [347000 ; 1070000] 385000 [242000 ; 487000] 60.25% [22.60%; 140.35%] 60 + y 217000 [86000 ; 497000] 478000 [263000 ; 810000] 265000 [174000 ; 322000] 55.44% [21.48% ; 122.02%] Total 5469000 [2220000 ; 11755000] 13074000 [7623000 ; 19886000] 7677000 [5334000 ; 8320000] 58.72% [26.88%; 109.22%] GP consultations 0–4 y 207000 [83000 ; 478000] 445000 [241000 ; 763000] 241000 [156000 ; 293000] 54.16% [20.47%; 121.18%] 5–19 y 624000 [258000 ; 1270000] 1527000 [934000 ; 2142000] 894000 [668000 ; 943000] 58.55% [31.18%; 101.01%] 20–29 y 95000 [37000 ; 223000] 238000 [127000 ; 409000] 144000 [88000 ; 190000] 60.50% [21.52%; 149.80%] 30–39 y 112000 [44000 ; 252000] 270000 [149000 ; 440000] 160000 [104000 ; 192000] 59.26% [23.64%; 128.36%] 40–49 y 157000 [63000 ; 337000] 364000 [210000 ; 555000] 209000 [145000 ; 224000] 57.42% [26.11%; 106.82%] 50–59 y 58000 [23000 ; 133000] 143000 [78000 ; 240000] 86000 [54000 ; 109000] 60.14% [22.65%; 140.12%] 60 + y 81000 [32000 ; 186000] 179000 [98000 ; 303000] 99000 [65000 ; 120000] 55.31% [21.92%; 120.83%] Total 1333000 [541000 ; 2880000] 3166000 [1839000 ; 4852000] 1850000 [1281000 ; 2017000] 58.48% [25.08%; 114.95%] Hospitalizations 0–4 y 9000 [4000 ; 21000] 19000 [10000 ; 33000] 10000 [7000 ; 13000] 52.63% [21.21%; 130.00%] 5–19 y 3000 [1000 ; 6000] 7000 [4000 ; 10000] 4000 [3000 ; 4000] 57.14% [30.00%; 100.00%] 20–29 y 2000 [1000 ; 4000] 4000 [2000 ; 8000] 3000 [2000 ; 4000] 75.00% [25.00%; 200.00%] 30–39 y 2000 [1000 ; 5000] 5000 [3000 ; 8000] 3000 [2000 ; 4000] 60.00% [25.00%; 133.33%] 40–49 y 3000 [1000 ; 6000] 7000 [4000 ; 10000] 4000 [3000 ; 4000] 57.14% [30.00%; 100.00%] 50–59 y 5000 [2000 ; 11000] 12000 [7000 ; 21000] 7000 [5000 ; 9000] 58.33% [23.81%; 142.86%] 60 + y 8000 [3000 ; 17000] 17000 [9000 ; 28000] 9000 [6000 ; 11000] 52.94% [21.43%; 122.22%] Total 31000 [12000 ; 71000] 72000 [40000 ; 118000] 41000 [27000 ; 49000] 56.94% [22.97%; 122.50%] Deaths 0–4 y 30 [10 ; 60] 50 [30 ; 90] 30 [20 ; 40] 60.00% [22.22%; 133.33%] 5–19 y 60 [20 ; 120] 140 [90 ; 190] 80 [60 ; 90] 57.14% [33.33%; 88.89%] 20–29 y 40 [10 ; 90] 100 [50 ; 160] 60 [40 ; 80] 60.00 [25.00%; 160.00%] 30–39 y 40 [20 ; 100] 110 [60 ; 180] 60 [40 ; 80] 54.55% [22.22%; 133.33%] 40–49 y 60 [30 ; 140] 150 [80 ; 220] 80 [60 ; 90] 53.33% [27.27%; 112.50%] 50–59 y 350 [140 ; 790] 860 [460 ; 1430] 520 [320 ; 650] 60.47% [22.54%; 141.30%] 60 + y 1810 [720 ; 4150] 4000 [2200 ; 6780] 2210 [1460 ; 2690] 55.25% [21.55%; 122.27%] Total 2390 [950 ; 5450] 5400 [2980 ; 9060] 3050 [2000 ; 3700] 56.48% [20.10%; 185.00%] LYs lost 0–4 y 1000 [0 ; 2000] 2000 [1000 ; 3000] 1000 [1000 ; 1000] 50.00% [33.33%; 33.33%] 5–19 y 2000 [1000 ; 4000] 5000 [3000 ; 6000] 3000 [2000 ; 3000] 60.00% [50.00%; 60.00%] 20–29 y 1000 [0 ; 3000] 3000 [2000 ; 5000] 2000 [1000 ; 2000] 66.67% [40.00%; 66.67%] 30–39 y 1000 [1000 ; 3000] 3000 [2000 ; 5000] 2000 [1000 ; 2000] 66.67% [40.00%; 66.67%] 40–49 y 2000 [1000 ; 3000] 4000 [2000 ; 6000] 2000 [1000 ; 2000] 50.00% [16.67%; 100.00%] 50–59 y 7000 [3000 ; 17000] 18000 [10000 ; 31000] 11000 [7000 ; 14000] 61.11% [22.58%; 140.00%] 60 + y 23000 [9000 ; 52000] 50000 [28000 ; 85000] 28000 [18000 ; 34000] 56.00% [21.18%; 85.71%] Total 37000 [15000 ; 84000] 85000 [47000 ; 141000] 48000 [32000 ; 58000] 56.47% [21.28%; 121.28%] QALY lost 0–4 y 7000 [3000 ; 16000] 15000 [8000 ; 25000] 8000 [5000 ; 10000] 53.33% [20.00%; 125.00%] 5–19 y 27000 [11000 ; 54000] 65000 [40000 ; 91000] 38000 [28000 ; 40000] 58.46% [30.77%; 100.00%] 20–29 y 5000 [2000 ; 12000] 12000 [7000 ; 21000] 7000 [5000 ; 10000] 58.33% [23.81%; 142.86%] 30–39 y 6000 [2000 ; 13000] 14000 [8000 ; 22000] 8000 [5000 ; 10000] 57.14% [22.73%; 125.00%] 40–49 y 8000 [3000 ; 17000] 18000 [10000 ; 27000] 10000 [7000 ; 11000] 55.56% [25.93%; 110.00%] 50–59 y 9000 [3000 ; 20000] 21000 [12000 ; 36000] 13000 [8000 ; 16000] 61.90% [22.22%; 133.33%] 60 + y 19000 [8000 ; 44000] 43000 [24000 ; 73000] 24000 [16000 ; 29000] 55.81% [21.92%; 120.83%] Total 80000 [32000 ; 175000] 187000 [107000 ; 295000] 109000 [74000 ; 123000] 58.29% [25.08%; 114.95%] Workdays lost * 0–4 y 219000 [87000 ; 506000] 471000 [255000 ; 806000] 255000 [165000 ; 309000] 54.14% [20.47%; 121.18%] 5–19 y 660000 [273000 ; 1342000] 1614000 [987000 ; 2264000] 945000 [706000 ; 997000] 58.55% [31.18%; 101.01%] 20–29 y 186000 [73000 ; 436000] 467000 [249000 ; 802000] 283000 [173000 ; 373000] 60.60% [21.57%; 149.80%] 30–39 y 256000 [101000 ; 578000] 618000 [342000 ; 1007000] 365000 [238000 ; 439000] 59.06% [23.63%; 128.36%] 40–49 y 360000 [145000 ; 776000] 837000 [484000 ; 1279000] 482000 [334000 ; 517000] 57.59% [26.11%; 106.82%] 50–59 y 120000 [48000 ; 276000] 298000 [162000 ; 499000] 179000 [113000 ; 227000] 60.07% [22.65%; 140.12%] 60 + y 81000 [32000 ; 185000] 178000 [98000 ; 302000] 99000 [65000 ; 120000] 55.62% [21.52%; 122.45%] Total 1882000 [759000 ; 4100000] 4483000 [2577000 ; 6959000] 2626000 [1794000 ; 2922000] 58.58% [25.78%; 113.39%] *For 0 to 19 y workdays lost is associated to caregivers. Economic and Productivity Impact of Universal Influenza Vaccination UIV program was associated with substantial reductions in both healthcare-related costs and productivity losses compared to the base case scenario, as shown in Table 5 . Total costs related to general practitioner (GP) consultations decreased from 236.00 million USD (95% CI: 137.13–361.89) in the base case to 99.38 million USD (95% CI: 40.30–214.69) under the UIV strategy, reflecting an absolute reduction of 137.93 million USD (95% CI: 95.49–150.37) and a relative decrease of 58.44% (95% CI: 26.39%–109.66%). The greatest absolute savings were observed in the 5–19-year group (66.64 million USD; 95% CI: 49.80–70.26), while the highest relative reduction was seen among individuals aged 20–29 years (60.64%; 95% CI: 21.63%–149.89%). Hospitalization costs followed a similar trend, declining from 320.06 million USD (95% CI: 177.17–528.98) to 139.18 million USD (95% CI: 55.44–316.16), representing a reduction of 180.89 million USD (95% CI: 118.62–216.89) and a relative reduction of 56.52% (95% CI: 30.55%–107.63%). The highest absolute cost reductions in hospitalizations were observed among adults aged 60 years and older (45.68 million USD; 95% CI: 30.47–55.96), followed closely by those aged 50–59 years (40.35 million USD; 95% CI: 25.35–51.09) and young children under 5 years (40.10 million USD; 95% CI: 25.85–48.64). Regarding productivity loss, total costs decreased from 125.71 million USD (95% CI: 72.28–195.15) to 52.77 million USD (95% CI: 21.29–114.99), yielding savings of 73.63 million USD (95% CI: 50.33–81.94) and a relative reduction of 58.57% (95% CI: 25.79%–113.35%). The most notable absolute reduction occurred among caregivers of school-aged children (5–19 years: 26.50 million USD; 95% CI: 19.81–27.95). Table 5 Predicted costs of Universal Influenza Vaccination USD (millions) Costs Universal influenza vaccination Base case scenario Difference Relative reduction GP consultations 0–4 y 15.44 [6.17 ; 35.66] 33.19 [17.98 ; 56.85] 17.96 [11.63 ; 21.82] 54.11% [20.46% ; 121.36%] 5–19 y 46.52 [19.27 ; 94.69] 113.81 [69.65 ; 159.69] 66.64 [49.8 ; 70.26] 58.55% [31.19% ; 100.87%] 20–29 y 7.08 [2.78 ; 16.6] 17.76 [9.46 ; 30.51] 10.77 [6.6 ; 14.18] 60.64% [21.63% ; 149.89%] 30–39 y 8.34 [3.3 ; 18.81] 20.15 [11.13 ; 32.79] 11.91 [7.75 ; 14.3] 59.11% [23.64% ; 128.48%] 40–49 y 11.67 [4.7 ; 25.13] 27.1 [15.65 ; 41.4] 15.61 [10.8 ; 16.72] 57.60% [26.09% ; 106.84%] 50–59 y 4.32 [1.71 ; 9.91] 10.69 [5.81 ; 17.9] 6.43 [4.04 ; 8.15] 60.15% [22.57% ; 140.28%] 60 + y 6.04 [2.39 ; 13.84] 13.32 [7.33 ; 22.58] 7.37 [4.86 ; 8.96] 55.33% [21.52% ; 122.24%] Total 99.38 [40.3 ; 214.69] 236.00 [137.13 ; 361.89] 137.93 [95.49 ; 150.37] 58.44% [26.39% ; 109.66%] Hospitalizations 0–4 y 34.90 [13.94 ; 80.59] 75.00 [40.64 ; 128.52] 40.10 [25.85 ; 48.64] 53.47% [20.11% ; 119.68%] 5–19 y 8.94 [3.70 ; 18.21] 21.89 [13.39 ; 30.71] 12.84 [9.58 ; 13.51] 58.66% [31.19% ; 100.90%] 20–29 y 5.87 [2.31 ; 13.77] 14.73 [7.84 ; 25.30] 8.93 [5.47 ; 11.77] 60.63% [21.62% ; 150.13%] 30–39 y 9.71 [3.85 ; 21.91] 23.48 [12.96 ; 38.19] 13.88 [9.02 ; 16.65] 59.11% [23.64% ; 128.43%] 40–49 y 14.83 [5.97 ; 31.96] 34.43 [19.91 ; 52.63] 19.60 [13.74 ; 21.30] 56.93% [25.78% ; 106.98%] 50–59 y 27.04 [10.70 ; 62.11] 67.00 [36.40 ; 112.16] 40.35 [25.35 ; 51.09] 60.24% [22.60% ; 140.36%] 60 + y 37.90 [15.02 ; 86.90] 83.59 [46.04 ; 141.62] 45.68 [30.47 ; 55.96] 54.66% [21.25% ; 121.57%] Total 139.18 [55.44 ; 316.16] 320.06 [177.17 ; 528.98] 180.89 [118.62 ; 216.89] 56.52% [30.55% ; 107.63%] Productivity loss * 0–4 y 6.14 [2.45 ; 14.18] 13.20 [7.15 ; 22.61] 7.14 [4.62 ; 8.68] 54.09% [20.43% ; 121.44%] 5–19 y 18.50 [7.66 ; 37.65] 45.26 [27.69 ; 63.50] 26.50 [19.81 ; 27.95] 58.55% [31.18% ; 100.94%] 20–29 y 5.22 [2.05 ; 12.24] 13.09 [6.97 ; 22.49] 7.94 [4.86 ; 10.46] 60.66% [21.64% ; 150.07%] 30–39 y 7.18 [2.84 ; 16.20] 17.34 [9.59 ; 28.23] 10.25 [6.67 ; 12.30] 59.11% [23.64% ; 128.29%] 40–49 y 10.11 [4.07 ; 21.77] 23.47 [13.56 ; 35.86] 13.52 [9.36 ; 14.49] 57.61% [26.09% ; 106.86%] 50–59 y 3.37 [1.33 ; 7.75] 8.36 [4.54 ; 14.00] 5.03 [3.16 ; 6.37] 60.17% [22.57% ; 140.31%] 60 + y 2.26 [0.90 ; 5.19] 5.00 [2.75 ; 8.47] 2.77 [1.82 ; 3.36] 55.40% [21.49% ; 122.18%] Total 52.77 [21.29 ; 114.99] 125.71 [72.28 ; 195.15] 73.63 [50.33 ; 81.94] 58.57% [25.79% ; 113.35%] * For 0 to 19 y productivity loss is associated to caregivers Sensitivity analysis The results of the univariate sensitivity analysis for societal costs, which highlight the six parameters with the greatest influence on cost outcomes, are illustrated in Fig. 2 . Univariate sensitivity analysis of prevented societal cost.. The most influential factor was workday loss per influenza episode, followed by the cost per hospitalization and the number of GP visits per influenza case. These variables showed the largest variation in prevented costs when individually adjusted within plausible ranges. In contrast, parameters such as the cost per GP visit and average workday cost had a lower impact on the economic outcomes. The asymmetric width of the bars in the tornado diagram reflects the direction and magnitude of the influence of each parameter, providing insight into which inputs are most critical for economic model stability. Coverage level analysis The coverage level analysis demonstrated a consistent, positive association between increased vaccination coverage and reductions in both health outcomes and economic burden, as seen in Table 6 . As VCR increased from the base case of 24.13% to a universal coverage scenario of 52.09%, substantial decreases were observed across all clinical outcomes, including GP consultations, hospitalizations, deaths, and workdays lost. Under the universal scenario, the model estimated a 57.65% reduction in GP consultations, 56.23% in hospitalizations, and 55.53% in influenza-related deaths, relative to the base case. Productivity loss also declined by 57.79%, equivalent to approximately 2.6 million fewer workdays lost. These improvements translated into significant cost savings. From the third-party payer perspective, the reduction in costs ranged from USD 75.7 million in Incremental Scenario 1 to USD 321.58 million in Universal Scenario. From the societal perspective, the universal coverage scenario (52.09% VCR) achieved the highest impact, with a 57.04% reduction in societal costs, translating into total savings of USD 389.22 million. Table 6 Health and economic impact of increased influenza vaccination coverage in Mexico Outcomes Costs (USD millions ) Average VCR GP consultations Hospitalizations Deaths LYs QALYs Workdays lost Third party Societal Base Case 24.13% 3166000 [1839000 ; 4852000] 72000 [40000 ; 118000] 5400 [2980 ; 9060] 85000 [47000 ; 141000] 187000 [107000 ; 295000] 4483000 [2577000 ; 6959000] 555.86 [314.58 ; 890.80] 681.90 [386.82 ; 1,086.32] Scenarios Relative Reduction vs Base Case Incremental 1 31.12% 13.48% [8% ; 22.49%] 13.27% [7.93% ; 21.83%] 12.94% [7.84% ; 21.48%] 13.28% [8.07% ; 21.86%] 13.42% [8.07% ; 22.27%] 13.61% [8.18% ; 22.57%] 13.61% [8.18% ; 22.57%] 13.42% [8.03% ; 22.19%] Incremental 2 38.11% 28.06% [17.68% ; 40.91%] 27.32% [17.64% ; 39.77%] 26.82% [17.39% ; 39.35%] 27.42% [17.85% ; 39.93%] 27.9% [17.86% ; 40.64%] 28.25% [17.99% ; 40.94%] 28.25% [17.99% ; 40.94%] 27.76% [17.76% ; 40.41%] Incremental 3 45.10% 42.92% [28.5% ; 57.9%] 41.82% [28.29% ; 56.28%] 41.14% [27.98% ; 55.76%] 41.94% [28.61% ; 56.4%] 42.67% [28.69% ; 57.44%] 43.12% [28.91% ; 57.89%] 43.12% [28.91% ; 57.89%] 42.46% [28.53% ; 57.17%] Universal 52.09% 57.65% [40.32% ; 70.93%] 56.23% [39.86% ; 69.05%] 55.53% [39.42% ; 68.56%] 56.36% [40.21% ; 69.2%] 57.3% [40.45% ; 70.37%] 57.79% [40.74% ; 70.88%] 57.79% [40.74% ; 70.88%] 57.04% [40.23% ; 70.05%] Discussion In alignment with global efforts to reduce the burden of influenza, the implementation of a UIV strategy in Mexico could offer substantial public health and economic benefits. Drawing from the experience of the United States, where the Advisory Committee on Immunization Practices (ACIP) recommended vaccination for all individuals aged 6 months and older [16]. Similar arguments in favor of UIV [48] could be aligned with the World Health Organization’s 2019–2030 Global Influenza Strategy, which emphasizes simplified recommendations and equitable access as core objectives [1] and may be applicable to the current Mexican context to promote health equity. First, the shift to universal vaccination could markedly reduce influenza-related morbidity and mortality in Mexico. Modeled reductions across clinical outcomes reflect both direct protection among vaccinated individuals and indirect protection at the population level (herd effect), amplifying the overall public health impact. These findings are consistent with evidence from other countries reporting significant declines in hospitalizations and deaths following