Respiratory syncytial virus hospitalisation by chronological month of age and by birth month in infants
Ling Guo,
Sebastien Kenmoe,
Fuyu Miyake,
Alexandria Chung,
Han Zhang,
Teresa Bandeira,
Mauricio T. Caballero,
Jean-Sébastien Casalegno,
Rodrigo Fasce,
Chakhunashvili Giorgi,
Terho Heikkinen,
Q. Sue Huang,
Esther Nyadzua Katama,
James W. Keck,
Enmei Liu,
Josko Markic,
Hannah C. Moore,
Jocelyn Moyes,
Barbara A. Rath,
Candice Romero,
Qianli Wang,
Marta Werner,
Chee Fu Yung,
Harish Nair and
You Li ()
Additional contact information
Ling Guo: Nanjing Medical University
Sebastien Kenmoe: University of Edinburgh
Fuyu Miyake: University of Edinburgh
Alexandria Chung: University of Edinburgh
Han Zhang: Nanjing Medical University
Teresa Bandeira: Centro Hospitalar Universitário Lisboa Norte
Mauricio T. Caballero: Universidad Nacional de San Martin
Jean-Sébastien Casalegno: Laboratoire de Virologie
Rodrigo Fasce: Institute of Public Health
Chakhunashvili Giorgi: National Center for Disease Control and Public Health
Terho Heikkinen: University of Turku
Q. Sue Huang: Institute of Environmental Science and Research
Esther Nyadzua Katama: KEMRI-Wellcome Trust Research Programme
James W. Keck: Alaska Native Tribal Health Consortium
Enmei Liu: Children’s Hospital of Chongqing Medical University
Josko Markic: University Hospital of Split
Hannah C. Moore: The Kids Research Institute Australia
Jocelyn Moyes: National Institute for Communicable Diseases
Barbara A. Rath: Vaccine Safety Initiative
Candice Romero: Culmen International Company
Qianli Wang: Fudan University
Marta Werner: Grant Benavente Clinical Hospital
Chee Fu Yung: KK Women’s and Children’s Hospital
Harish Nair: Nanjing Medical University
You Li: Nanjing Medical University
Nature Communications, 2025, vol. 16, issue 1, 1-13
Abstract:
Abstract Understanding the distribution of respiratory syncytial virus (RSV) disease burden by more granular age bands in infants is necessary for optimising infant RSV immunisation strategies. Using a Bayesian model, we synthesised published data from a systematic literature review and unpublished data shared by international collaborators for estimating the distribution of infant RSV hospitalisations by month of age. Based on local RSV seasonality data, we further developed and validated a web-based prediction tool for estimating infant RSV hospitalisation distribution by birth month. Although RSV hospitalisation burden mostly peaked at the second month of life and was concentrated in infants under six months globally, substantial variations were noted in the age distribution of RSV hospitalisation among infants born in different months. Passive immunisation strategies should ideally be tailored to the local RSV disease burden distribution by age and birth month to maximise their per-dose effectiveness before a universal immunisation can be achieved.
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-61400-1
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DOI: 10.1038/s41467-025-61400-1
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