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Impact of subgroup distribution on seasonality of human respiratory syncytial virus: a global systematic analysis.
Deng, S., Guo, L., Cohen, C., Meijer, A., Moyes, J., Pasittungskul, S., Poovorawan, Y., Teirlink, A., Boven, M. van, Wanlapakorn, N., Wolter, N., Paget, J., Nair, H., Li, Y. Impact of subgroup distribution on seasonality of human respiratory syncytial virus: a global systematic analysis. Journal of Infectious Diseases: 2024, 229(Suppl. 1), p. S25-S33.
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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 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We compiled published data on RSV seasonality through a systematic literature review, and supplemented with unpublished data shared by international collaborators.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.
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 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.
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 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.
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 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.