broader vaccination policies[49–52]. Second, simplifying recommendations to “vaccinate all persons aged ≥ 6 months” can enhance coverage among currently prioritized groups (e.g., pregnant women, older adults), as universal messaging streamlines communication and reduces confusion [1,53]. Third, expanding seasonal influenza vaccine use may strengthen overall vaccine manufacturing capacity, which is essential for pandemic preparedness by ensuring rapid scalability during emergencies [36]; This point has been emphasized by WHO and CIDRAP in support of pandemic resilience [1,54]. Fourth, Mexico’s domestic vaccine production capabilities present a unique opportunity: increased local manufacturing for seasonal vaccination could stimulate the national economy, maintain supply chain autonomy, and potentially reduce costs [42,53]. Our findings demonstrate that a UIV strategy has the potential to reduce influenza-related cases, hospitalizations, and deaths, as well as productivity losses during a typical influenza season. The estimated decrease in healthcare utilization implies a meaningful relief for an often-overburdened health system, particularly during seasonal peaks when service demand intensifies. From a societal perspective, the observed reduction in workdays lost reveals the far-reaching economic implications of the intervention. This reduction reflects a substantial mitigation of indirect costs associated with influenza, particularly those stemming from absenteeism in the workforce. These results are particularly relevant from a third-party payer and societal perspective, highlighting not only improved health outcomes but also more efficient use of healthcare resources. The observed reductions across all age groups reinforce the added value of indirect protection, especially for currently recommended target populations. For example, our results suggest reductions in cases from 54.11% to 55.44% and hospitalizations from 52.63% to 52.94% among children under 4 years of age and older adults. Given potential uncertainties in vaccine uptake under a UIV strategy, we conducted sensitivity analyses across a range of vaccination coverage scenarios. These analyses reaffirmed the strong relationship between coverage levels and health impact. Achieving high coverage will require addressing key determinants of vaccine uptake, including access, affordability, awareness, acceptance, and activation [55]. Integrating influenza vaccination with other existing public health campaigns may enhance acceptance and opportunistic value, particularly in a stepwise approach targeting specific age groups. Examples of such stratified strategies are explored in the Supplemental Materials. One limitation of our costing analysis is the exclusion of vaccination program costs (e.g., vaccine procurement, administration, campaign logistics). Future evaluations should incorporate these factors, tailored to the unique structure of Mexico’s fragmented healthcare system and the characteristics of national public–private manufacturing agreements that enable preferential pricing. This would allow for a more comprehensive cost-effectiveness assessment under real-world conditions. Notably, previous research has found UIV strategies to be cost-effective [18] or even cost-saving in various countries [36]. As with any modeling study, our analysis has several limitations. Model outputs depend on the quality of the underlying assumptions and input data. Where Mexican-specific data were unavailable, we relied on adjusted estimates from other countries for parameters such as healthcare utilization, mortality, productivity loss, and influenza-related QALY lost. The latter were derived from a Spanish longitudinal study that estimated disutility using EQ-5D scores in both hospitalized and ambulatory patients and converted these estimates into QALY by incorporating episode duration (LY factor) for non-fatal cases and life expectancy for fatal cases. This approach, while necessary, introduces uncertainty. Additionally, influenza incidence incidence of influenza was derived from placebo arms of clinical trials, as in a previous publication [20], which may yield conservative results compared to studies using U.S.-based incidence estimates with generally higher values [21]. Vaccine efficacy inputs were based on clinical data, which may differ from real-world effectiveness. In addition, vaccine effectiveness was not stratified by age group or vaccine platform, although it is well recognized that effectiveness may vary between children and adults and across adult age strata (e.g., 18–65 years vs ≥ 65 years), as well as between inactivated and live-attenuated formulations. This simplification may therefore obscure age-specific differences in protection. Furthermore, assuming identical clinical progression among vaccinated and unvaccinated individuals who develop influenza may underestimate the benefits of vaccination. We also did not stratify the 5–59-year age group by high-risk subpopulations, potentially undervaluing health benefits and the additional protective effects vaccination could offer beyond influenza infection [56]. Lastly, while our analysis considered a quadrivalent influenza vaccine, our results may remain relevant in scenarios where a trivalent vaccine is used, such as in the context of the B/Yamagata lineage disappearance [57]. Despite these limitations, our findings suggest that universal vaccination represents a strategy that can reduce both healthcare and societal costs while enhancing health equity. Leveraging Mexico’s manufacturing capacity and evolving vaccination infrastructure, the adoption of a universal influenza vaccine policy could support disease control, strengthen economic resilience, and improve preparedness for future pandemic threats objectives that are consistent with both global health frameworks and national priorities. Conclusions This study demonstrates that adopting a Universal Influenza Vaccination strategy in Mexico could markedly reduce the seasonal influenza burden by providing both direct protection and indirect community benefits. The consistent reductions in infections, hospitalizations, productivity losses, and healthcare costs across all age groups highlight the public health and economic value of expanding routine influenza vaccination. Abbreviations CI Confidence interval CONAPO National Population Council GP General practitioner HRQL Health-related quality of life ILI Influenza-like illness LYs Life-years MAE Mean absolute error QALYs Quality-adjusted life years USD United States dollar UIV Universal influenza vaccination VCRs Vaccine coverage rates VE Vaccine effectiveness yo Year old. Declarations Ethics approval and consent to participate This study was based exclusively on secondary data obtained from published literature and publicly available sources. No individual-level identifiable data were used. Therefore, ethics approval and informed consent were not required in accordance with applicable regulations and institutional policies. Consent for publication Not applicable. Competing Interest Pascal Crépey received consulting fees from Sanofi Pasteur. Patricia Cervantes, José Bartelt-Hofer, Carlos Noda and Alexis Pozzo di Borgo are Sanofi Pasteur employees and may hold stock. Funding Competing Interests Pascal Crépey received consulting fees from Sanofi Pasteur. Patricia Cervantes, José Bartelt-Hofer, Carlos Noda and Alexis Pozzo di Borgo are Sanofi Pasteur employees and may hold stock. Author Contribution AP and JB contributed to the conception and design of the study. PCP and CN were responsible for data collection. PC performed and led the statistical analyses. AP, JB contributed to the interpretation of the results. AP, PCP y CN drafted the manuscript. All authors critically revised the manuscript for important intellectual content and approved the final version. Acknowledgement The authors would like to acknowledge Dr. Diana Vilar, from the National Cancer Institute of Mexico, for her valuable contribution as an expert advisor to this investigation. Data Availability All data used in this study were derived from previously published studies and publicly available sources cited in the reference list. 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Vaccine. 7 de enero de 2019;37(2):226 − 34. Li R, Li Q, Liu Y, Shen M, Zhang L, Zhuang G. Modelling the impact of universal influenza vaccines on seasonal influenza with different subtypes. Epidemiol Infect. 2 de noviembre de 2021;149:e253. Hill EM, Petrou S, de Lusignan S, Yonova I, Keeling MJ. Seasonal influenza: Modelling approaches to capture immunity propagation. PLoS Comput Biol. 28 de octubre de 2019;15(10):e1007096. Romero-Feregrino R, Romero-Cabello R, Rodríguez-León MA, Rocha-Rocha VM, Romero-Feregrino R, Muñoz-Cordero B. Report of the Influenza Vaccination Program in Mexico (2006–2022) and Proposals for Its Improvement. Vaccines (Basel). 3 de noviembre de 2023;11(11):1686. Roadmap | CIDRAP [Internet]. [citado 3 de julio de 2025]. Disponible en: https://ivr.cidrap.umn.edu/roadmap Thomson A, Robinson K, Vallée-Tourangeau G. The 5As: A practical taxonomy for the determinants of vaccine uptake. Vaccine. 2016;34(8):1018-24. Fröbert O, Götberg M, Erlinge D, Akhtar Z, Christiansen EH, MacIntyre CR. Influenza Vaccination After Myocardial Infarction. Circulation. 2021;144(18):1476-84. Paget J, Caini S, Del Riccio M, van Waarden W, Meijer A. Has influenza B/Yamagata become extinct and what implications might this have for quadrivalent influenza vaccines? Euro Surveill. 2022;27(39). Additional Declarations Competing interest reported. Pascal Crépey received consulting fees from Sanofi Pasteur. Patricia Cervantes, José Bartelt-Hofer, Carlos Noda and Alexis Pozzo di Borgo are Sanofi Pasteur employees and may hold stock. Supplementary Files SupplementaryUIVMexicoMWAuthorsVF.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 09 Apr, 2026 Reviewers invited by journal 02 Apr, 2026 Editor invited by journal 05 Mar, 2026 Editor assigned by journal 05 Mar, 2026 Submission checks completed at journal 05 Mar, 2026 First submitted to journal 02 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9013333","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619099824,"identity":"42c69b2a-a29b-49b9-b8d6-051865277ed4","order_by":0,"name":"Pascal Crépey","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuklEQVRIiWNgGAWjYPACGyBmbDxAipY0kJYGkrQcBpPEaeGfffjYg49t5+3Wth8G2lJjE01Qi8S5tHTDmW23k7edSQRqOZaW20BIiwEPj5k0L1CL2QGgFsaGw8Ro4f8m/bftXLLZ+YdEa+Fhk2ZsO2BndoNYWyTOsJkb9pxLTjC7AbQlgRi/8PcwP3vwo8zO3ux8+sMHH2psCGsBAjYGRjaGRLDKBCKUQ7Qw/GGwJ1LxKBgFo2AUjEQAAHOhRSUM+yAAAAAAAElFTkSuQmCC","orcid":"","institution":"University of Rennes","correspondingAuthor":true,"prefix":"","firstName":"Pascal","middleName":"","lastName":"Crépey","suffix":""},{"id":619099825,"identity":"6f25a1c6-9ff0-43bc-b8bf-a64f050e7617","order_by":1,"name":"Patricia Cervantes","email":"","orcid":"","institution":"Sanofi","correspondingAuthor":false,"prefix":"","firstName":"Patricia","middleName":"","lastName":"Cervantes","suffix":""},{"id":619099826,"identity":"13d03f76-aaf7-43a5-88db-95ff482738f7","order_by":2,"name":"José Bartelt-Hofer","email":"","orcid":"","institution":"Sanofi Vaccines","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"","lastName":"Bartelt-Hofer","suffix":""},{"id":619099828,"identity":"4e6ee5ac-ca4e-4874-a665-4c88b1a7c2c8","order_by":3,"name":"Carlos Noda","email":"","orcid":"","institution":"Sanofi","correspondingAuthor":false,"prefix":"","firstName":"Carlos","middleName":"","lastName":"Noda","suffix":""},{"id":619099829,"identity":"f03f95e3-9a1d-414d-9115-0a3bcdbf0f59","order_by":4,"name":"Alexis Pozzo Borgo","email":"","orcid":"","institution":"Sanofi","correspondingAuthor":false,"prefix":"","firstName":"Alexis","middleName":"Pozzo","lastName":"Borgo","suffix":""}],"badges":[],"createdAt":"2026-03-02 19:38:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9013333/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9013333/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106468997,"identity":"89f04011-57c9-4588-8912-981c3fb0f15f","added_by":"auto","created_at":"2026-04-09 00:45:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":229836,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative incidence of symptomatic Influenza cases by season per age-group and for all age groups.\u003c/p\u003e\n\u003cp\u003e*The black dots correspond to observed symptomatic influenza incidence, while the bars stand for the incidence estimated by the model.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9013333/v1/ef89b22a0f3518e57fc011de.jpg"},{"id":106725281,"identity":"bc27c67b-baa6-4caa-9e25-d5e366ad5265","added_by":"auto","created_at":"2026-04-12 18:32:14","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27610,"visible":true,"origin":"","legend":"\u003cp\u003eUnivariate sensitivity analysis of prevented societal cost.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9013333/v1/333940bdf35277fbe34cc97f.jpg"},{"id":106726975,"identity":"8d9e6c15-6b59-483c-9401-dd7d07970d93","added_by":"auto","created_at":"2026-04-12 18:37:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1798933,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9013333/v1/7491e32a-1313-41b3-97e3-2712a8050166.pdf"},{"id":106468996,"identity":"3ba3a6cd-149a-48a7-bb64-cde2b5c1166c","added_by":"auto","created_at":"2026-04-09 00:45:06","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":325270,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryUIVMexicoMWAuthorsVF.docx","url":"https://assets-eu.researchsquare.com/files/rs-9013333/v1/d32c4f59000ea4e126c66bb2.docx"}],"financialInterests":"Competing interest reported. Pascal Crépey received consulting fees from Sanofi Pasteur. Patricia Cervantes, José Bartelt-Hofer, Carlos Noda and Alexis Pozzo di Borgo are Sanofi Pasteur employees and may hold stock.","formattedTitle":"Evaluation of the public health and economic impact of universal influenza vaccination in Mexico","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSeasonal influenza causes 1\u0026nbsp;billion cases annually worldwide, of which up to 5\u0026nbsp;million are severe, and between 291,000 and 645,000 influenza-related deaths [1,2]. Although all individuals are at risk, vaccination recommendations primarily focus on groups with a higher risk of complications [3]. However, many cases occur in healthy, economically active adults, resulting in an average of 175,000 deaths annually from 1999 to 2015[2,4] and causing a significant impact on quality of life and the economy [5].