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 Wanlapokorn; Nicole Wolter; John Paget; Harish Nair; You Li

doi:10.1093/infdis/jiad192

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 Wanlapokorn, Nicole Wolter, John Paget, Harish Nair^*, You Li^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Introduction: Previous studies reported inconsistent findings regarding the association between
respiratory syncytial virus (RSV) subgroup distribution and timing of RSV seasonal epidemics, possibly due to not accounting for confounders such as meteorological factors. We aimed to improve the understanding of the association through a global-level systematic analysis that 35 accounted for these potential confounders.

Methods: We compiled published data on RSV seasonality through a systematic literature review, and supplemented with unpublished data shared by international collaborators. RSV seasonal characteristics were defined for each study-year based on the annual cumulative proportion (ACP) of RSV-positive cases, with ACP of 10% and 90% being defined as season onset and offset, respectively. Linear regression models with study-level clustered standard errors were conducted to analyse the association of proportion of RSV-A with the corresponding RSV season onset and offset separately, while accounting for meteorological factors.

Results: We included a total of 36 studies from 36 sites in 20 countries, which cumulatively provided data for 179 study-years in 1995–2019. Overall, year-on-year variations in RSV season onset, offset, and duration were generally comparable among tropical, sub-tropical, and temperate regions. Regression analysis by latitude groups showed that RSV subgroup distribution was not significantly associated with RSV season onset or offset globally; the only exception was for RSV season offset in the tropics in one model, possibly by chance. Models that included both RSV subgroup distribution and meteorological factors only jointly explained 2–4% of the variations in RSV season onset and offset.

Conclusion: Globally, RSV subgroup distribution had negligible impact on the RSV seasonal characteristics. RSV subgroup distribution and meteorological factors jointly could only explain limited year-on-year variations in RSV season onset and offset. The role of population susceptibility, mobility, and viral interference should be examined in future studies.

Original language	English
Number of pages	18
Journal	The Journal of Infectious Diseases
Early online date	30 May 2023
DOIs	https://doi.org/10.1093/infdis/jiad192
Publication status	E-pub ahead of print - 30 May 2023

Keywords / Materials (for Non-textual outputs)

respiratory syncytial virus
seasonality
subgroup
meteorological factors

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10.1093/infdis/jiad192Licence: All Rights Reserved

Impact of subgroup distribution on seasonality of human respiratory syncytial virus A global systematic analysisAccepted author manuscript, 726 KBLicence: Creative Commons: Attribution (CC-BY)

PRomISE: Preparing for RSV Immunization and Surveillance in Europe
Nair, H. (Principal Investigator), Campbell, H. (Co-investigator) & Cunningham, S. (Co-investigator)
EU government bodies
1/11/21 → 30/04/24
Project: Research

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Deng, S., Guo, L., Cohen, C., Meijer, A., Moyes, J., Pasittungkul, S., Poovorawan, Y., Teirlinck, A., van Boven, M., Wanlapokorn, N., Wolter, N., Paget, J., Nair, H., & Li, Y. (2023). Impact of subgroup distribution on seasonality of human respiratory syncytial virus: A global systematic analysis. The Journal of Infectious Diseases. Advance online publication. https://doi.org/10.1093/infdis/jiad192

@article{0b982f59e8e14f07bcdceaa1210cf0af,

title = "Impact of subgroup distribution on seasonality of human respiratory syncytial virus: A global systematic analysis",

abstract = "Introduction: Previous studies reported inconsistent findings regarding the association between respiratory syncytial virus (RSV) subgroup distribution and timing of RSV seasonal epidemics, possibly due to not accounting for confounders such as meteorological factors. We aimed to improve the understanding of the association through a global-level systematic analysis that 35 accounted for these potential confounders. Methods: We compiled published data on RSV seasonality through a systematic literature review, and supplemented with unpublished data shared by international collaborators. RSV seasonal characteristics were defined for each study-year based on the annual cumulative proportion (ACP) of RSV-positive cases, with ACP of 10\% and 90\% being defined as season onset and offset, respectively. Linear regression models with study-level clustered standard errors were conducted to analyse the association of proportion of RSV-A with the corresponding RSV season onset and offset separately, while accounting for meteorological factors. Results: We included a total of 36 studies from 36 sites in 20 countries, which cumulatively provided data for 179 study-years in 1995–2019. Overall, year-on-year variations in RSV season onset, offset, and duration were generally comparable among tropical, sub-tropical, and temperate regions. Regression analysis by latitude groups showed that RSV subgroup distribution was not significantly associated with RSV season onset or offset globally; the only exception was for RSV season offset in the tropics in one model, possibly by chance. Models that included both RSV subgroup distribution and meteorological factors only jointly explained 2–4\% of the variations in RSV season onset and offset. Conclusion: Globally, RSV subgroup distribution had negligible impact on the RSV seasonal characteristics. RSV subgroup distribution and meteorological factors jointly could only explain limited year-on-year variations in RSV season onset and offset. The role of population susceptibility, mobility, and viral interference should be examined in future studies.",

keywords = "respiratory syncytial virus, seasonality, subgroup, meteorological factors",

author = "Shuyu Deng and Ling Guo and Cheryl Cohen and Adam Meijer and Jocelyn Moyes and Siripat Pasittungkul and Yong Poovorawan and Anne Teirlinck and \{van Boven\}, Michiel and Nasamon Wanlapokorn and Nicole Wolter and John Paget and Harish Nair and You Li",

year = "2023",

month = may,

day = "30",

doi = "10.1093/infdis/jiad192",

language = "English",

journal = "The Journal of Infectious Diseases",

issn = "0022-1899",

publisher = "Oxford University Press",

}

TY - JOUR

T1 - Impact of subgroup distribution on seasonality of human respiratory syncytial virus

