Scholarlink

<p>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 Using a Bayesian model, we synthesised published data from a systematic literature review and unpublished data shared by international collaborators for estimating the distribution of infant RSV hospitalisations by month of age.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.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Respiratory syncytial virus hospitalisation by chronological month of age and by birth month in infants

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月3日

查看全文
  • 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,
  • Zakhar Shchomak,
  • Rosário Barreto,
  • Julia Dvorkin,
  • Florence Morfin-Sherpa,
  • Karseladze Irakli,
  • Zakhashvili Khatuna,
  • Tarkhan-Mouravi Olgha,
  • Tim Wood,
  • Martin Mutunga,
  • Agustus Kea,
  • Luo Ren,
  • Na Zang,
  • Yu Deng,
  • Dina Mrcela,
  • Mohinder Sarna,
  • Belaynew Taye,
  • Huong Le,
  • Nicole Wolter,
  • Cheryl Cohen,
  • Sibongile Walaza,
  • Patrick E. Obermeier,
  • Paula Enriquez,
  • Ivan Rodriguez,
  • Dominique Ploin,
  • Horvat Come,
  • Olga Lopez,
  • Andres Bugueño,
  • Alfonso Cepeda,
  • Christine Desnoyers,
  • Sara Bressler,
  • Heather Scobie,
  • Giselle Soto,
  • Isabel Bazan,
  • Roger Hernandez,
  • Harish Nair,
  • You Li,
  • Xin Wang,
  • Hanna Nohynek,
  • Louis Bont,
  • Peter Openshaw,
  • Andrew Pollard,
  • Veena Kumar,
  • Elizabeth Begier,
  • Jim Janimak,
  • Jenny Hendrix,
  • Rolf Kramer,
  • Eva Molero

摘要

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.