\u003c/p\u003e \u003cp\u003eIn Mexico, influenza and pneumonia remain among the ten leading causes of death. Between 2010 and 2019, an estimated 73,459 to 101,114 hospitalizations and 15,620 to 31,081 deaths were reported annually [6,7]. Although influenza circulation decreased during the SARS-CoV-2 pandemic [8], the 2022\u0026ndash;2023 season had the highest number of cases since the 2009 pandemic [9]. In Mexico, influenza vaccination is primarily targeted at children aged 6 to 59 months, adults aged 60 years and older, and individuals aged 5 to 59 years who are at high risk for influenza-related complications (approximately 7% of this age group) [10], resulting in an overall vaccine coverage of approximately 25% of the general population, with an estimated 33 to 35\u0026nbsp;million doses administered each influenza season [11]. however, most hospitalizations and deaths occur in unvaccinated individuals [12,13].\u003c/p\u003e \u003cp\u003eThe \"Global Influenza Strategy 2019\u0026ndash;2030\" and its perspective for Latin America emphasize the importance of enhancing influenza prevention, detection, control, and treatment, reinforcing the need to strengthen the epidemiological surveillance and to assess the burden of disease and its economic impact [1,14]. To augment the prevention of influenza, Mexican experts have proposed universal influenza vaccination from 6 months of age [15]. The United States experience and other international studies demonstrate the potential benefits of such an approach [16\u0026ndash;19]. Some Mexican studies have identified opportunities to improve protection [20\u0026ndash;22], however, these analyses are limited to specific strategies and rely on static models, which do not capture the indirect benefits of vaccination, such as the protection conferred to unvaccinated individuals through reduced transmission [23,24]. From a societal perspective, and considering US vaccination coverage rates as a possible target for universal influenza vaccination in Mexico, this study aims to estimate, for a typical influenza season, the potential health and economic benefits of transitioning to a universal influenza vaccination strategy, irrespective of vaccine formulation, as the modeling focuses on the overall impact of increased coverage\u003c/p\u003e"},{"header":"Methods and material","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEpidemiological Model\u003c/h2\u003e \u003cp\u003eA dynamic epidemiological, influenza transmission model has been developed to accurately assess the impact of influenza vaccination. It is composed of two sub-models; both split the population into compartments based on their status regarding the disease. Individuals may be either susceptible to infection (S), exposed but not infectious (E), infected and infectious (I) or immune to infection (recovered; R). One sub-model considers the non-vaccinated population, the other the vaccinated one (Supplemental Fig.\u0026nbsp;1). In addition, the population is stratified into 7 age-groups (0-4yo, 5-19yo, 20-29yo, 30-39yo, 40-49yo, 50\u0026ndash;59, 60 and older) derived from the national population database (\u003cem\u003eConsejo Nacional de Poblaci\u0026oacute;n\u003c/em\u003e \u0026ndash; \u003cem\u003eCONAPO\u003c/em\u003e) [25]. As the model is age-structured, it uses an age-dependent contact matrix adapted to the given age-groups from the contact matrix for Mexico estimated by Prem et al. [26]. The dynamic transmission model was calibrated to reproduce the yearly influenza incidence under current vaccination coverage levels. To reflect real-world epidemiological variability, we defined three incidence scenarios: a typical season, based on the average annual incidence from 2015 to 2020; a high-incidence season, based on data from 2015\u0026ndash;2016; and a low-incidence season, based on 2017\u0026ndash;2018. Full details and results for the high- and low-incidence scenarios are provided in Additional file 1. The probability of transmission per contact was adjusted accordingly in each scenario to reflect the observed burden of disease. Probabilities of influenza transmission upon contact are inferred using a Bayesian inference framework (dust, mcstate).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHealth-Economic model\u003c/h3\u003e\n\u003cp\u003eA health economic model was developed to estimate the health and economic outcomes associated with each vaccination strategy, based on the outputs of the epidemiological model. The model is a decision tree structured by age groups, aligned with those described previously. Age-specific influenza cases estimated by the epidemiological model were translated into transition probabilities of general practitioner (GP) consultations, hospitalizations and deaths, and outcomes expressed in terms of life-years lost, and quality-adjusted life-years (QALYs) lost. The model also calculated the direct medical costs related to these outcomes, as well as indirect costs associated with productivity losses due to illness and death. See Supplemental Fig.\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eAs this analysis is retrospective in nature, future costs and health outcomes were not projected and therefore were not subjected to discounting. However, consistent with national guidelines, life-years (LYs) and QALYs lost due to influenza-related mortality were discounted at an annual rate of 5% [27].\u003c/p\u003e\n\u003ch3\u003eInfluenza incidence\u003c/h3\u003e\n\u003cp\u003eEstimating the real burden of influenza is a necessary step before trying to evaluate the performance of strategies aiming at reducing it. In Mexico, influenza epidemiological surveillance mainly relies on the reporting of outpatient cases (10% are sampled for laboratory tests), as well as hospitalizations and deaths who meet the case definition for influenza like illness (ILI) or severe acute respiratory infections (SARI) [28]. But limitations due to the heterogeneity of the healthcare systems (public/private, primary to third care clinics overlapping different pools of potential patients) make estimates of influenza incidence based on this system unreliable.\u003c/p\u003e \u003cp\u003eIn our analysis, the incidence estimation was based on a previously used methodology [20,29]. that derives average incidence or attack rates based from report of placebo arms of previous clinical trials [30\u0026ndash;32]. These estimates can be considered representative of a typical-influenza season. These rates were distributed across the 2015\u0026ndash;2020 seasons using a locally derived coefficient, calculated by dividing the number of cases reported in a given season [9] by the average number of cases per season during the modeled period. This method allows the estimation of influenza incidence per season and age-group as given in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eWe then used the weekly proportion of influenza positive tests reported to the national surveillance system of respiratory diseases (SISVEFLU and SISVER by their Spanish acronyms) [12] and combined it with the yearly incidence estimated previously to compute the weekly incidence over the period.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimations of symptomatic influenza incidence by age-groups and influenza season in Mexico.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e 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align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3.86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.85%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016\u0026ndash;2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.77%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5.19%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.46%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.81%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.01%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2018\u0026ndash;2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.81%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6.08%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2019\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5.05%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2021\u0026ndash;2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.83%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e* 2020 to 2022 seasons were excluded from the analysis to avoid biasing the results due to the uncommon nature of influenza circulation during COVID-19 pandemic\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eVaccination efficacy and coverage rates scenarios\u003c/h3\u003e\n\u003cp\u003eHistorical vaccine coverage rates (VCRs) were estimated using official records of influenza vaccine doses administered, as reported by national health authorities [11], in combination with demographic data from the National Population Council (CONAPO) database [25]. To estimate age-specific coverage among high-risk populations, administered doses were proportionally distributed by age group based on population size and the estimated prevalence of high-risk conditions, following the methodology outlined by Tapia-Conyer et al., [33]. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the average VCRs across the seasons analyzed for both the base case (reflecting historical vaccination practices) and the proposed universal vaccination strategy. The universal vaccination scenario assumes current VCRs for the youngest (6 months to 4 years) and oldest (\u0026ge;\u0026thinsp;60 years) age groups and extrapolates coverage for other age cohorts using data from the U.S. CDC\u0026rsquo;s National Immunization Survey-Flu for the 2022\u0026ndash;2023 season. Specifically, data included individuals from birth up to 17 years of age, with coverage rates for those aged 6 months to 17 years derived from pediatric estimates [34], while adult coverage was based on reported uptake among those aged 18\u0026ndash;49 and 50\u0026ndash;64 years [35].\u003c/p\u003e \u003cp\u003eCoverage rates are reported as the percentage of the target population who completed the full vaccination schedule.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVCRs average across influenza seasons by age group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 months \u0026ndash; 4 y\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u0026ndash;19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u0026ndash;29\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e60 +\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eGeneral population\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBase case scenario\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80.23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.68%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.52%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26.16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e90.93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e24.13%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversal Vaccination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e80.23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e36.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e51.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e90.93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e52.09%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn our analysis we assume that vaccination campaigns start every year on week 40 and that 80% of the targeted population is vaccinated at the end of December (week 52), then the rest (20%) vaccinated from January to March.\u003c/p\u003e \u003cp\u003eAge-specific influenza vaccine efficacy estimates were obtained from Clements et al. assuming overall efficacy in the absence of B-lineage mismatch. Reported efficacy values were 60% for children under 5 years, 64% for individuals aged 5\u0026ndash;49 years, 63% for those aged 50\u0026ndash;64 years, and 60% for adults aged 65 years and older [36].\u003c/p\u003e\n\u003ch3\u003eHealth-economic model inputs\u003c/h3\u003e\n\u003cp\u003eProbabilities of General Practitioner (GP) visits, hospitalizations, and deaths related to influenza were estimated using data from the US population [37], due to the lack of publicly available data for Mexico. GP visit probabilities were adjusted to reflect Mexico\u0026rsquo;s lower doctor visit rate per capita compared to the U.S., based on 2021 national statistics [38]. Hospitalization and mortality rates were not adjusted, under the assumption that these outcomes are comparable between countries. In the absence of disaggregated data, these estimates were also applied to high-risk populations as a conservative approach (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e for details).\u003c/p\u003e \u003cp\u003eThese epidemiological probabilities constitute key drivers of the economic model, as they determine the expected number of healthcare events attributable to influenza in each age group. When combined with unit costs (GP visits, hospitalizations, productivity losses) and health utility parameters (baseline QALYs and QALY losses per episode), they allow estimation of total direct medical costs, indirect costs, and quality-adjusted life years (QALYs) lost.