Bibliographic record
Abstract
Respiratory syncytial virus (RSV) is a leading cause of severe respiratory infections in infants. At the start of this thesis, no immunization strategy was available to protect all infants against RSV. Since 2023, two new immunisation strategies have been approved by the European Medicines Agency (EMA) to protect all infants against RSV disease: one maternal vaccine and one monoclonal antibody. The objective of this thesis was to support the introduction of infant RSV immunization in the Netherlands in the aftermath of the SARS-CoV-2 pandemic. First, we aimed to estimate the of RSV in healthy term-born infants and the potential impact of RSV immunization on the healthcare burden of RSV. To estimate incidencem we followed over 9,000 infants until their first birthday. We found that 1 in 56 infants had to be hospitalized and 1 in 7 infants had to consult a doctor because of RSV infections during their first year of life. Then we developed scenarios to estimate the potential impact of different immunization strategies in the Netherlands. The analyses compared current recommendations for palivizumab with a year-long maternal vaccine program and a seasonal monoclonal antibody (mAb) program. A seasonal mAb immunization program would result in the largest reduction in RSV-related hospitalizations and medical consultations. Second, we investigated the changes in RSV epidemiology during the SARS-CoV-2 pandemic. The SARS-CoV-2 pandemic severely disrupted RSV seasonality. In 2020, many countries implemented large-scale non-pharmaceutical interventions (NPIs), like stay-at-home orders. RSV activity dropped and little to no RSV activity was observed until spring or summer 2021. Resurgences were observed in 2021 often outside of the expected period for the RSV season. We showed that the timing of the resurgences was associated with the relaxation of NPIs, particularly with schools reopening. Since the first resurgences, RSV has been gradually returning to pre-pandemic patterns. The high healthcare burden associated with RSV showed in this thesis underscores the need for broad RSV immunization strategies to protect all infants. The SARS-CoV-2 pandemic showed that unexpected events can disrupt the epidemiology of RSV. Therefore, immunization programs must be able to absorb or adapt to future disruptions. To ensure their long-term success, RSV immunization programs should be built with resilience in mind.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.416 | 0.271 |
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".