Epidemiological Characteristics of Respiratory Syncytial Virus Infection Among Hospitalized Children With Acute Respiratory Tract Infections From 2014 to 2022 in a Hospital in Hubei Province, China: Longitudinal Surveillance Study
Bibliographic record
Abstract
BACKGROUND: Longitudinal studies characterizing the epidemic trend of respiratory syncytial virus (RSV) in Hubei Province are scarce. OBJECTIVE: We aimed to depict the dynamics of the RSV epidemic among hospitalized children with acute respiratory tract infections (ARTIs) during 2014 to 2022 in the Maternal and Child Health Hospital of Hubei Province and investigate the influence of the 2-child policy and the COVID-19 pandemic on RSV prevalence. METHODS: The medical records and testing results of hospitalized children with ARTI from January 2014 to June 2022 were extracted. Nasopharyngeal samples were tested with direct immunofluorescence assay. Detection rates of RSV were categorized according to the diagnosis of patients: (1) overall, (2) upper respiratory tract infection (URTI), and (3) lower respiratory tract infection (LRTI). Poisson regression models were used to investigate the association between RSV detection rate and age, gender, or diagnosis. The detection rates of RSV before and after the implementation of the universal 2-child policy were compared using a Poisson regression model. Multiple comparisons of RSV detection rates were conducted among 3 stages of the COVID-19 pandemic using chi-square tests. Seasonal autoregressive integrated moving average was performed to predict RSV behaviors from February 2020 to June 2020 under the assumption of a non-COVID-19 scenario. RESULTS: Among 75,128 hospitalized children with ARTI, 11.1% (8336/75,128) were RSV-positive. Children aged <1 year had higher detection rates than older children (4204/26,498, 15.9% vs 74/5504, 1.3%; P<.001), and children with LRTI had higher detection rates than children with URTI (7733/53,145, 14.6% vs 603/21,983, 2.7%; P<.001). Among all the children, a clear seasonal pattern of the RSV epidemic was observed before 2021. Most of the highest detection rates were concentrated between December and February. The yearly detection rate of RSV remained at a relatively low level (about 8%) from 2014 to 2017, then increased to 12% and above from 2018. The highest monthly detection rate was in December 2018 (539/1493, 36.1%), and the highest yearly rate was in 2021 (1372/9328, 14.7%). There was a moderate increase in the RSV detection rate after the 2-child policy was implemented (before: 860/10,446, 8.2% vs after: 4920/43,916, 11.2%; P<.001). The largest increase, by 5.83%, occurred in children aged <1 year. The RSV epidemic level decreased sharply in the short term after the COVID-19 outbreak (detection rate before: 1600/17,010, 9.4% vs after: 32/1135, 2.8%; P<.001). The largest decrease, by 12.0%, occurred in children aged <1 year, but a rebounding epidemic occurred after 2020 (680/5744, 11.8%; P<.001). CONCLUSIONS: Children have been experiencing increased prevalence of RSV since 2018 based on surveillance from a hospital in Hubei Province with a large sample size. The 2-child policy might have increased the RSV prevalence, and the COVID-19 epidemic had a temporary inhibitory effect on RSV transmission. Vaccines against RSV are urgently needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".