Influenza Vaccine Effectiveness among Children with and without Underlying Conditions

Haya Hayek; Emma K Noble; Laura S Stewart; Leila C Sahni; Julie A Boom; Marian G Michaels; John V Williams; Janet A Englund; Eileen J Klein; Mary A Staat; Elizabeth P Schlaudecker; Rangaraj Selvarangan; Jennifer E Schuster; Geoffrey A Weinberg; Peter G Szilagyi; Benjamin R Clopper; Heidi L Moline; Kelsey M Sumner; Natasha B Halasa; Samantha M Olson

doi:10.1542/peds.2025-072184

. Author manuscript; available in PMC: 2026 Mar 28.

Published in final edited form as: Pediatrics. 2026 Feb 1;157(2):e2025072184. doi: 10.1542/peds.2025-072184

Influenza Vaccine Effectiveness among Children with and without Underlying Conditions

Haya Hayek ^1,^a, Emma K Noble ^2,^3,^a, Laura S Stewart ¹, Leila C Sahni ⁴, Julie A Boom ⁴, Marian G Michaels ⁵, John V Williams ^5,⁶, Janet A Englund ⁷, Eileen J Klein ⁷, Mary A Staat ⁸, Elizabeth P Schlaudecker ⁸, Rangaraj Selvarangan ⁹, Jennifer E Schuster ⁹, Geoffrey A Weinberg ¹⁰, Peter G Szilagyi ^10,¹¹, Benjamin R Clopper ¹², Heidi L Moline ¹², Kelsey M Sumner ², Natasha B Halasa ^1,^b, Samantha M Olson ^2,^b

¹Vanderbilt University Medical Center, Nashville, TN

²Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA

³Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA

⁴Texas Children’s Hospital, Department of Pediatrics, Baylor College of Medicine, Houston, TX

⁵UPMC Children’s Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA

⁶Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI

⁷Seattle Children’s Research Institute, Seattle, Washington, WA

⁸Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH

⁹University of Missouri—Kansas City School of Medicine, Children’s Mercy Kansas City, Kansas City, MO

¹⁰University of Rochester School of Medicine and Dentistry, Rochester, NY

¹¹Department of Pediatrics, UCLA Mattel Children’s Hospital, University of California at Los Angeles, Los Angeles, California

¹²Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA

Contributed equally as co-first authors

Contributed equally as co-senior authors

Contributors Statement Page

Haya Hayek conceptualized the research question, contributed to the investigation and data interpretation, participated in writing the original draft, and critically reviewed and edited the manuscript.

Emma K. Noble conceptualized the research question, curated the data, conducted formal analysis, developed the methodology, performed visualization, and participated in writing the original draft, and critically reviewed and edited the manuscript.

Laura S. Stewart, Leila C. Sahni, Julie A. Boom, Marian G. Michaels, John V. Williams, Janet A. Englund, Eileen J. Klein, Mary A. Staat, Elizabeth P. Schlaudecker, Rangaraj Selvarangan, Jennifer E. Schuster, Geoffrey A. Weinberg, Peter G. Szilagyi, Monica N. Singer, Benjamin R. Clopper, and Heidi L. Moline designed data collection instruments, coordinated and supervised project administration, data collection and testing, funding acquisition, and reviewed and edited the manuscript for important intellectual content.

Kelsey M. Sumner developed the methodology and reviewed and edited the manuscript.

Natasha B. Halasa and Samantha M. Olson conceptualized and designed the study and research question, conducted investigation, designed data collection instruments, coordinated, and supervised project administration, data collection and testing, contributed to data interpretation and funding acquisition, provided supervision, and critically reviewed and edited the manuscript.

^✉

Address correspondence to: Samantha M. Olson, MPH, Influenza Division, National Center for Immunization and Respiratory Diseases, US Centers for Disease Control and Prevention, 1600 Clifton Rd, NE, H24-7, Atlanta, GA 30329-4027 (ylz8@cdc.gov).

PMCID: PMC13027338 NIHMSID: NIHMS2150159 PMID: 41506521

Abstract

Objective

Children with certain underlying conditions are at higher risk for severe influenza-related complications. In the U.S. annual influenza vaccination is recommended for all children aged ≥6 months, yet vaccine effectiveness (VE) in children with underlying conditions remains less understood. We assessed VE against laboratory-confirmed influenza in children with and without underlying conditions presenting to emergency departments or admitted to hospitals.

Methods

We enrolled U.S. children 6 months to 17 years old at 7 pediatric medical centers within the New Vaccine Surveillance Network during five influenza seasons (2015–2020). Influenza status was confirmed by molecular testing and vaccination status was verified using state immunization registries or from healthcare clinicians. Underlying conditions were abstracted from medical records or self-reported by parents/guardians.VE was estimated by comparing the odds of vaccination among influenza-positive cases versus controls, adjusting for age, site, and calendar time.

Results

Of the 15,875 children included, 2,821 (18%) tested positive for influenza. Overall, VE against influenza-associated ED visits or hospitalizations was 43% (95% confidence interval [CI]: 35–50%) for children with underlying conditions and 53% (95% CI: 47–59%) for those without, and there was significant effect measure modification by the presence of underlying conditions (p=0.04). VE was lowest among children with respiratory conditions (31%, 95% CI: 19–42%).

Conclusion

Influenza vaccination provided protection in both children with and without underlying conditions. Efforts to improve influenza vaccination coverage and to initiate early treatment for influenza, particularly in populations at increased risk for severe influenza, are essential to reducing influenza-associated complications.

Article Summary

This study assesses influenza vaccine effectiveness (VE) in children with and without underlying conditions, providing detailed insights into how VE varies by specific conditions.

Introduction

Seasonal influenza is a major cause of outpatient visits and hospitalizations among children, resulting in increased healthcare costs and missed school days^1–3. In the 2023–2024 influenza season in the United States, there were an estimated 6.8 million influenza-associated visits to health care clinicians, 46,000 influenza-associated hospital admissions, and over 500 influenza-associated deaths among children⁴. Young children and those with certain underlying conditions are at higher risk of severe illness and complications from influenza⁵. However, children with and without underlying conditions are susceptible to complications, including pneumonia, respiratory failure, and even death⁶.

