Evidence map›Paper›PMID 39606407›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Relating

Ke Li, Louis J Bont, Daniel M Weinberger, Virginia E Pitzer

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ke LiDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Louis J BontDivision of Infectious Diseases, Department of Pediatrics, University Medical Center Utrecht, Utrecht, the Netherlands.
Daniel M WeinbergerDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
Virginia E PitzerDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.

Funding

Predicting and monitoring variations in the effects of vaccines against RSVR01AI137093 · NIAID · YALE UNIVERSITY · PI Virginia E Pitzer, Daniel Martin Weinberger · 2018 to 2026
$3.4M
NIAID NIH HHS R01 AI137093
6 · The paper itself

Abstract

Respiratory syncytial virus (RSV) infections are a major public health concern for pediatric populations and older adults. Viral kinetics, the dynamic processes of viral infection within an individual over time, vary across different populations. However, RSV transmission in different age groups is incompletely understood from the perspective of individual-level viral kinetics. To explore how individual viral kinetics can be related to RSV transmission, we first fitted a mathematical model to longitudinal viral kinetic data from 53 individuals in pediatric, adult, and elderly age groups using a hierarchical Bayesian framework to estimate important viral kinetic parameters. Using a probabilistic model, we then related the within-host viral load to the probability of transmission for each age group. We found that children had higher peak viral loads and longer shedding periods compared to other age groups, suggesting a higher transmission probability in children over the infectious period. We validated our findings by comparing the estimated secondary attack rate across different age groups to empirical estimates from household transmission studies. Our work highlights the importance of age-specific considerations in understanding and managing RSV infections, suggesting that age-targeted interventions will be more effective in controlling RSV transmission.

Identifiers

PMID39606407
PMCPMC11601762

What OpenQuestion holds

Textmetadata
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.