\u003c/p\u003e \u003cp\u003eAll cost estimates are expressed in 2023 U.S. dollars (USD), reflecting a typical influenza season from a retrospective perspective. Unit costs for GP consultations and hospitalizations were sourced from public social security institutions in Mexico [39]. Hospitalization costs were calculated based on unitary costs and the average length of stay for influenza cases by age group, using discharge data from 2008 to 2021 [7]. The cost of workdays lost was valued using the average daily wage in Mexico between January and August 2023, as reported by the Ministry of Labor and Social Welfare, and was applied only to individuals of working age [40]. An average exchange rate for the second quarter of 2023 (1 USD\u0026thinsp;=\u0026thinsp;17.07 MXN) was applied to convert all costs from Mexican pesos to U.S. dollars [41].\u003c/p\u003e \u003cp\u003eModel estimates that include vaccine acquisition and administration costs are reported separately in Supplemental Table\u0026nbsp;2. These figures are based on assumptions due to confidential pricing agreements established through a public-private partnership in Mexico and therefore may not reflect actual market conditions [42].\u003c/p\u003e \u003cp\u003eWorkdays lost consider the absenteeism and presenteeism reported by Zumofen et al., including the missed days of caregivers for caring sick children [4], these days were adjusted by work effectiveness during presenteeism [43] and age-specific economic activity rates from the 2022 National Survey of Occupation and Employment [44]. Finally utility measures for the general population specific to Mexico are taken from GBD database [45] and Influenza-related QALY lost estimates in our model are derived from a Spanish longitudinal study by Hollmann et al., which used EQ-5D scores to measure health-related quality of life (HRQL) in hospitalized and ambulatory patients with influenza (H1N1) 2009. The study calculated \u0026ldquo;disutility\u0026rdquo; as the difference between pre-episode and during-episode EQ-5D utility indices and converted these into QALYs lost by incorporating the LYs factor in this context, the duration of the episode in days, using the formula DQ\u0026thinsp;=\u0026thinsp;Du \u0026times; d / 365. Mean disutility was 0.58 for hospitalized and 0.43 for ambulatory patients, corresponding to QALYs lost of 0.031 and 0.009, respectively [46].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHealth Economic Model Input Values\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDistribution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eProbability of a GP visit per flu case\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0-4y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.32632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"20\" rowspan=\"21\"\u003e \u003cp\u003e-20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"20\" rowspan=\"21\"\u003e \u003cp\u003e+\u0026thinsp;20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"20\" rowspan=\"21\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e[43], [44]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5-19y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22758\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20-29y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30-39y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40-49y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50-59y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.22448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60p\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.37433\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eProbability of hospitalization per flu infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0-4y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"13\" rowspan=\"14\"\u003e \u003cp\u003e[43]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5-19y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20-29y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30-39y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40-49y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50-59y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01930\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60p\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03482\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eProbability of death per flu infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0-4y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5-19y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20-29y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30-39y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40-49y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50-59y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60p\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00839\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCost (USD) per GP visits*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll age-groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e74.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u0026thinsp;20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLognormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[45], [53]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eCost (USD) per Hosp visits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0-4y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e3,899.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e-30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e+\u0026thinsp;30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eLognormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e[45], [7]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5-19y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e3,015.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20-29y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e3,304.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30-39y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e4,637.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40-49y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e5,068.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50-59y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e5,435.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60p\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e5,030.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWork day cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll age-groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e28.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+\u0026thinsp;20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLognormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[46]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eWorkday loss per symptomatic influenza episode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0-4y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eLognormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e[4], [49], [50].\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5-19y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20-29y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30-39y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40-49y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50-59y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60p\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eBaseline utility (QALYs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0-4y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e-20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e+\u0026thinsp;20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eLognormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e[51], [54]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5-19y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20-29y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30-39y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40-49y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50-59y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60p\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQALY lost per medically-attended influenza episode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInpatients. All age-groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLognormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e[52]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutpatients. All age-groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLognormal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e* The GP costs also consider a treatment with oseltamivir according to National Guidelines of flu treatment [47]. An average cost of \u003cspan\u003e$\u003c/span\u003e10.81 USD in line with prices of national consolidated purchases [53] was added on top of GP visit cost.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analysis\u003c/h2\u003e \u003cp\u003eWe conducted univariate sensitivity analyses on key clinical and economic parameters detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, with results presented as Tornado diagrams. Variables with no impact on the economic outcomes, such as mortality-related parameters and quality of life losses, were excluded from this analysis. In addition, alternative vaccine coverage levels were explored to assess their impact on model results.\u003c/p\u003e \u003cp\u003eVaccine effectiveness (VE) was not varied independently in the univariate sensitivity analysis because it was embedded within the transmission dynamics and model calibration process to reproduce observed epidemiological patterns. Varying VE in isolation would disrupt the internally calibrated relationship between transmission parameters and observed incidence. Therefore, uncertainty related to VE is reflected indirectly through the model\u0026rsquo;s probabilistic structure and calibration framework.\u003c/p\u003e \u003cp\u003eFinally, Additional file 1 provides:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eResults from two targeted vaccination strategies focused on specific age groups, as a potential stepwise approach toward universal vaccination.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eScenario analyses for influenza seasons with lower and higher incidence, corresponding respectively to the 2017\u0026ndash;2018 and 2015\u0026ndash;2016 seasons.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eModel calibration for the study period.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Cumulative incidence of symptomatic Influenza cases by season per age-group and for all age groups., the influenza transmission model accurately reproduced age-specific influenza incidence across multiple seasons included in the analysis. However, the complex and variable epidemiological patterns observed in tropical settings, particularly the occurrence of multiple peaks within a single year, led to some degree of under or overestimation in certain age groups and seasons. The overall mean absolute error (MAE), which quantifies the average discrepancy between model predictions and observed data, was highest among children aged 0\u0026ndash;4 years and adults aged 40\u0026ndash;49 years (MAE: 8%), and lowest in the \u0026ge;\u0026thinsp;60-year age group (MAE: 1.13%). When averaged across all age groups and seasons, the MAE was 2.75%, indicating good model fit.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e*The black dots correspond to observed symptomatic influenza incidence, while the bars stand for the incidence estimated by the model.\u003c/p\u003e\n\u003ch3\u003eImpact of Universal Vaccination on Health Outcomes\u003c/h3\u003e\n\u003cp\u003eThe implementation of a UIV program led to substantial and consistent reductions in the overall burden of disease, highlighting its potential as a transformative public health intervention as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe model estimated a reduction of 7.68\u0026nbsp;million symptomatic cases (95% CI: 5.33\u0026ndash;8.32\u0026nbsp;million), corresponding to a 58.72% decrease (95% CI: 26.88%\u0026ndash;109.22%) compared to current coverage levels. This reduction was observed across all age groups and was particularly pronounced among individuals aged 5\u0026ndash;19 and 40\u0026ndash;49 years, two demographic groups characterized by high social mobility and contact rates that may contribute substantially to viral transmission. Although the upper bound of the 95% confidence interval for the relative reduction exceeded 100%, this reflects the probabilistic structure of the model and variability in simulated incidence scenarios rather than a literal reduction beyond the total number of cases. Across all simulations, the effect consistently favored universal vaccination. These findings indicate both direct protection among vaccinated individuals and indirect (herd) effects that enhance population-level impact.\u003c/p\u003e \u003cp\u003eThe model estimated a reduction of 7.68\u0026nbsp;million symptomatic cases (95% CI: 5.33\u0026ndash;8.32\u0026nbsp;million), which translates into a 58.72% (95% CI: 26.88%-109.22%) decrease compared to current coverage levels. This significant drop in incidence was observed across all age groups, suggesting a strong population-wide effect. This effect was particularly notable among individuals aged 5\u0026ndash;19 and 40\u0026ndash;49 years; two demographic groups with high social mobility and contact rates, which may act as key transmitters of the virus.