Seasonal influenza vaccination remains the most effective preventive measure against influenza, and has been associated with a reduction of influenza-associated complications and a reduction in the global burden of influenza disease⁷. In the US, the Advisory Committee on Immunization Practices recommends seasonal influenza vaccination for all persons 6 months and older⁸. US pediatric vaccine effectiveness (VE) estimates against influenza illness (including inpatient and outpatient) from the 2023–2024 season ranged from 44% to 71%^9,10, similar to a systematic review that reported effectiveness between 54% and 83% for reducing hospitalizations¹¹. Another study reported a pooled influenza VE of 46% among children aged 6 months to 17 years over nine seasons, with variations by virus type and age group¹². Previous studies on influenza VE report similar estimates in children with and without underlying conditions when stratified¹³. However, few studies assessed VE among children with specific underlying conditions, such as respiratory or immunocompromising conditions¹⁴. Understanding VE in these populations is crucial as these populations are disproportionately affected by severe influenza outcomes¹⁵. Further research could help improve vaccination strategies to reduce the incidence and severity of influenza in children with underlying conditions.

Our study uses data from the New Vaccine Surveillance Network (NVSN) to assess influenza VE in children with and without underlying conditions who presented to the ED or were hospitalized across five influenza seasons.

Methods

Study Design and Population

We used NVSN acute respiratory illness (ARI) surveillance data from 2015–2020 for children 6 months–17 years of age enrolled at seven U.S. pediatric medical centers to conduct a test negative design study to assess influenza VE against ED visits and hospitalizations among children with and without underlying conditions^16,17. ED enrollments did not occur at any site during the 2015–2016 influenza season. Kansas City, MO did not perform vaccine verification for children enrolled in the ED for the full study period; therefore, these data were not included in the ED analysis.

Research staff obtained written informed consent by each child’s parent or guardian and assent, when applicable, was provided by the child. Full inclusion/exclusion criteria have been previously reported^16,18. Briefly, we enrolled those who resided within each hospital’s catchment area, had an illness duration <14 days, and were enrolled <48 hours after hospital admission for an ARI-related condition. Children were excluded from enrollment if they experienced fever and neutropenia associated with malignancy, were readmitted within 4 days, were transferred from another hospital after an admission >48 hours or had a known non-respiratory condition that caused their hospitalization. Fever and neutropenia associated with malignancy was defined as a documented diagnosis of malignancy with an absolute neutrophil count <500 cells/μL measured within 72 hours of admission and fever, determined through chart review.

At enrollment, an interview was conducted with the parent/guardian of children enrolled to collect demographic data, illness characteristics, and medical and vaccination history. Race and ethnicity were self-reported or abstracted from the medical record and were collected given known associations between race/ethnicity and vaccine uptake, influenza infection, and healthcare utilization¹⁹. Children were categorized according to their highest level of care; children enrolled in the ED who were subsequently admitted were classified as inpatients.

Underlying Conditions

Underlying conditions data were abstracted from medical records for all seasons. Specific underlying conditions included in data abstraction were selected based on expert opinion on conditions that are associated with potentially higher risk of severe outcomes from a pediatric respiratory illness. During the 2015–2016 through 2017–2018 seasons, parents/guardians were also asked about their child’s underlying conditions upon enrollment. Indication of an underlying condition by either method was included in the analysis. Children with at least one of the following conditions were considered to have an underlying condition: respiratory, cardiovascular, neurological/neuromuscular, hematologic, oncologic/immunosuppressive, renal/urologic, endocrine, gastrointestinal/hepatic, developmental, genetic/metabolic, obesity, or other chronic illness/condition. Further details are available in Supplemental Table 1.

Influenza Testing and Vaccination Status

Our main outcome was influenza case status. During enrollment, research staff collected respiratory specimens or salvaged clinical specimens and tested the samples for influenza virus using reverse transcription-polymerase chain reaction (RT-PCR) assays. Additional details regarding participant enrollment, specimen collection, and testing have been previously published^16,20,21. Case-patients were children that tested positive for influenza by RT-PCR research or clinical molecular assays, and control-patients were children that tested negative for influenza by all research and clinical molecular assays performed. Those that received only non-molecular rapid antigen tests were excluded.

Our main exposure was vaccination status. Documentation from state immunization information systems or healthcare clinicians was used to determine current season influenza vaccination status for patients enrolled. Children were classified as vaccinated if they received at least one verified dose of the current season’s influenza vaccine ≥14 days before symptom onset.

Statistical Analysis

We used a test-negative design to assess influenza VE among children with and without underlying conditions. Children who (i) did not meet inclusion criteria or had an unknown symptom onset date; (ii) had inconclusive, discrepant, or missing influenza results; (iii) had unknown vaccination status or only self-reported vaccination status; or (iv) received influenza vaccine <14 days before symptom onset were excluded from final analyses.

Firth’s logistic regression models were used to estimate VE by comparing the odds of current season influenza vaccination in cases with influenza compared with test-negative controls adjusting for study site, age group, and calendar time of symptom onset²². Age group was categorized as 6–23 months, 2–8 years, and 9–17 years. Calendar time was defined as pre-peak, peak, and post-peak for each site-specific influenza season, where a site-specific influenza season’s peak period is defined as the two weeks prior through the two weeks following the week with the most influenza case-patients based on NVSN data at the site. These confounders were identified a priori consistent with prior NVSN seasonal and multi-season VE studies^{17,20,21,23–26}. Additional covariates were assessed because of their potential association with influenza status and vaccination uptake; however, we did not include additional confounders in the final models. Firth’s logistic regression models were used due to small sample size among some of the conditions. The adjusted odds ratio (aOR) was used to estimate VE using the following equation: (1 – aOR) × 100%. In subgroup analyses, we evaluated VE among children with the previously defined underlying condition categories, including those with multiple underlying condition categories. We also conducted subgroup analyses to assess VE by influenza type and subtype, age, and admission status among those with and without underlying conditions.

