Implications of respiratory syncytial virus seasonality for the timing of passive immunisation scenarios in Latin America and the caribbean – a cross-sectional modelling study
Bibliographic record
Abstract
BACKGROUND: The variation in respiratory syncytial virus (RSV) seasonality presents challenges for the timing of RSV prophylaxis. Prevention policies must consider seasonal dynamics to protect infants from severe RSV infections. We evaluated the timing and impact of passive immunisation on birth cohorts in Latin America and the Caribbean, accounting for RSV seasonality, duration of protection and uptake. METHODS: We characterised the 2010-2019 RSV seasonality by climate region using a moving averages-based method and surveillance data and identified newborns eligible for passive RSV immunisation under varied assumptions of protection duration and strategies. Lastly, we explored different intervention time windows and estimated RSV-associated acute lower respiratory infections (ALRI) averted among newborns. FINDINGS: In 2010-2019, 28 countries reported 317,951 RSV-positive respiratory samples (12.6 % RSV positivity). RSV epidemics followed a south-to-north progression, with onset ranging from March to November in subtropical climates, and year-round epidemics in the tropics. Seasonal immunisation benefited newborns born during January-September in temperate countries, while those born year-round in the tropics benefited from immunisation during at least one epidemic. Year-round vaccination covered newborns for at least one season; long-acting monoclonal antibodies (mAb) administered at five months to infants of immunised mothers extended protection through the remaining season. Year-round campaigns suited tropical climates. At 80 % coverage, 61.3 % (95 % CI 60.7-67) and 55 % (95 % CI 55.0-56.0) RSV-ALRI cases among 0- < 12 months were averted through mAb in exemplar temperate and tropical countries, respectively. In subtropical countries, combined RSV maternal vaccination and long-acting mAb averted 57.3 % (95 %CI:56.8-57.8) of RSV-ALRI. Efficiency per 100,000 doses administered varied minimally across strategies. CONCLUSIONS: RSV climatic variations underscored the importance of surveillance in tailoring the timing and extent of annual campaigns. RSV seasonality informs the selection of interventions. Public health initiatives can enhance prevention for newborns by defining optimal windows for immunising at-risk-infants.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".