\u003c/p\u003e \u003cp\u003eThe reductions in healthcare utilization further underscore the potential system-level benefits. A decrease of 1.85\u0026nbsp;million general practitioner (GP) consultations (95% CI: 1.28\u0026ndash;2.02\u0026nbsp;million) and 41,000 hospitalizations (95% CI: 27,000\u0026ndash;49,000).\u003c/p\u003e \u003cp\u003eIn terms of severe outcomes, the prevention of approximately 3,050 deaths (95% CI: 2,000\u0026ndash;3,700) is a critical finding. While influenza-related mortality disproportionately affects older adults and individuals with comorbidities, the overall decline suggests that broader coverage could significantly mitigate the risk of fatal outcomes across the population. Reductions in years of LY lost (48,000; CI: 32,000\u0026ndash;58,000) and QALY lost (109,000; 95% CI: 74,000\u0026ndash;123,000) further illustrate the health gains from a universal approach.\u003c/p\u003e \u003cp\u003eFrom a societal perspective, the avoidance of 2.63\u0026nbsp;million workdays lost (95% CI: 1.79\u0026ndash;2.92\u0026nbsp;million) reveals the far-reaching economic implications of the intervention.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredicted outcomes of Universal Influenza Vaccination\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUniversal influenza vaccination\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBase case scenario\u003c/p\u003e \u003cp\u003e(current coverage)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDifference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRelative reduction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eSymptomatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e635000 [254000 ; 1466000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1364000 [739000 ; 2337000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e738000 [478000 ; 897000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e54.11% [20.49%; 121.39%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2742000 [1136000 ; 5581000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6708000 [4104000 ; 9413000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3928000 [2936000 ; 4143000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.56% [31.20%; 71.46%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e423000 [166000 ; 992000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1061000 [565000 ; 1823000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e644000 [394000 ; 848000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.70% [22.03%; 150.09%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e498000 [197000 ; 1124000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1204000 [665000 ; 1960000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e712000 [463000 ; 854000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.14% [23.60%; 91.73%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e697000 [281000 ; 1502000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1619000 [935000 ; 2474000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e933000 [645000 ; 1e\u0026thinsp;+\u0026thinsp;06]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.63% [26.09% ; 42.78%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258000 [102000 ; 592000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e639000 [347000 ; 1070000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e385000 [242000 ; 487000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.25% [22.60%; 140.35%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e217000 [86000 ; 497000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e478000 [263000 ; 810000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e265000 [174000 ; 322000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.44% [21.48% ; 122.02%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5469000 [2220000 ; 11755000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13074000 [7623000 ; 19886000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7677000 [5334000 ; 8320000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.72% [26.88%; 109.22%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eGP consultations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e207000 [83000 ; 478000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e445000 [241000 ; 763000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e241000 [156000 ; 293000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e54.16% [20.47%; 121.18%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e624000 [258000 ; 1270000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1527000 [934000 ; 2142000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e894000 [668000 ; 943000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.55% [31.18%; 101.01%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95000 [37000 ; 223000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e238000 [127000 ; 409000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144000 [88000 ; 190000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.50% [21.52%; 149.80%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112000 [44000 ; 252000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e270000 [149000 ; 440000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e160000 [104000 ; 192000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.26% [23.64%; 128.36%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e157000 [63000 ; 337000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e364000 [210000 ; 555000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e209000 [145000 ; 224000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.42% [26.11%; 106.82%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58000 [23000 ; 133000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e143000 [78000 ; 240000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86000 [54000 ; 109000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.14% [22.65%; 140.12%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81000 [32000 ; 186000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e179000 [98000 ; 303000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99000 [65000 ; 120000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.31% [21.92%; 120.83%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1333000 [541000 ; 2880000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3166000 [1839000 ; 4852000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1850000 [1281000 ; 2017000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.48% [25.08%; 114.95%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eHospitalizations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9000 [4000 ; 21000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19000 [10000 ; 33000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10000 [7000 ; 13000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52.63% [21.21%; 130.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3000 [1000 ; 6000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7000 [4000 ; 10000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4000 [3000 ; 4000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.14% [30.00%; 100.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2000 [1000 ; 4000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4000 [2000 ; 8000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3000 [2000 ; 4000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e75.00% [25.00%; 200.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2000 [1000 ; 5000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5000 [3000 ; 8000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3000 [2000 ; 4000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.00% [25.00%; 133.33%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3000 [1000 ; 6000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7000 [4000 ; 10000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4000 [3000 ; 4000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.14% [30.00%; 100.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5000 [2000 ; 11000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12000 [7000 ; 21000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7000 [5000 ; 9000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.33% [23.81%; 142.86%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8000 [3000 ; 17000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17000 [9000 ; 28000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9000 [6000 ; 11000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52.94% [21.43%; 122.22%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31000 [12000 ; 71000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72000 [40000 ; 118000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41000 [27000 ; 49000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.94% [22.97%; 122.50%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eDeaths\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 [10 ; 60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 [30 ; 90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 [20 ; 40]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.00% [22.22%; 133.33%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 [20 ; 120]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e140 [90 ; 190]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80 [60 ; 90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.14% [33.33%; 88.89%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 [10 ; 90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 [50 ; 160]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60 [40 ; 80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.00 [25.00%; 160.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 [20 ; 100]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110 [60 ; 180]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60 [40 ; 80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e54.55% [22.22%; 133.33%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 [30 ; 140]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150 [80 ; 220]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80 [60 ; 90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e53.33% [27.27%; 112.50%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e350 [140 ; 790]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e860 [460 ; 1430]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e520 [320 ; 650]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.47% [22.54%; 141.30%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1810 [720 ; 4150]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4000 [2200 ; 6780]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2210 [1460 ; 2690]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.25% [21.55%; 122.27%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2390 [950 ; 5450]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5400 [2980 ; 9060]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3050 [2000 ; 3700]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.48% [20.10%; 185.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eLYs lost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1000 [0 ; 2000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2000 [1000 ; 3000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1000 [1000 ; 1000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.00% [33.33%; 33.33%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2000 [1000 ; 4000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5000 [3000 ; 6000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3000 [2000 ; 3000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.00% [50.00%; 60.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1000 [0 ; 3000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3000 [2000 ; 5000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2000 [1000 ; 2000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e66.67% [40.00%; 66.67%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1000 [1000 ; 3000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3000 [2000 ; 5000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2000 [1000 ; 2000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e66.67% [40.00%; 66.67%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2000 [1000 ; 3000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4000 [2000 ; 6000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2000 [1000 ; 2000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e50.00% [16.67%; 100.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7000 [3000 ; 17000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18000 [10000 ; 31000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11000 [7000 ; 14000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e61.11% [22.58%; 140.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23000 [9000 ; 52000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50000 [28000 ; 85000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28000 [18000 ; 34000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.00% [21.18%; 85.71%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37000 [15000 ; 84000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85000 [47000 ; 141000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48000 [32000 ; 58000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.47% [21.28%; 121.28%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eQALY lost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7000 [3000 ; 16000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15000 [8000 ; 25000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8000 [5000 ; 10000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e53.33% [20.00%; 125.