For infants and children 6 months–8 years, a sensitivity analysis was conducted where patients were classified as fully vaccinated if they received two doses of the current season’s influenza vaccine ≥14 days before illness onset. A separate sensitivity analysis was also conducted excluding infants aged 6 to 7 months to allow sufficient time to receive two influenza doses in the current season. Lastly, we assessed VE among children with only one underlying condition to isolate the impact of individual underlying conditions compared to the effect of multi-morbid conditions. To assess if underlying conditions were an effect measure modifier, we added an interaction term for vaccination status and underlying conditions to the a priori model and considered a p-value <0.05 as significant. All analyses were conducted in R version 4.1.2.

Ethics

This study was reviewed and approved by the Centers for Disease Control and Prevention (CDC) and participating sites’ institutional review boards ^§.

Results

Characteristics of Study Population

Of the 15,875 children included, 2,821 (18%) tested positive for influenza and 13,054 (82%) tested negative (Figure 1). Overall, 7,834 children (49%) were vaccinated and 8,041 (51%) were unvaccinated. Among influenza-positive cases, 33% were vaccinated (920/2821) compared to 53% of controls (6914/13054; Table 1). There were notable differences in demographic characteristics by influenza case and vaccination status. The median age of cases (4 years, interquartile range [IQR]: 2–7) was higher than that of controls (2 years, IQR: 1–5) while the median age of vaccinated children (2 years, IQR: 1–4 years) was lower compared to unvaccinated children (3 years, IQR: 1–6). The sex distribution was comparable by both case and vaccination status, but the proportion of Black, Non-Hispanic children was higher among cases (43%) compared to controls (31%) as well as among unvaccinated children enrolled (41%) compared to vaccinated children (24%). Among cases, 1,128 (40%) had at least one underlying condition compared to 6,067 (46%) controls. Respiratory conditions were the most common among both cases (25%) and controls (33%). Vaccinated children enrolled in our study were more likely to have at least one underlying condition (50%) compared to unvaccinated children (41%), including a higher frequency when stratified by individual underlying conditions.

Table 1.

Distribution of demographics and underlying conditions for children by influenza case- and vaccination status

Characteristic	Influenza Case-Status			Vaccination Status¹

	Influenza-Positive N = 2821	Influenza-Negative N = 13054	p-value²	Vaccinated N = 7834	Unvaccinated N = 8041	p-value²

Age (years), median (IQR)	4.0 (2.0, 7.0)	2.0 (1.0, 5.0)	<0.001	2.0 (1.0, 4.0)	3.0 (1.0, 6.0)	<0.001
Age, n (%)			<0.001			<0.001
6─23 months	675 (24%)	5798 (44%)		3797 (48%)	2676 (33%)
2─8 years	1583 (56%)	5515 (42%)		3043 (39%)	4055 (50%)
9─17 years	563 (20%)	1741 (13%)		994 (13%)	1310 (16%)
Sex, n (%)			0.900			0.200
Male	1557 (55%)	7229 (55%)		4378 (56%)	4408 (55%)
Female	1264 (45%)	5825 (45%)		3456 (44%)	3633 (45%)
Race-ethnicity, no./total no.³ (%)			<0.001			<0.001
White Non-Hispanic	725/2815 (26%)	4223/13008 (32%)		2855/7802 (37%)	2093/8021 (26%)
Black Non-Hispanic	1203/2815 (43%)	4021/13008 (31%)		1900/7802 (24%)	3324/8021 (41%)
Other Non-Hispanic	219/2815 (8%)	1202/13008 (9%)		772/7802 (10%)	649/8021 (8%)
Hispanic	668/2815 (24%)	3562/13008 (27%)		2275/7802 (29%)	1955/8021 (24%)
Underlying conditions⁴, no./total no.³ (%)			<0.001			<0.001
No underlying conditions	1693/2821 (60%)	6987/13054 (54%)		3941/7834 (50%)	4739/8041 (59%)
≥ 1 underlying condition	1128/2821 (40%)	6067/13054 (46%)		3893/7834 (50%)	3302/8041 (41%)
Respiratory	696/2821 (25%)	4357/13054 (33%)	<0.001	2701/7834 (34%)	2352/8041 (29%)	<0.001
Asthma	587/2821 (21%)	3512/13054 (27%)	<0.001	2015/7834 (26%)	2084/8041 (26%)	0.800
Cardiovascular	131/2768 (5%)	865/12847 (7%)	<0.001	691/7700 (9%)	305/7915 (4%)	<0.001
Neurological/Neuromuscular	213/2821 (8%)	1225/13054 (9%)	0.002	978/7834 (12%)	460/8041 (6%)	<0.001
Hematologic	116/2770 (4%)	474/12837 (4%)	0.200	355/7688 (5%)	235/7919 (3%)	<0.001
Oncologic/Immunosuppressive	71/2766 (3%)	356/12833 (3%)	0.600	311/7685 (4%)	116/7914 (2%)	<0.001
Renal/Urologic	36/2821 (1%)	204/13054 (2%)	0.300	164/7834 (2%)	76/8041 (0.9%)	<0.001
Endocrine	39/2767 (1%)	189/12834 (2%)	0.900	154/7684 (2%)	74/7917 (0.9%)	<0.001
Diabetes	21/2767 (0.8%)	45/12834 (0.4%)	0.005	41/7684 (0.5%)	25/7917 (0.3%)	0.049
Gastrointestinal/Hepatic	172/2821 (6%)	1120/13054 (9%)	<0.001	912/7834 (12%)	380/8041 (5%)	<0.001
Developmental	165/2821 (6%)	874/13052 (7%)	0.11	689/7834 (9%)	350/8039 (4%)	<0.001
Genetic/Metabolic	91/2772 (3%)	598/12855 (5%)	0.002	485/7704 (6%)	204/7923 (3%)	<0.001
Obesity⁵	155/750 (21%)	706/3721 (19%)	0.300	390/2185 (18%)	471/2286 (21%)	0.022
Other Chronic Condition	31/2821 (1%)	247/13054 (2%)	0.005	201/7834 (3%)	77/8041 (1%)	<0.001
Prematurity ⁶ , no./total no. (%)	122/674 (18%)	1291/5788 (22%)	0.014	821/3787 (22%)	592/2675 (22%)	0.700
Admission status, n (%)			<0.001			<0.001
Inpatient	1097 (39%)	8079 (62%)		5011 (64%)	4165 (52%)
Emergency Department	1724 (61%)	4975 (38%)		2823 (36%)	3876 (48%)
Influenza vaccination status, n (%)			<0.001
Vaccinated	920 (33%)	6914 (53%)		----	----
Unvaccinated	1901 (67%)	6140 (47%)		----	----
Influenza status						<0.001
Negative	----	----		6914 (88%)	6140 (76%)
Positive	----	----		920 (12%)	1901 (24%)
Influenza type and subtype, no./total no.³ (%)			<0.001			<0.001
A(H1N1)pdm09	836/2714 (31%)	----		244/7799 (3%)	592/7969 (7%)
A(H3N2)	952/2714 (35%)	----		351/7799 (5%)	601/7969 (8%)
B	926/2714 (34%)	----		290/7799 (4%)	636/7969 (8%)
Duration of illness at enrollment, n (%)			0.017			0.034
0─2 days	1503 (53%)	6592 (50%)		3947 (50%)	4148 (52%)
3─4 days	696 (25%)	3469 (27%)		2128 (27%)	2037 (25%)
5─7 days	494 (18%)	2255 (17%)		1331 (17%)	1418 (18%)
8─10 days	94 (3%)	537 (4%)		300 (4%)	331 (4%)
11─13 days	34 (1%)	201 (2%)		128 (2%)	107 (1%)
Study site, n (%)			<0.001			<0.001
Cincinnati OH	488 (17%)	1731 (13%)		897 (11%)	1322 (16%)
Houston TX	295 (10%)	2575 (20%)		1611 (21%)	1259 (16%)
Kansas City MO	94 (3%)	595 (5%)		295 (4%)	394 (5%)
Nashville TN	828 (29%)	3055 (23%)		1620 (21%)	2263 (28%)
Oakland CA	23 (0.8%)	297 (2%)		169 (2%)	151 (2%)
Pittsburgh PA	548 (19%)	2373 (18%)		1508 (19%)	1413 (18%)
Rochester NY	346 (12%)	1227 (9%)		815 (10%)	758 (9%)
Seattle WA	199 (7%)	1201 (9%)		919 (12%)	481 (6%)
Influenza season of enrollment, n (%)			<0.001			<0.001
2015─2016	144 (5%)	1566 (12%)		966 (12%)	744 (9%)
2016─2017	538 (19%)	2857 (22%)		1761 (22%)	1634 (20%)
2017─2018	696 (25%)	2990 (23%)		1575 (20%)	2111 (26%)
2018─2019	624 (22%)	2794 (21%)		1876 (24%)	1542 (19%)
2019─2020	819 (29%)	2847 (22%)		1656 (21%)	2010 (25%)

