Regional and type-specific variations in the global seasonality of human parainfluenza viruses and the influence of climatic factors: a systematic review and meta-analysis

作者：Junru Chen, Shuyu Deng, Xiaoyu Xu, Shuting Chen, Yara‐Natalie Abo, Quique Bassat, Jikui Deng, Andrey B. Komissarov, Enmei Liu, Carmen Muñoz‐Almagro, Ren Luo, K. A. Stolyarov, Jane Tomlinson, Zhiqing Cai, Mengling Qiao, You Li, Xin Wang, Maria Cisneros, Andrew Daley, Daria Danilenko, Guangcheng Deng, Yu Deng, Cristian Launes, Aleix Lluansi, Oula Mansour, Yuyi Tang, Gregory Waller, Na Zang, Jinjun Zheng · 发表于：The Lancet Global Health · 年份：2025 · DOI：10.1016/s2214-109x(25)00188-3 · 被引用次数：8 · 研究领域：Respiratory viral infections research、Virology and Viral Diseases、Viral Infections and Vectors

Background Human parainfluenza viruses (hPIVs) are common viral causes of acute respiratory infections, resulting in substantial global disease burden. Seasonal patterns of hPIV epidemics can vary by geographical region and viral type, although these patterns are not well understood at a global level. We aimed to characterise regional and type-specific variations in hPIV seasonality and assess the potential role of climatic factors in explaining these variations. Methods In this systematic review and meta-analysis, we collected monthly aggregated seasonal activity data for hPIV and its four types (hPIV-1, hPIV-2, hPIV-3, and hPIV-4) from various sources, including a systematic search of Embase, MEDLINE, and Ovid Global Health, for literature published between Jan 1, 2000, and Dec 31, 2024; unpublished data contributed by an established collaborative network; and public viral surveillance datasets from online platforms. We included studies that continuously tested hPIVs throughout their study period and reported seasonal activity in defined geographical locations on a monthly basis (or if monthly data could be derived from reports). We excluded published studies if they had fewer than 20 cases, focused on specific medical conditions, or contained duplicate data from published literature or publicly available datasets. A prespecified collection template was used to collect data from members in the collaborative network. We extracted site-specific monthly case counts of combined...