T2 - A global systematic analysis

AU - Deng, Shuyu

AU - Guo, Ling

AU - Cohen, Cheryl

AU - Meijer, Adam

AU - Moyes, Jocelyn

AU - Pasittungkul, Siripat

AU - Poovorawan, Yong

AU - Teirlinck, Anne

AU - van Boven, Michiel

AU - Wanlapokorn, Nasamon

AU - Wolter, Nicole

AU - Paget, John

AU - Nair, Harish

AU - Li, You

PY - 2023/5/30

Y1 - 2023/5/30

N2 - Introduction: Previous studies reported inconsistent findings regarding the association between respiratory syncytial virus (RSV) subgroup distribution and timing of RSV seasonal epidemics, possibly due to not accounting for confounders such as meteorological factors. We aimed to improve the understanding of the association through a global-level systematic analysis that 35 accounted for these potential confounders. Methods: We compiled published data on RSV seasonality through a systematic literature review, and supplemented with unpublished data shared by international collaborators. RSV seasonal characteristics were defined for each study-year based on the annual cumulative proportion (ACP) of RSV-positive cases, with ACP of 10% and 90% being defined as season onset and offset, respectively. Linear regression models with study-level clustered standard errors were conducted to analyse the association of proportion of RSV-A with the corresponding RSV season onset and offset separately, while accounting for meteorological factors. Results: We included a total of 36 studies from 36 sites in 20 countries, which cumulatively provided data for 179 study-years in 1995–2019. Overall, year-on-year variations in RSV season onset, offset, and duration were generally comparable among tropical, sub-tropical, and temperate regions. Regression analysis by latitude groups showed that RSV subgroup distribution was not significantly associated with RSV season onset or offset globally; the only exception was for RSV season offset in the tropics in one model, possibly by chance. Models that included both RSV subgroup distribution and meteorological factors only jointly explained 2–4% of the variations in RSV season onset and offset. Conclusion: Globally, RSV subgroup distribution had negligible impact on the RSV seasonal characteristics. RSV subgroup distribution and meteorological factors jointly could only explain limited year-on-year variations in RSV season onset and offset. The role of population susceptibility, mobility, and viral interference should be examined in future studies.

AB - Introduction: Previous studies reported inconsistent findings regarding the association between respiratory syncytial virus (RSV) subgroup distribution and timing of RSV seasonal epidemics, possibly due to not accounting for confounders such as meteorological factors. We aimed to improve the understanding of the association through a global-level systematic analysis that 35 accounted for these potential confounders. Methods: We compiled published data on RSV seasonality through a systematic literature review, and supplemented with unpublished data shared by international collaborators. RSV seasonal characteristics were defined for each study-year based on the annual cumulative proportion (ACP) of RSV-positive cases, with ACP of 10% and 90% being defined as season onset and offset, respectively. Linear regression models with study-level clustered standard errors were conducted to analyse the association of proportion of RSV-A with the corresponding RSV season onset and offset separately, while accounting for meteorological factors. Results: We included a total of 36 studies from 36 sites in 20 countries, which cumulatively provided data for 179 study-years in 1995–2019. Overall, year-on-year variations in RSV season onset, offset, and duration were generally comparable among tropical, sub-tropical, and temperate regions. Regression analysis by latitude groups showed that RSV subgroup distribution was not significantly associated with RSV season onset or offset globally; the only exception was for RSV season offset in the tropics in one model, possibly by chance. Models that included both RSV subgroup distribution and meteorological factors only jointly explained 2–4% of the variations in RSV season onset and offset. Conclusion: Globally, RSV subgroup distribution had negligible impact on the RSV seasonal characteristics. RSV subgroup distribution and meteorological factors jointly could only explain limited year-on-year variations in RSV season onset and offset. The role of population susceptibility, mobility, and viral interference should be examined in future studies.

KW - respiratory syncytial virus

KW - seasonality

KW - subgroup

KW - meteorological factors

U2 - 10.1093/infdis/jiad192

DO - 10.1093/infdis/jiad192

M3 - Article

SN - 0022-1899

JO - The Journal of Infectious Diseases

JF - The Journal of Infectious Diseases

ER -

Impact of subgroup distribution on seasonality of human respiratory syncytial virus: A global systematic analysis

Abstract

Keywords / Materials (for Non-textual outputs)

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Projects

PRomISE: Preparing for RSV Immunization and Surveillance in Europe

Cite this