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Abbreviations: IQR interquartile range; CA California; MO Missouri; NY New York; OH Ohio; PA Pennsylvania; TN Tennessee; TX Texas; WA Washington;

Vaccination status based on verified influenza vaccination records from healthcare providers and immunization information systems, children were defined as vaccinated if they received at least one verified dose of current season influenza vaccine ≥ 14 days before symptom onset

Wilcoxon rank sum test; Pearson’s Chi-squared test

The denominator for some of these characteristics is different from the total number of cases/controls or vaccinated/unvaccinated patients due to missingness

⁴

Influenza case-patients had a median of 1 specific underlying condition (IQR: 1–3) and a median of 1 underlying condition categories (IQR: 1–2)

⁵

Obesity only calculated for children ≥ 24 months of age and based on BMI ≥ 95^th percentile from 2000 CDC growth charts³⁸, calculated using cdcanthro package in R version 4.1.2

⁶

Prematurity only calculated for children ≤ 23 months of age and defined as children born < 37 weeks gestational age

Among cases with at least one underlying condition, respiratory conditions were the most common, regardless of the enrollment setting (Figure 2). Underlying conditions were more common in hospitalized influenza case-patients than in the ED. The proportion of hospitalized cases who were vaccinated was higher among those with at least one underlying condition (43%) compared to those without (33%; Table 2). The proportion of supplemental oxygen use and intensive care unit (ICU) admission was higher among cases with at least one underlying condition (42% and 17%, respectively) than cases with no underlying conditions (28% and 12%, respectively).

Table 2.

Disease severity among hospitalized influenza case-patients with and without underlying conditions by influenza vaccination status

Characteristic	At Least One Underlying condition¹			No Underlying conditions

	Total	Vaccinated²	Unvaccinated	Total	Vaccinated²	Unvaccinated

Hospitalization, N (%)	653	278 (43%)	375 (57%)	444	146 (33%)	298 (67%)
Hospital stay (days), median (IQR)	2 (1 – 3)	2 (1 – 3)	2 (1 – 3)	1 (1 – 2)	2 (1 – 2)	1 (1 – 2)
Need for supplemental oxygen, no./total no.³ (%)	277/652 (42%)	115/278 (41%)	162/374 (43%)	125/444 (28%)	46/146 (32%)	79/298 (27%)
ICU, no./total no.³ (%)	95/569 (17%)	42/238 (18%)	53/331 (16%)	47/381 (12%)	19/127 (15%)	28/254 (11%)
ICU stay (days), median (IQR)	3 (2 – 7)	3 (1 – 7)	3 (2 – 6.75)	2 (1 – 4)	2.5 (1 – 4)	2 (1.5 – 4.5)
Need for intubation, no./total no.³ (%)	21/569 (4%)	10/238 (4%)	11/331 (3%)	13/380 (3%)	5/127 (4%)	8/253 (3%)
ECMO, no./total no.³ (%)	0/569 (0%)	0/238 (0%)	0/331 (0%)	1/381 (0.3%)	0/127 (0%)	1/254 (0.4%)
Death, no./total no.³ (%)	1/569 (0.2%)	0/238 (0%)	1/331 (0.3%)	1/380 (0.3%)	0/127 (0%)	1/253 (0.4%)

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Abbreviations: ECMO Extracorporeal Membrane Oxygenation; ICU intensive care unit; IQR interquartile range

Underlying condition defined as the presence of at least one of the following conditions: respiratory, cardiovascular, neurologic/neuromuscular, hematologic, oncologic/immunosuppressive, renal/urologic, endocrine, gastrointestinal/hepatic, developmental disorders, genetic/metabolic, obesity, or other chronic conditions. Hospitalized influenza case-patients had a median of 2 (IQR: 1 – 3) underlying conditions.