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27000 [11000 ; 54000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65000 [40000 ; 91000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38000 [28000 ; 40000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.46% [30.77%; 100.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5000 [2000 ; 12000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12000 [7000 ; 21000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7000 [5000 ; 10000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.33% [23.81%; 142.86%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6000 [2000 ; 13000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14000 [8000 ; 22000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8000 [5000 ; 10000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.14% [22.73%; 125.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8000 [3000 ; 17000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18000 [10000 ; 27000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10000 [7000 ; 11000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.56% [25.93%; 110.00%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9000 [3000 ; 20000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21000 [12000 ; 36000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13000 [8000 ; 16000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e61.90% [22.22%; 133.33%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19000 [8000 ; 44000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43000 [24000 ; 73000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24000 [16000 ; 29000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.81% [21.92%; 120.83%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80000 [32000 ; 175000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e187000 [107000 ; 295000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e109000 [74000 ; 123000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.29% [25.08%; 114.95%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eWorkdays lost *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e219000 [87000 ; 506000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e471000 [255000 ; 806000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e255000 [165000 ; 309000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e54.14% [20.47%; 121.18%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e660000 [273000 ; 1342000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1614000 [987000 ; 2264000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e945000 [706000 ; 997000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.55% [31.18%; 101.01%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e186000 [73000 ; 436000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e467000 [249000 ; 802000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e283000 [173000 ; 373000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.60% [21.57%; 149.80%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e256000 [101000 ; 578000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e618000 [342000 ; 1007000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e365000 [238000 ; 439000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.06% [23.63%; 128.36%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e360000 [145000 ; 776000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e837000 [484000 ; 1279000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e482000 [334000 ; 517000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.59% [26.11%; 106.82%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120000 [48000 ; 276000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e298000 [162000 ; 499000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e179000 [113000 ; 227000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e60.07% [22.65%; 140.12%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81000 [32000 ; 185000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e178000 [98000 ; 302000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99000 [65000 ; 120000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.62% [21.52%; 122.45%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1882000 [759000 ; 4100000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4483000 [2577000 ; 6959000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2626000 [1794000 ; 2922000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.58% [25.78%; 113.39%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e*For 0 to 19 y workdays lost is associated to caregivers.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEconomic and Productivity Impact of Universal Influenza Vaccination\u003c/h2\u003e \u003cp\u003eUIV program was associated with substantial reductions in both healthcare-related costs and productivity losses compared to the base case scenario, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Total costs related to general practitioner (GP) consultations decreased from 236.00\u0026nbsp;million USD (95% CI: 137.13\u0026ndash;361.89) in the base case to 99.38\u0026nbsp;million USD (95% CI: 40.30\u0026ndash;214.69) under the UIV strategy, reflecting an absolute reduction of 137.93\u0026nbsp;million USD (95% CI: 95.49\u0026ndash;150.37) and a relative decrease of 58.44% (95% CI: 26.39%\u0026ndash;109.66%). The greatest absolute savings were observed in the 5\u0026ndash;19-year group (66.64\u0026nbsp;million USD; 95% CI: 49.80\u0026ndash;70.26), while the highest relative reduction was seen among individuals aged 20\u0026ndash;29 years (60.64%; 95% CI: 21.63%\u0026ndash;149.89%).\u003c/p\u003e \u003cp\u003eHospitalization costs followed a similar trend, declining from 320.06\u0026nbsp;million USD (95% CI: 177.17\u0026ndash;528.98) to 139.18\u0026nbsp;million USD (95% CI: 55.44\u0026ndash;316.16), representing a reduction of 180.89\u0026nbsp;million USD (95% CI: 118.62\u0026ndash;216.89) and a relative reduction of 56.52% (95% CI: 30.55%\u0026ndash;107.63%). The highest absolute cost reductions in hospitalizations were observed among adults aged 60 years and older (45.68\u0026nbsp;million USD; 95% CI: 30.47\u0026ndash;55.96), followed closely by those aged 50\u0026ndash;59 years (40.35\u0026nbsp;million USD; 95% CI: 25.35\u0026ndash;51.09) and young children under 5 years (40.10\u0026nbsp;million USD; 95% CI: 25.85\u0026ndash;48.64).\u003c/p\u003e \u003cp\u003eRegarding productivity loss, total costs decreased from 125.71\u0026nbsp;million USD (95% CI: 72.28\u0026ndash;195.15) to 52.77\u0026nbsp;million USD (95% CI: 21.29\u0026ndash;114.99), yielding savings of 73.63\u0026nbsp;million USD (95% CI: 50.33\u0026ndash;81.94) and a relative reduction of 58.57% (95% CI: 25.79%\u0026ndash;113.35%). The most notable absolute reduction occurred among caregivers of school-aged children (5\u0026ndash;19 years: 26.50\u0026nbsp;million USD; 95% CI: 19.81\u0026ndash;27.95).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredicted costs of Universal Influenza Vaccination USD (millions)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCosts\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUniversal influenza vaccination\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBase case scenario\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDifference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRelative reduction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eGP consultations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.44 [6.17 ; 35.66]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.19 [17.98 ; 56.85]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.96 [11.63 ; 21.82]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.11%\u003c/p\u003e \u003cp\u003e[20.46% ; 121.36%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.52 [19.27 ; 94.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e113.81 [69.65 ; 159.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.64 [49.8 ; 70.26]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.55%\u003c/p\u003e \u003cp\u003e[31.19% ; 100.87%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.08 [2.78 ; 16.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.76 [9.46 ; 30.51]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.77 [6.6 ; 14.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.64%\u003c/p\u003e \u003cp\u003e[21.63% ; 149.89%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.34 [3.3 ; 18.81]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.15 [11.13 ; 32.79]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.91 [7.75 ; 14.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.11%\u003c/p\u003e \u003cp\u003e[23.64% ; 128.48%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.67 [4.7 ; 25.13]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.1 [15.65 ; 41.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.61 [10.8 ; 16.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.60%\u003c/p\u003e \u003cp\u003e[26.09% ; 106.84%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.32 [1.71 ; 9.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.69 [5.81 ; 17.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.43 [4.04 ; 8.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.15%\u003c/p\u003e \u003cp\u003e[22.57% ; 140.28%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.04 [2.39 ; 13.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.32 [7.33 ; 22.58]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.37 [4.86 ; 8.96]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.33%\u003c/p\u003e \u003cp\u003e[21.52% ; 122.24%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.38 [40.3 ; 214.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e236.00 [137.13 ; 361.89]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e137.93 [95.49 ; 150.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.44%\u003c/p\u003e \u003cp\u003e[26.39% ; 109.66%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eHospitalizations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.90 [13.94 ; 80.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.00 [40.64 ; 128.52]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.10 [25.85 ; 48.64]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.47%\u003c/p\u003e \u003cp\u003e[20.11% ; 119.68%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.94 [3.70 ; 18.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.89 [13.39 ; 30.71]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.84 [9.58 ; 13.51]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.66%\u003c/p\u003e \u003cp\u003e[31.19% ; 100.90%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.87 [2.31 ; 13.77]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.73 [7.84 ; 25.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.93 [5.47 ; 11.77]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.63%\u003c/p\u003e \u003cp\u003e[21.62% ; 150.13%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.71 [3.85 ; 21.91]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.48 [12.96 ; 38.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.88 [9.02 ; 16.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.11%\u003c/p\u003e \u003cp\u003e[23.64% ; 128.43%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.83 [5.97 ; 31.96]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.43 [19.91 ; 52.63]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.60 [13.74 ; 21.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.93%\u003c/p\u003e \u003cp\u003e[25.78% ; 106.98%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.04 [10.70 ; 62.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.00 [36.40 ; 112.16]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.35 [25.35 ; 51.09]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.24%\u003c/p\u003e \u003cp\u003e[22.60% ; 140.36%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"1\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37.90 [15.02 ; 86.90]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.59 [46.04 ; 141.62]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.68 [30.47 ; 55.96]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.66%\u003c/p\u003e \u003cp\u003e[21.25% ; 121.57%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139.18\u003c/p\u003e \u003cp\u003e[55.44 ; 316.16]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e320.06\u003c/p\u003e \u003cp\u003e[177.17 ; 528.98]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e180.89\u003c/p\u003e \u003cp\u003e[118.62 ; 216.89]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.52%\u003c/p\u003e \u003cp\u003e[30.55% ; 107.63%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eProductivity loss *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;4 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.14 [2.45 ; 14.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.20 [7.15 ; 22.61]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.14 [4.62 ; 8.68]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.09% [20.43% ; 121.44%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026ndash;19 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.50 [7.66 ; 37.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.26 [27.69 ; 63.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.50 [19.81 ; 27.95]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.55% [31.18% ; 100.94%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;29 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.22 [2.05 ; 12.24]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.09 [6.97 ; 22.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.94 [4.86 ; 10.46]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.66% [21.64% ; 150.07%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.18 [2.84 ; 16.