Evidence map›Paper›PMID 39881360›Full record

SynthesisBMC medicine2025

Understanding the local-level variations in seasonality of human respiratory syncytial virus infection: a systematic analysis.

Sheng Ye, Shuyu Deng, Yumeng Miao, David Torres-Fernandez, Quique Bassat, Xin Wang, You Li

Abstract readSystematic Review
In one paragraph

Synthesis in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
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  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sheng Ye *Department of Epidemiology, National Vaccine Innovation Platform, School of Public Health, Nanjing Medical University, Nanjing, China.
Shuyu Deng *Department of Epidemiology, National Vaccine Innovation Platform, School of Public Health, Nanjing Medical University, Nanjing, China.
Yumeng MiaoDepartment of Epidemiology, National Vaccine Innovation Platform, School of Public Health, Nanjing Medical University, Nanjing, China.
David Torres-FernandezISGlobal, Barcelona, Spain.
Quique BassatISGlobal, Barcelona, Spain.
Xin WangDepartment of Biostatistics, National Vaccine Innovation Platform, School of Public Health, Nanjing Medical University, Nanjing, China. xin.wang@njmu.edu.cn.
You LiDepartment of Epidemiology, National Vaccine Innovation Platform, School of Public Health, Nanjing Medical University, Nanjing, China. you.li@njmu.edu.cn.

Funding

Generalitat de Catalunya (through the CERCA Program) CEX2018-000806-S"La Caixa" Foundation LCF/BQ/DR21/11880018the National Natural Science Foundation of China No. 82404372the National Natural Science Foundation of China No. 82473692
6 · The paper itself

Abstract

backgroundWhile previous reports characterised global and regional variations in RSV seasonality, less is known about local variations in RSV seasonal characteristics. This study aimed to understand the local-level variations in RSV seasonality and to explore the role of geographical, meteorological, and socio-demographic factors in explaining these variations.

methodsWe conducted a systematic literature review to identify published studies reporting data on local-level RSV season onset, offset, or duration for at least two local sites. In addition, we included three datasets of RSV activity from Japan, Spain, and Scotland with available site-specific data. RSV season onset, offset, and duration were defined using the annual cumulative proportion method. We estimated between-site variations within a region using the earliest onset, the earliest offset, and the shortest duration of RSV season of that region as the references and synthesised the variations across regions by a multi-level mixed-effects meta-analysis. Using the three datasets from Japan, Spain and Scotland, we applied linear regression models with clustered standard errors to explore the association of geographical, meteorological, and socio-demographic factors with the season onset and offset, respectively.

resultsWe included 7 published studies identified from the systematic literature search. With the additional 3 datasets, these data sources covered 888,447 RSV-positive cases from 101 local study sites during 1995 to 2020. Local-level variations in RSV season within a region were estimated to be 6 weeks (41 days, 95% CI: 25-57) for season onset, 5 weeks (32 days, 13-50) for season offset, and 6 weeks (40 days, 20-59) for season duration, with substantial differences across years. Multiple factors, such as temperature, relative humidity, wind speed, annual household income, population size, latitude, and longitude, could jointly explain 66% to 84% and 35% to 49% of the variations in season onset and offset, respectively, although their individual effects varied by individual regions.

conclusionsLocal-level variations in RSV season onset could be as much as 6 weeks, which could be influenced by meteorological, geographical, and socio-demographic factors. The reported variations in this study could have important implications for local-level healthcare resources planning and immunisation strategy.

trial registrationPROSPERO CRD42023482432.

Indexed as

Respiratory Syncytial Virus InfectionsSeasonsHumansJapanRespiratory Syncytial Virus, HumanScotlandSpainMeteorological factorsRespiratory syncytial virusSeasonalitySocio-demographic factors

Identifiers

PMID39881360
PMCPMC11781002

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.