Impact of Subgroup Distribution on Seasonality of Human Respiratory Syncytial Virus: A Global Systematic Analysis
Shuyu Deng, Ling Guo, Cheryl Cohen, Adam Meijer, Jocelyn Moyes, Siripat Pasittungkul, Yong Poovorawan, Anne Teirlinck, Michiel van Boven, Nasamon Wanlapakorn, Nicole Wolter, John Paget, Harish Nair, You Li, Respiratory Virus Global Epidemiology Network and the PROMISE Investigators, Shuyu Deng, Ling Guo, You Li, Cheryl Cohen, Jocelyn Moyes, Nicole Wolter, Anne von Gottberg, Adam Meijer, Anne Teirlinck, Michiel van Boven, Siripat Pasittungkul, Yong Poovorawan, Nasamon Wanlapakorn, John Paget, Harish Nair, Jeroen Aerssens, Gabriela Ispas, Bahar Ahani, Jessica E. Atwell, Elizabeth Begier, Tin Tin Htar, Mathieu Bangert, Rolf Kramer, Charlotte Vernhes, Philippe Beutels, Louis Bont, Harry Campbell, Harish Nair, You Li, Richard Osei‐Yeboah, Xin Wang, Rachel Cohen, Gaël Dos Santos, Theo Last, Veena Kumar, Núria Machín, Hanna Nohynek, Peter Openshaw, John Paget, Andrew J. Pollard, Anne Teirlinck
Abstract
BACKGROUND: Previous studies reported inconsistent findings regarding the association between respiratory syncytial virus (RSV) subgroup distribution and timing of RSV season. We aimed to further understand the association by conducting a global-level systematic analysis. METHODS: We compiled published data on RSV seasonality through a systematic literature review, and unpublished data shared by international collaborators. Using annual cumulative proportion (ACP) of RSV-positive cases, we defined RSV season onset and offset as ACP reaching 10% and 90%, respectively. Linear regression models accounting for meteorological factors were constructed to analyze the association of proportion of RSV-A with the corresponding RSV season onset and offset. RESULTS: We included 36 study sites from 20 countries, providing data for 179 study-years in 1995-2019. Globally, RSV subgroup distribution was not significantly associated with RSV season onset or offset globally, except for RSV season offset in the tropics in 1 model, possibly by chance. Models that included RSV subgroup distribution and meteorological factors explained only 2%-4% of the variations in timing of RSV season. CONCLUSIONS: Year-on-year variations in RSV season onset and offset are not well explained by RSV subgroup distribution or meteorological factors. Factors including population susceptibility, mobility, and viral interference should be examined in future studies.