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.34 [9.59 ; 28.23]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.25 [6.67 ; 12.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e59.11% [23.64% ; 128.29%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.11 [4.07 ; 21.77]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.47 [13.56 ; 35.86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.52 [9.36 ; 14.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.61% [26.09% ; 106.86%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;59 y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.37 [1.33 ; 7.75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.36 [4.54 ; 14.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.03 [3.16 ; 6.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.17% [22.57% ; 140.31%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026thinsp;+\u0026thinsp;y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.26 [0.90 ; 5.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.00 [2.75 ; 8.47]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.77 [1.82 ; 3.36]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.40% [21.49% ; 122.18%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.77 [21.29 ; 114.99]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125.71 [72.28 ; 195.15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.63 [50.33 ; 81.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.57% [25.79% ; 113.35%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e* For 0 to 19 y productivity loss is associated to caregivers\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analysis\u003c/h2\u003e \u003cp\u003eThe results of the univariate sensitivity analysis for societal costs, which highlight the six parameters with the greatest influence on cost outcomes, are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Univariate sensitivity analysis of prevented societal cost..\u003c/p\u003e \u003cp\u003eThe most influential factor was workday loss per influenza episode, followed by the cost per hospitalization and the number of GP visits per influenza case. These variables showed the largest variation in prevented costs when individually adjusted within plausible ranges. In contrast, parameters such as the cost per GP visit and average workday cost had a lower impact on the economic outcomes.\u003c/p\u003e \u003cp\u003eThe asymmetric width of the bars in the tornado diagram reflects the direction and magnitude of the influence of each parameter, providing insight into which inputs are most critical for economic model stability.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCoverage level analysis\u003c/h2\u003e \u003cp\u003eThe coverage level analysis demonstrated a consistent, positive association between increased vaccination coverage and reductions in both health outcomes and economic burden, as seen in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. As VCR increased from the base case of 24.13% to a universal coverage scenario of 52.09%, substantial decreases were observed across all clinical outcomes, including GP consultations, hospitalizations, deaths, and workdays lost.\u003c/p\u003e \u003cp\u003eUnder the universal scenario, the model estimated a 57.65% reduction in GP consultations, 56.23% in hospitalizations, and 55.53% in influenza-related deaths, relative to the base case. Productivity loss also declined by 57.79%, equivalent to approximately 2.6\u0026nbsp;million fewer workdays lost.\u003c/p\u003e \u003cp\u003eThese improvements translated into significant cost savings. From the third-party payer perspective, the reduction in costs ranged from USD 75.7\u0026nbsp;million in Incremental Scenario 1 to USD 321.58\u0026nbsp;million in Universal Scenario. From the societal perspective, the universal coverage scenario (52.09% VCR) achieved the highest impact, with a 57.04% reduction in societal costs, translating into total savings of USD 389.22\u0026nbsp;million.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHealth and economic impact of increased influenza vaccination coverage in Mexico\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c9\" namest=\"c3\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eCosts (USD millions )\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAverage VCR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eGP consultations\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eHospitalizations\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e\u003cb\u003eDeaths\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eLYs\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eQALYs\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eWorkdays lost\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eThird party\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003eSocietal\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBase Case\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3166000 [1839000 ; 4852000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e72000\u003c/p\u003e \u003cp\u003e[40000 ; 118000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5400 [2980 ; 9060]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85000 [47000 ; 141000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e187000 [107000 ; 295000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4483000 [2577000 ; 6959000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e555.86 [314.58 ; 890.80]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e681.90\u003c/p\u003e \u003cp\u003e[386.82 ; 1,086.32]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eScenarios\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c11\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRelative Reduction vs Base Case\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncremental 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.48%\u003c/p\u003e \u003cp\u003e[8% ; 22.49%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e13.27% [7.93% ; 21.83%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.94% [7.84% ; 21.48%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.28% [8.07% ; 21.86%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.42% [8.07% ; 22.27%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.61% [8.18% ; 22.57%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e13.61% [8.18% ; 22.57%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13.42%\u003c/p\u003e \u003cp\u003e[8.03% ; 22.19%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncremental 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.06% [17.68% ; 40.91%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e27.32% [17.64% ; 39.77%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.82% [17.39% ; 39.35%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.42% [17.85% ; 39.93%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.9% [17.86% ; 40.64%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.25% [17.99% ; 40.94%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.25% [17.99% ; 40.94%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e27.76% [17.76% ; 40.41%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncremental 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.92% [28.5% ; 57.9%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e41.82% [28.29% ; 56.28%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.14% [27.98% ; 55.76%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e41.94% [28.61% ; 56.4%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e42.67% [28.69% ; 57.44%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e43.12% [28.91% ; 57.89%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e43.12% [28.91% ; 57.89%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e42.46% [28.53% ; 57.17%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.09%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.65% [40.32% ; 70.93%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e56.23% [39.86% ; 69.05%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.53% [39.42% ; 68.56%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.36% [40.21% ; 69.2%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e57.3% [40.45% ; 70.37%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e57.79% [40.74% ; 70.88%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e57.79% [40.74% ; 70.88%]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e57.04% [40.23% ; 70.05%]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn alignment with global efforts to reduce the burden of influenza, the implementation of a UIV strategy in Mexico could offer substantial public health and economic benefits. Drawing from the experience of the United States, where the Advisory Committee on Immunization Practices (ACIP) recommended vaccination for all individuals aged 6 months and older [16].\u003c/p\u003e \u003cp\u003eSimilar arguments in favor of UIV [48] could be aligned with the World Health Organization\u0026rsquo;s 2019\u0026ndash;2030 Global Influenza Strategy, which emphasizes simplified recommendations and equitable access as core objectives [1] and may be applicable to the current Mexican context to promote health equity.\u003c/p\u003e \u003cp\u003eFirst, the shift to universal vaccination could markedly reduce influenza-related morbidity and mortality in Mexico. Modeled reductions across clinical outcomes reflect both direct protection among vaccinated individuals and indirect protection at the population level (herd effect), amplifying the overall public health impact. These findings are consistent with evidence from other countries reporting significant declines in hospitalizations and deaths following broader vaccination policies[49\u0026ndash;52].\u003c/p\u003e \u003cp\u003eSecond, simplifying recommendations to \u0026ldquo;vaccinate all persons aged\u0026thinsp;\u0026ge;\u0026thinsp;6 months\u0026rdquo; can enhance coverage among currently prioritized groups (e.g., pregnant women, older adults), as universal messaging streamlines communication and reduces confusion [1,53].\u003c/p\u003e \u003cp\u003eThird, expanding seasonal influenza vaccine use may strengthen overall vaccine manufacturing capacity, which is essential for pandemic preparedness by ensuring rapid scalability during emergencies [36]; This point has been emphasized by WHO and CIDRAP in support of pandemic resilience [1,54].\u003c/p\u003e \u003cp\u003eFourth, Mexico\u0026rsquo;s domestic vaccine production capabilities present a unique opportunity: increased local manufacturing for seasonal vaccination could stimulate the national economy, maintain supply chain autonomy, and potentially reduce costs [42,53].\u003c/p\u003e \u003cp\u003eOur findings demonstrate that a UIV strategy has the potential to reduce influenza-related cases, hospitalizations, and deaths, as well as productivity losses during a typical influenza season. The estimated decrease in healthcare utilization implies a meaningful relief for an often-overburdened health system, particularly during seasonal peaks when service demand intensifies. From a societal perspective, the observed reduction in workdays lost reveals the far-reaching economic implications of the intervention. This reduction reflects a substantial mitigation of indirect costs associated with influenza, particularly those stemming from absenteeism in the workforce.\u003c/p\u003e \u003cp\u003eThese results are particularly relevant from a third-party payer and societal perspective, highlighting not only improved health outcomes but also more efficient use of healthcare resources. The observed reductions across all age groups reinforce the added value of indirect protection, especially for currently recommended target populations. For example, our results suggest reductions in cases from 54.11% to 55.44% and hospitalizations from 52.63% to 52.94% among children under 4 years of age and older adults.\u003c/p\u003e \u003cp\u003eGiven potential uncertainties in vaccine uptake under a UIV strategy, we conducted sensitivity analyses across a range of vaccination coverage scenarios. These analyses reaffirmed the strong relationship between coverage levels and health impact. Achieving high coverage will require addressing key determinants of vaccine uptake, including access, affordability, awareness, acceptance, and activation [55]. Integrating influenza vaccination with other existing public health campaigns may enhance acceptance and opportunistic value, particularly in a stepwise approach targeting specific age groups. Examples of such stratified strategies are explored in the Supplemental Materials.\u003c/p\u003e \u003cp\u003eOne limitation of our costing analysis is the exclusion of vaccination program costs (e.g., vaccine procurement, administration, campaign logistics). Future evaluations should incorporate these factors, tailored to the unique structure of Mexico\u0026rsquo;s fragmented healthcare system and the characteristics of national public\u0026ndash;private manufacturing agreements that enable preferential pricing. This would allow for a more comprehensive cost-effectiveness assessment under real-world conditions. Notably, previous research has found UIV strategies to be cost-effective [18] or even cost-saving in various countries [36].\u003c/p\u003e \u003cp\u003eAs with any modeling study, our analysis has several limitations. Model outputs depend on the quality of the underlying assumptions and input data. Where Mexican-specific data were unavailable, we relied on adjusted estimates from other countries for parameters such as healthcare utilization, mortality, productivity loss, and influenza-related QALY lost. The latter were derived from a Spanish longitudinal study that estimated disutility using EQ-5D scores in both hospitalized and ambulatory patients and converted these estimates into QALY by incorporating episode duration (LY factor) for non-fatal cases and life expectancy for fatal cases. This approach, while necessary, introduces uncertainty. Additionally, influenza incidence incidence of influenza was derived from placebo arms of clinical trials, as in a previous publication [20], which may yield conservative results compared to studies using U.S.