Vaccination status is based on verified influenza vaccination records from healthcare providers and immunization information systems, children were defined as vaccinated if they received at least one verified dose of current season influenza vaccine ≥ 14 days before symptom onset

The denominator for some of these characteristics is different from the total number of vaccinated and unvaccinated patients due to missingness

Among controls, 57% of those with at least one underlying condition were vaccinated compared to 50% of those with no underlying conditions (Figure 3). The percentage of those vaccinated varied by underlying condition category. Vaccination was lowest among controls with obesity (48%) and highest among controls with oncologic/immunosuppressive conditions (75%).

Figure 3. — Abbreviations: CI, confidence interval; VE, vaccine effectiveness; ED, emergency department

¹Vaccination status is based on verified influenza vaccination records from healthcare clinicians and immunization information systems, children were defined as vaccinated if they received at least one verified dose of current season influenza vaccine ≥ 14 days before symptom onset.

²VE calculated as (1 − aOR)*100 using firth logistic regression models adjusted for age (categorized 6–23 mon, 2–8 yrs, 9–17 yrs), study site, and calendar time of symptom onset (influenza season peak tertiles).

³Underlying conditions defined as presence of at least one of the following conditions: respiratory, cardiovascular, neurologic/neuromuscular, hematologic, oncologic/immunosuppressive, renal/urologic, endocrine, gastrointestinal/hepatic, developmental disorders, genetic/metabolic, obesity, or other chronic conditions. VE only reported for conditions that had sufficient sample size.

Vaccine Effectiveness

Among children admitted to the hospital or seen in the ED, VE was 43% (95% confidence interval [CI]: 35–50%) for children with at least one underlying condition and 53% (95% CI: 47–59%) among children without underlying conditions (Figure 3). There was a significant difference in overall VE by the presence of underlying conditions (p=0.04). Effect measure modification by the presence of underlying conditions was not significant among only hospitalized children (p=0.25) but was significant among children enrolled in the ED (p=0.03). Among hospitalized children, VE was 44% (95% CI: 33–53%) for those with underlying conditions compared to 54% (95% CI: 43–63%) for those without (Figure 4). VE was 32% (95% CI: 15–46%) for children in the ED with at least one underlying condition and 51% (95% CI: 42–58%) among those without.

Figure 4. — Abbreviations: CI, confidence interval; VE, vaccine effectiveness

¹Vaccination status is based on verified influenza vaccination records from healthcare clinicians and immunization information systems, children were defined as vaccinated if they received at least one verified dose of current season influenza vaccine ≥ 14 days before symptom onset

²VE calculated as (1 − aOR)*100 using Firth’s logistic regression models adjusted for age (categorized 6–23 mon, 2–8 yrs, 9–17 yrs), study site, and calendar time of symptom onset (influenza season peak tertiles)

³VE calculated as (1 − aOR)*100 using Firth’s logistic regression models adjusted for study site and calendar time of symptom onset (influenza season peak tertiles)

Further, VE against influenza illness varied by the type of underlying condition, inclusive of those with or without other co-morbid conditions. The lowest VE point estimate was among those with respiratory conditions (31%, 95% CI: 19–42%) compared to the highest VE among children with endocrine conditions (64%, 95% CI: 34–81%; Figure 3). Among children with asthma, VE against influenza illness was 30% (95% CI: 16–42%). For those with oncologic/immunosuppressive conditions, VE was 48% (95% CI: 9–70%), and for neurological/neuromuscular conditions, VE was 53% (95% CI: 36–65%).

Sensitivity Analyses

Results from sensitivity analyses were consistent with the primary findings. When restricting analyses to children 6 months–8 years who were fully vaccinated with two doses in the same season, VE estimates were similar to those observed in the main analysis (Supplemental Table 2). Excluding infants aged 6–7 months to allow time for full vaccination did not change VE estimates (Supplemental Table 3). Likewise, limiting the analysis to children with only one underlying condition yielded VE estimates comparable to those observed when including children with multiple comorbidities (Supplemental Table 4).

Discussion

Our study, using five influenza seasons in the United States, offers insights into VE against laboratory-confirmed influenza in children with underlying conditions. In our study, nearly half of hospitalized children with influenza and 40% of children seen in the ED had underlying conditions. We noted a lower VE of 43% against influenza illness among children with underlying conditions, compared to 53% VE observed among those without underlying conditions, although confidence intervals overlapped when stratified. We also found varying VE estimates for specific conditions, such as respiratory or immunocompromising conditions, but all demonstrated significant protection, suggesting that influenza vaccination remains broadly effective for all children. It is important to note, however, that underlying conditions may influence VE through different mechanisms. For immunocompromising conditions, reduced VE may reflect impaired immune response to vaccination, whereas for respiratory conditions, vaccination may elicit an adequate immune response, but influenza infection can exacerbate the underlying disease, contributing to illness severity. This distinction may help explain why VE estimates were lower for respiratory conditions than for immunosuppressive conditions in our study, though small subgroup sizes limit interpretation. Vaccination uptake among children with different conditions varied from less than half to three quarters, highlighting the importance of targeted interventions to increase vaccination rates among children with underlying conditions.

Our point estimates for VE against ED visits and hospital admissions were generally similar for those with at least one underlying condition compared to those without underlying conditions. These findings were reflective of previous studies. One study that examined effectiveness against death reported a VE of 65% among those without underlying conditions and a slightly lower but comparable VE of 51% among those with underlying conditions²⁷. Similarly, a study of children in the US outpatient setting reported nearly identical VE estimates of 51% and 52% for children with and without underlying conditions, respectively, though some differences in point estimates were observed by specific underlying conditions¹³.

