Influenza Vaccine Effectiveness Against Pediatric Deaths: 2016-2025
Leonard, J. S.; Reinhart, K.; Lu, P.-J.; Santibanez, T.; Srivastav, A.; Hung, M.-C.; Jain, A.; Budd, A.; Huang, S.; Kniss, K.; Price, A. M.; Burns, E.; Ellington, S.; Flannery, B.
Show abstract
BACKGROUND AND OBJECTIVESSeasonal influenza vaccination has been shown to reduce the risk of influenza and severe complications among children 6 months and older. Since 2010, reported numbers of influenza-associated pediatric deaths among children aged <18 years have ranged from 37 during the 2011-2012 season to 289 during 2024-2025. We estimated influenza vaccine effectiveness (VE) against pediatric death from 2016-2017 through 2024-2025. METHODSWe conducted a case-cohort analysis comparing current season influenza vaccination status among reported influenza-associated pediatric deaths with survey estimates of influenza vaccination coverage in pediatric age groups. Underlying medical conditions and current seasonal influenza vaccination were obtained from surveillance case reports. We estimated vaccination odds ratios (OR) and 95% confidence intervals (CI) from logistic regression comparing influenza vaccination among children who died with vaccination coverage in comparison cohorts. VE was calculated as (1 - OR) x 100. RESULTSFrom August 2016 through July 2025, 1234 laboratory-confirmed influenza-associated pediatric deaths were reported among children aged 6 months--17 years. Of 1086 reported deaths including influenza vaccination information, 124 (23%) of 530 children with underlying medical conditions and 70 (13%) of 556 children without known conditions were fully vaccinated against influenza. Average influenza vaccination coverage in survey cohorts was 49%. VE was 80% (95% CI, 75% to 84%) overall, 77% (95% CI, 71% to 82%) among children with underlying medical conditions and 87% (95% CI, 84% to 89%) among children without known conditions. CONCLUSIONSInfluenza vaccination reduced risk of fatal influenza among children with or without known underlying medical conditions.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Increased Influenza Severity in Children in the Wake of SARS-CoV-2 94%
- Inpatient Burden of Respiratory Syncytial Virus Infection and Influenza in Children Younger than 5 years in Japan, 2011-2022: A database study 93%
- Prior SARS-CoV-2 Infection and COVID-19 Vaccine Effectiveness against Outpatient Illness during Widespread Circulation of SARS-CoV-2 Omicron Variant, US Flu VE Network 93%
Similar papers in this journal
- Evaluation of a city-wide school-located influenza vaccination program in Oakland, California with respect to race and ethnicity: a matched cohort study 96%
- Assessment of Potential Adverse Events Following the 2022–2023 Seasonal Influenza Vaccines Among U.S. Adults Aged 65 Years and Older 95%
- Safety Monitoring of Health Outcomes following Influenza Vaccination during the 2023-2024 Season among U.S. Medicare Beneficiaries Aged 65 Years and Older 95%
Similar papers in this journal
- Effectiveness of Influenza Vaccines in the HIVE household cohort over 8 years: is there evidence of indirect protection? 95%
- The Nicaraguan Pediatric Influenza Cohort Study, 2011-2019: influenza incidence, seasonality, and transmission 94%
- Effectiveness of 13-valent pneumococcal conjugate vaccine against medically-attended lower respiratory tract infection and pneumonia among older adults 93%
Similar papers in this journal
- Risk factors for severe COVID-19 in hospitalized children in Canada: A national prospective study from March 2020–May 2021 93%
- Vaccination reduces need for emergency care in breakthrough COVID-19 infections: A multicenter cohort study 93%
- Effectiveness of CoronaVac in the setting of high SARS-CoV-2 P.1 variant transmission in Brazil: A test-negative case-control study 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.