-based incidence estimates with generally higher values [21]. Vaccine efficacy inputs were based on clinical data, which may differ from real-world effectiveness. In addition, vaccine effectiveness was not stratified by age group or vaccine platform, although it is well recognized that effectiveness may vary between children and adults and across adult age strata (e.g., 18\u0026ndash;65 years vs\u0026thinsp;\u0026ge;\u0026thinsp;65 years), as well as between inactivated and live-attenuated formulations. This simplification may therefore obscure age-specific differences in protection. Furthermore, assuming identical clinical progression among vaccinated and unvaccinated individuals who develop influenza may underestimate the benefits of vaccination. We also did not stratify the 5\u0026ndash;59-year age group by high-risk subpopulations, potentially undervaluing health benefits and the additional protective effects vaccination could offer beyond influenza infection [56]. Lastly, while our analysis considered a quadrivalent influenza vaccine, our results may remain relevant in scenarios where a trivalent vaccine is used, such as in the context of the B/Yamagata lineage disappearance [57].\u003c/p\u003e \u003cp\u003eDespite these limitations, our findings suggest that universal vaccination represents a strategy that can reduce both healthcare and societal costs while enhancing health equity. Leveraging Mexico\u0026rsquo;s manufacturing capacity and evolving vaccination infrastructure, the adoption of a universal influenza vaccine policy could support disease control, strengthen economic resilience, and improve preparedness for future pandemic threats objectives that are consistent with both global health frameworks and national priorities.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrates that adopting a Universal Influenza Vaccination strategy in Mexico could markedly reduce the seasonal influenza burden by providing both direct protection and indirect community benefits. The consistent reductions in infections, hospitalizations, productivity losses, and healthcare costs across all age groups highlight the public health and economic value of expanding routine influenza vaccination.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCONAPO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Population Council\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGeneral practitioner\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHRQL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth-related quality of life\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eILI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInfluenza-like illness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLYs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLife-years\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMAE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMean absolute error\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eQALYs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eQuality-adjusted life years\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUnited States dollar\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUIV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUniversal influenza vaccination\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVCRs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVaccine coverage rates\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVaccine effectiveness\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eyo\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eYear old.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was based exclusively on secondary data obtained from published literature and publicly available sources. No individual-level identifiable data were used. Therefore, ethics approval and informed consent were not required in accordance with applicable regulations and institutional policies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eCompeting Interest\u003c/p\u003e\n\u003cp\u003ePascal Cr\u0026eacute;pey received consulting fees from Sanofi Pasteur. Patricia Cervantes, Jos\u0026eacute; Bartelt-Hofer, Carlos Noda and Alexis Pozzo di Borgo are Sanofi Pasteur employees and may hold stock. \u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePascal Cr\u0026eacute;pey received consulting fees from Sanofi Pasteur. Patricia Cervantes, Jos\u0026eacute; Bartelt-Hofer, Carlos Noda and Alexis Pozzo di Borgo are Sanofi Pasteur employees and may hold stock.\u003c/p\u003e\n\u003cp\u003eAuthor Contribution\u003c/p\u003e\n\u003cp\u003eAP and JB contributed to the conception and design of the study. PCP and CN were responsible for data collection. PC performed and led the statistical analyses. AP, JB contributed to the interpretation of the results. AP, PCP y CN drafted the manuscript. All authors critically revised the manuscript for important intellectual content and approved the final version.\u003c/p\u003e\n\u003cp\u003eAcknowledgement\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge Dr. Diana Vilar, from the National Cancer Institute of Mexico, for her valuable contribution as an expert advisor to this investigation.\u003c/p\u003e\n\u003cp\u003eData Availability\u003c/p\u003e\n\u003cp\u003eAll data used in this study were derived from previously published studies and publicly available sources cited in the reference list. The model inputs and analytic code supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. Global Influenza Strategy 2019–2030. 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Lineamiento Estandarizado para la vigilancia epidemiológica y por laboratorio de la enfermedad respiratoria viral. 2022.\u003c/li\u003e\n\u003cli\u003eBianculli P, Bellier L, Mangado I, Pérez C, Mieres G, Lazarov L, et al. Switching from trivalent to quadrivalent inactivated influenza vaccines in Uruguay: a cost-effectiveness analysis. Hum Vaccin Immunother. 2022;18(5).\u003c/li\u003e\n\u003cli\u003eJefferson T, Rivetti A, Di Pietrantonj C, Demicheli V. Vaccines for preventing influenza in healthy children. Cochrane Database Syst Rev. 1 de febrero de 2018;2(2):CD004879.\u003c/li\u003e\n\u003cli\u003eDemicheli V, Jefferson T, Ferroni E, Rivetti A, Di Pietrantonj C. Vaccines for preventing influenza in healthy adults. Cochrane Database Syst Rev. 1 de febrero de 2018;2(2):CD001269.\u003c/li\u003e\n\u003cli\u003eDemicheli V, Jefferson T, Di Pietrantonj C, Ferroni E, Thorning S, Thomas RE, et al. Vaccines for preventing influenza in the elderly. 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CLIN INFECT DIS. febrero de 2009;48(3):292-8.\u003c/li\u003e\n\u003cli\u003eNational Institute of Statistics and Geography (INEGI). National Survey of Occupation and Employment [Internet]. 2023. Disponible en: https://www.inegi.org.mx/programas/enoe/15ymas/#Tabulados\u003c/li\u003e\n\u003cli\u003eGlobal Health Data Exchange, Institute for Health Metrics and Evaluation. GBD Results Tools [Internet]. 2021. Disponible en: http://ghdx.healthdata.org/gbd-results-tool?params=gbd-api-2019-permalink/c5e7049114e612cf14cd886aa0d9905d\u003c/li\u003e\n\u003cli\u003eHollmann M, Garin O, Galante M, Ferrer M, Dominguez A, Alonso J. Impact of influenza on health-related quality of life among confirmed (H1N1)2009 patients. PLoS One. 2013;8(3).\u003c/li\u003e\n\u003cli\u003ePrevención, diagnóstico y tratamiento de la influenza estacional. Ciudad de México: Secretaría de Salud. 2015;1–22.\u003c/li\u003e\n\u003cli\u003eBerman P, Orenstein W, Hinman A, Gazmararian J. Stakeholder attitudes toward influenza vaccination policy in the United States. Health Promot Pract. 2010;11(6):807 − 16.\u003c/li\u003e\n\u003cli\u003eYang KC, Hung HF, Chen MK, Chen SLS, Fann JCY, Chiu SYH, et al. Cost-effectiveness analysis of universal influenza vaccination: Application of the susceptible–infectious–complication–recovery model. International Journal of Infectious Diseases. agosto de 2018;73:102-8.\u003c/li\u003e\n\u003cli\u003eLeidner AJ, Murthy N, Chesson HW, Biggerstaff M, Stoecker C, Harris AM, et al. Cost-effectiveness of adult vaccinations: A systematic review. Vaccine. 7 de enero de 2019;37(2):226 − 34.\u003c/li\u003e\n\u003cli\u003eLi R, Li Q, Liu Y, Shen M, Zhang L, Zhuang G. Modelling the impact of universal influenza vaccines on seasonal influenza with different subtypes. Epidemiol Infect. 2 de noviembre de 2021;149:e253.\u003c/li\u003e\n\u003cli\u003eHill EM, Petrou S, de Lusignan S, Yonova I, Keeling MJ. Seasonal influenza: Modelling approaches to capture immunity propagation. PLoS Comput Biol. 28 de octubre de 2019;15(10):e1007096.\u003c/li\u003e\n\u003cli\u003eRomero-Feregrino R, Romero-Cabello R, Rodríguez-León MA, Rocha-Rocha VM, Romero-Feregrino R, Muñoz-Cordero B. Report of the Influenza Vaccination Program in Mexico (2006–2022) and Proposals for Its Improvement. Vaccines (Basel). 3 de noviembre de 2023;11(11):1686.\u003c/li\u003e\n\u003cli\u003eRoadmap | CIDRAP [Internet]. [citado 3 de julio de 2025]. Disponible en: https://ivr.cidrap.umn.edu/roadmap\u003c/li\u003e\n\u003cli\u003eThomson A, Robinson K, Vallée-Tourangeau G. The 5As: A practical taxonomy for the determinants of vaccine uptake. Vaccine. 2016;34(8):1018-24.\u003c/li\u003e\n\u003cli\u003eFröbert O, Götberg M, Erlinge D, Akhtar Z, Christiansen EH, MacIntyre CR. Influenza Vaccination After Myocardial Infarction. Circulation. 2021;144(18):1476-84.\u003c/li\u003e\n\u003cli\u003ePaget J, Caini S, Del Riccio M, van Waarden W, Meijer A. Has influenza B/Yamagata become extinct and what implications might this have for quadrivalent influenza vaccines? Euro Surveill. 2022;27(39).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Influenza, Vaccination, Mexico, Epidemiological modeling, Health economic analysis, Public health","lastPublishedDoi":"10.21203/rs.3.rs-9013333/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9013333/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eInfluenza continues to represent a substantial global public health challenge. Although vaccination is the most effective intervention to mitigate its impact, current strategies offer room for enhancement. This study evaluates the potential health and economic benefits of adopting a Universal Influenza Vaccination (UIV) strategy in Mexico.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eTo evaluate the potential impact of a UIV program during a typical influenza season, we conducted a retrospective analysis applying United States vaccination coverage rates to age groups not currently targeted by Mexico\u0026rsquo;s national immunization strategy. An epidemiological model was developed to simulate influenza transmission and vaccination effects. Outputs from this model were subsequently integrated into a health economic framework populated with local data. Both deterministic and probabilistic sensitivity analyses were conducted to explore parameter uncertainty and assess the robustness of the results.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDuring a typical influenza season, implementation of the UIV strategy was projected to reduce disease burden, with an estimated 57.94% decrease in influenza cases (95% CI: 40.56%\u0026ndash;71.21%). This translated into reductions of 57.65% (40.32%\u0026ndash;70.93%) fewer medical consultations, 56.23% (39.86%\u0026ndash;69.05%) in hospital admissions and 55.53% (39.42%\u0026ndash;68.56%) in influenza-attributable mortality. The intervention also yielded notable health benefits, including a 56.36% (40.21%\u0026ndash;69.2%) decrease in life-years lost and a 57.3% (40.45%\u0026ndash;70.37%) reduction in QALYs lost. These outcomes were observed across both vaccinated and unvaccinated populations, suggesting significant indirect (herd) protection. From an economic standpoint, the strategy was associated with cost savings of USD 321.22\u0026nbsp;million from the third-party payer perspective and USD 388.96\u0026nbsp;million from the broader societal perspective.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eExpanding influenza immunization through a UIV program in Mexico may significantly reduce the disease burden and associated healthcare costs. The findings suggest that broader vaccine coverage could be a cost-effective and impactful strategy to improve population health outcomes.\u003c/p\u003e","manuscriptTitle":"Evaluation of the public health and economic impact of universal influenza vaccination in Mexico","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 00:45:02","doi":"10.21203/rs.3.rs-9013333/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"19582256556205890416704511585686325602","date":"2026-04-09T08:45:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T08:32:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-05T16:20:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-05T13:29:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-05T13:26:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-03-02T19:31:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d726590b-4a26-47df-a2ce-b03e3d880a37","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T00:45:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 00:45:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9013333","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9013333","identity":"rs-9013333","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}