We found that a higher percentage of influenza case-patients that were hospitalized had at least one underlying condition compared to those in the ED. This aligns with previous studies that found higher incidence of hospitalization in children with underlying conditions^28,29. Case-patients with at least one underlying condition were also more likely to exhibit severe outcomes when hospitalized, regardless of vaccination status, compared to their counterparts without underlying conditions. We observed that among children with influenza, those with at least one underlying condition were more likely to require supplemental oxygen and ICU admission compared to those without underlying conditions which may indicate a higher burden of disease for those with underlying conditions. In our study, 17% of influenza case-patients with underlying conditions were admitted to the ICU compared to 12% of those without. Other studies also found presence of underlying conditions to be a risk factor for severe outcomes in hospitalized children^30–32. This indicates that increased influenza vaccination uptake in those with underlying conditions, could help alleviate burden among this population at higher risk of severe influenza.

We also noted that influenza vaccine uptake appeared low in both children with and without underlying conditions in our study, varying heavily by condition type. Asthma was the most common underlying condition in our study, which is consistent with other studies showing a higher prevalence of asthma among children with influenza^16,17. The CDC considers those with asthma to be at high-risk for complications from influenza⁸; however, we found lower VE (30%) as well as low vaccine uptake (51%) among this group. Lower VE in children with asthma may be influenced by underlying immune dysfunction and allergic inflammation, which have been suggested to impair antibody responses; however, waning was not assessed in our study³³. Additionally, corticosteroid use, which is common in asthma treatment, may contribute to reduced VE³⁴. While our findings reflect uptake within the study population rather than population-level coverage, the observation of suboptimal vaccination uptake among these children with underlying conditions remains concerning. Lower vaccine uptake among these children with underlying conditions is particularly concerning given that our study reflects the pre-COVID-19 era, and vaccination uptake is likely to be even lower currently with the decline in vaccination rates and increase in vaccine hesitancy since the COVID-19 pandemic^25,35–37. Given the increased risk for severe influenza complications in children with underlying conditions, it is crucial to identify strategies to improve vaccination uptake and investigate new approaches to vaccination in these populations.

This study fills an important gap by offering detailed comparisons of influenza VE among children with underlying conditions. The multi-season, multi-site surveillance across diverse pediatric medical centers improves the generalizability of our findings. However, several limitations should be considered. The observational design may introduce bias, as we could not account for differences in hospital admission thresholds by condition, potentially affecting VE comparisons and limiting direct comparisons across groups. Clinician bias may have also influenced VE estimates, as children with underlying conditions may have a lower threshold for seeking care or being hospitalized. Further, small sample sizes in some subgroups, particularly those without other comorbidities, limited our ability to assess VE by isolated underlying conditions. Larger, more adequately powered studies focused on specific populations could help guide targeted vaccination strategies. We also excluded febrile children with neutropenia which may have inadvertently omitted early hematopoietic stem cell transplant recipients or children with severe oncologic or immunosuppressive conditions, limiting generalizability of our study for these groups. Height and weight data were also unavailable for over half of children above the age of 2, precluding accurate assessment of obesity and its potential impact on VE. In addition, our study only included ED and inpatient encounters and did not capture outpatient visits, which may limit generalizability of our findings across all care settings. Additionally, the timing of underlying conditions in relation to vaccination could not be assessed, as the date of diagnosis was not collected. Lastly, the use of the test-negative design and our classification of vaccination status and influenza testing are subject to the same limitations described in previous VE studies from this network^{17,20,21,23,24}. Further, an essential component of the test-negative design is that patients enrolled are healthcare-seeking, meaning they may be more likely to be vaccinated. While this increases the likelihood of vaccination within the test-negative design, both cases and controls are subject to the same bias.

In conclusion, our study demonstrated that influenza vaccination was effective in reducing laboratory-confirmed influenza among U.S. children with and without underlying conditions who presented to the ED or were hospitalized across multiple seasons. Although VE was lower in children with certain underlying conditions, the estimates were similar to those in children without these conditions, and influenza vaccination remains a crucial tool in preventing severe influenza outcomes in these groups. Our study lays the groundwork for future investigations aimed at refining influenza prevention strategies for these vulnerable groups and could help future pediatric vaccination policies. Efforts to improve influenza vaccine uptake and initiate early treatment for influenza, particularly among children with underlying conditions, should be prioritized to reduce the burden of influenza among pediatric populations.

Supplementary Material

Supplemental Materials

NIHMS2150159-supplement-Supplemental_Materials.docx^{(49.6KB, docx)}

What’s Known on This Subject

Children with certain underlying conditions are at increased risk for severe influenza complications. While annual influenza vaccination is recommended for all children, aged ≥6 months, previous studies have shown varying VE in children with and without underlying conditions.

What This Study Adds

This study provides influenza VE estimates among children with specific underlying conditions. It highlights the need for targeted strategies to improve influenza vaccine uptake and to investigate new approaches to vaccination in pediatric populations.

Acknowledgments

We thank the patients and their families who participated in this assessment. We also thank the NVSN teams at each of these sites for enrollment, testing, and data collection:

Vanderbilt University Medical Center, Nashville, TN; Texas Children’s Hospital, Houston, TX; UPMC Children’s Hospital of Pittsburgh, PA; Seattle Children’s Research Institute, Seattle, WA; Cincinnati Children’s Hospital Medical Center, Cincinnati, OH; Children’s Mercy Kansas City, Kansas City, MO; University of Rochester Medical Center, Rochester, NY; and University of California San Francisco Benioff Children’s Hospital Oakland, Oakland, CA.

Funding/Support:

This study is supported by the US Centers for Disease Control and Prevention

Role of Funder/Sponsor (if any):

The US Centers for Disease Control and Prevention was involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, and approval of the manuscript; and decision to submit the manuscript for publication.

Abbreviations:

aOR: adjusted odds ratio
CA: California
ED: emergency department
ICU: intensive care unit
IQR: interquartile range
MO: Missouri
NVSN: New Vaccine Surveillance Network
NY: New York
OH: Ohio
PA: Pennsylvania
RT-PCR: reverse transcription-polymerase chain reaction
TN: Tennessee
TX: Texas
US: United States
VE: vaccine effectiveness
WA: Washington

Footnotes

^§

See 45 C.F.R. part 46.114; 21 C.F.R. part 56.114

Conflict of Interest Disclosures (includes financial disclosures):

L.C.S. reports travel support from the Gates Foundation to attend a meeting.

M.G.M. reports grant support from the National Institutes of Health and a waiver of admission fees for speaking at the American Transplant Congress 2024.

J.V.W. reports grant support from the National Institutes of Health, consulting fees from Quidel for serving on a Scientific Advisory Board, an honorarium for a lecture in the Infectious Diseases of Children conference, and compensation for participation in the Independent Data Monitoring Committee (GlaxoSmithKline) and Data Safety Monitoring Board (NIAID IMPAACT study).

J.A.E. reports grant support from AstraZeneca, Pfizer, Merck, GlaxoSmithKline, and Moderna, consulting fees from Pfizer, Meissa Vaccine, Moderna Vaccines, AstraZeneca, GlaxoSmithKline, Merck, and Shionogi, and travel payments from AstraZeneca and Pfizer for lectures.

M.A.S. reports grant support from the National Institutes of Health, Cepheid, and Merck, support for contributions to UpToDate chapters, and consulting fees from Merck.

E.P.S. reports grant support from Pfizer, an honorarium from Sanofi Pasteur, travel funds from the Pediatric Infectious Diseases Society, participation on a DMID Data Safety Monitoring Board, and roles as a board member in the World Society of Pediatric Infectious Diseases and committee chair in the Pediatric Infectious Diseases Society.

R.S. reports grant support from Hologic, BioFire, Becton Dickinson, Luminex, and Cepheid and payment for serving on an Advisory Board from GlaxoSmithKline.

G.A.W. reports grant support from the AIDS Institute of the New York State Department of Health, consulting fees from the New York State Department of Health and Inhalon Biopharma, an honorarium from Merck, and board participation at Emory University.

N.B.H. reports grant support from Sanofi, Quidel, and Merck and an honorarium from Genentech.

S.M.O. reports travel support from the Gates Foundation to attend a meeting.

Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

References

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Associated Data

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

Supplementary Materials

Supplemental Materials

NIHMS2150159-supplement-Supplemental_Materials.docx^{(49.6KB, docx)}

[R1] 1.Neuzil KM, Mellen BG, Wright PF, Mitchel EF Jr., Griffin MR The effect of influenza on hospitalizations, outpatient visits, and courses of antibiotics in children. N Engl J Med. Jan 27 2000;342(4):225–31. doi: 10.1056/NEJM200001273420401 [DOI] [PubMed] [Google Scholar]

[R2] 2.Layne SP, Beugelsdijk TJ, Patel CK, et al. A global lab against influenza. Science. Sep 7 2001;293(5536):1729. doi: 10.1126/science.293.5536.1729 [DOI] [PubMed] [Google Scholar]

[R3] 3.Wang X, Li Y, O’Brien KL, et al. Global burden of respiratory infections associated with seasonal influenza in children under 5 years in 2018: a systematic review and modelling study. Lancet Glob Health. Apr 2020;8(4):e497–e510. doi: 10.1016/S2214-109X(19)30545-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R4] 4.Prevention CfDCa. Preliminary Estimated Flu Disease Burden 2023–2024 Flu Season. Accessed [March 26, 2025], https://www.cdc.gov/flu-burden/php/data-vis/2023-2024.html

[R5] 5.Committee on Infectious D. Recommendations for Prevention and Control of Influenza in Children, 2024–2025: Policy Statement. Pediatrics. Oct 1 2024;154(4)doi: 10.1542/peds.2024-068507 [DOI] [PubMed] [Google Scholar]

[R6] 6.Kondrich J, Rosenthal M. Influenza in children. Curr Opin Pediatr. Jun 2017;29(3):297–302. doi: 10.1097/MOP.0000000000000495 [DOI] [PubMed] [Google Scholar]

[R7] 7.Nayak J, Hoy G, Gordon A. Influenza in Children. Cold Spring Harb Perspect Med. Jan 4 2021;11(1)doi: 10.1101/cshperspect.a038430 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R8] 8.Grohskopf LA, Ferdinands JM, Blanton LH, Broder KR, Loehr J. Prevention and Control of Seasonal Influenza with Vaccines: Recommendations of the Advisory Committee on Immunization Practices - United States, 2024–25 Influenza Season. MMWR Recomm Rep. Aug 29 2024;73(5):1–25. doi: 10.15585/mmwr.rr7305a1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R9] 9.Tenforde MW, Reeves EL, Weber ZA, et al. Influenza vaccine effectiveness against hospitalizations and emergency department or urgent care encounters for children, adolescents, and adults during the 2023–2024 season, United States. Clin Infect Dis. Dec 4 2024;doi: 10.1093/cid/ciae597 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R10] 10.Chung JR, Price AM, Zimmerman RK, et al. Influenza vaccine effectiveness against medically attended outpatient illness, United States, 2023–24 season. Clin Infect Dis. Jan 6 2025;doi: 10.1093/cid/ciae658 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R11] 11.Boddington NL, Pearson I, Whitaker H, Mangtani P, Pebody RG. Effectiveness of Influenza Vaccination in Preventing Hospitalization Due to Influenza in Children: A Systematic Review and Meta-analysis. Clin Infect Dis. Nov 2 2021;73(9):1722–1732. doi: 10.1093/cid/ciab270 [DOI] [PubMed] [Google Scholar]

[R12] 12.Hood N, Flannery B, Gaglani M, et al. Influenza Vaccine Effectiveness Among Children: 2011–2020. Pediatrics. Apr 1 2023;151(4)doi: 10.1542/peds.2022-059922 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R13] 13.Shang M, Chung JR, Jackson ML, et al. Influenza vaccine effectiveness among patients with high-risk medical conditions in the United States, 2012–2016. Vaccine. Dec 18 2018;36(52):8047–8053. doi: 10.1016/j.vaccine.2018.10.093 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R14] 14.Fiore AE, Uyeki TM, Broder K, et al. Prevention and control of influenza with vaccines: recommendations of the Advisory Committee on Immunization Practices (ACIP), 2010. MMWR Recomm Rep. Aug 6 2010;59(RR-8):1–62. [PubMed] [Google Scholar]

[R15] 15.Coffin SE, Zaoutis TE, Rosenquist AB, et al. Incidence, complications, and risk factors for prolonged stay in children hospitalized with community-acquired influenza. Pediatrics. Apr 2007;119(4):740–8. doi: 10.1542/peds.2006-2679 [DOI] [PubMed] [Google Scholar]

[R16] 16.Perez A, Lively JY, Curns A, et al. Respiratory Virus Surveillance Among Children with Acute Respiratory Illnesses - New Vaccine Surveillance Network, United States, 2016–2021. Mmwr-Morbid Mortal W. Oct 7 2022;71(40):1253–1259. doi: 10.5487/resp.87841 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R17] 17.Sahni LC, Naioti EA, Olson SM, et al. Sustained Within-season Vaccine Effectiveness Against Influenza-associated Hospitalization in Children: Evidence From the New Vaccine Surveillance Network, 2015–2016 Through 2019–2020. Clin Infect Dis. Feb 8 2023;76(3):e1031–e1039. doi: 10.1093/cid/ciac577 [DOI] [PubMed] [Google Scholar]

[R18] 18.Rha B, Curns AT, Lively JY, et al. Respiratory Syncytial Virus-Associated Hospitalizations Among Young Children: 2015–2016. Pediatrics. Jul 2020;146(1)doi: 10.1542/peds.2019-3611 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R19] 19.Macias-Konstantopoulos WL, Collins KA, Diaz R, et al. Race, Healthcare, and Health Disparities: A Critical Review and Recommendations for Advancing Health Equity. West J Emerg Med. Sep 2023;24(5):906–918. doi: 10.5811/westjem.58408 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R20] 20.Campbell AP, Ogokeh C, Lively JY, et al. Vaccine Effectiveness Against Pediatric Influenza Hospitalizations and Emergency Visits. Pediatrics. Nov 2020;146(5)doi: 10.1542/peds.2020-1368 [DOI] [PubMed] [Google Scholar]

[R21] 21.Feldstein LR, Ogokeh C, Rha B, et al. Vaccine Effectiveness Against Influenza Hospitalization Among Children in the United States, 2015–2016. J Pediatric Infect Dis Soc. Mar 26 2021;10(2):75–82. doi: 10.1093/jpids/piaa017 [DOI] [PubMed] [Google Scholar]

[R22] 22.Firth D Bias Reduction of Maximum-Likelihood-Estimates. Biometrika. Mar 1993;80(1):27–38. doi:DOI 10.1093/biomet/80.1.27 [DOI] [Google Scholar]

[R23] 23.Campbell AP, Ogokeh C, Weinberg GA, et al. Effect of Vaccination on Preventing Influenza-Associated Hospitalizations Among Children During a Severe Season Associated With B/Victoria Viruses, 2019–2020. Clin Infect Dis. Aug 16 2021;73(4):e947–e954. doi: 10.1093/cid/ciab060 [DOI] [PubMed] [Google Scholar]

[R24] 24.Kim SS, Naioti EA, Halasa NB, et al. Vaccine Effectiveness Against Influenza Hospitalization and Emergency Department Visits in 2 A(H3N2) Dominant Influenza Seasons Among Children <18 Years Old-New Vaccine Surveillance Network 2016–2017 and 2017–2018. J Infect Dis. Aug 12 2022;226(1):91–96. doi: 10.1093/infdis/jiab624 [DOI] [PMC free article] [PubMed] [Google Scholar]

[R25] 25.Frutos AM, Price AM, Harker E, et al. Interim Estimates of 2023–24 Seasonal Influenza Vaccine Effectiveness - United States. MMWR Morb Mortal Wkly Rep. Feb 29 2024;73(8):168–174. doi: 10.15585/mmwr.mm7308a3 [DOI] [PMC free article] [PubMed] [Google Scholar]

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Influenza Vaccine Effectiveness among Children with and without Underlying Conditions

Haya Hayek, MD

Emma K Noble, MSPH

Laura S Stewart, PhD

Leila C Sahni, PhD, MPH

Julie A Boom, MD

Marian G Michaels, MD, MPH

John V Williams, MD

Janet A Englund, MD

Eileen J Klein, MD, MPH

Mary A Staat, MD, MPH

Elizabeth P Schlaudecker, MD, MPH

Rangaraj Selvarangan, BVSc, PhD

Jennifer E Schuster, MD, MSc

Geoffrey A Weinberg, MD

Peter G Szilagyi, MD, MPH

Benjamin R Clopper, MPH

Heidi L Moline, MD, MPH

Kelsey M Sumner, PhD

Natasha B Halasa, MD, MPH

Samantha M Olson, MPH

Abstract

Objective

Methods

Results

Conclusion

Article Summary

Introduction

Methods

Study Design and Population

Underlying Conditions

Influenza Testing and Vaccination Status

Statistical Analysis

Ethics

Results

Characteristics of Study Population

Figure 1.

Table 1.

Figure 2. Percentage of influenza case-patients with each underlying condition category1 across emergency department and inpatient settings.

Table 2.

Figure 3. Influenza vaccine effectiveness against influenza illness in children with and without at least one underlying condition.

Vaccine Effectiveness

Figure 4. Influenza vaccine effectiveness against influenza-associated hospitalization or emergency department visits among patients with and without underlying conditions by influenza type and subtype, age, and admission status.

Sensitivity Analyses

Discussion

Supplementary Material

What’s Known on This Subject

What This Study Adds

Acknowledgments

Funding/Support:

Role of Funder/Sponsor (if any):

Abbreviations:

Footnotes

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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