Evidence map›Paper›PMID 41472268›Full record

ArticleViruses2025

Amna Tariq, Ping Yan, Amanda Bleichrodt, Gerardo Chowell

Abstract read
In one paragraph

Article in Viruses, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Amna TariqDepartment of Pediatrics Infectious Diseases, Stanford School of Medicine, Palo Alto, CA 94305, USA.
Ping YanDepartment of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada.ORCID 0000-0001-6765-0735
Amanda BleichrodtDepartment of Public Health Sciences, Clemson University, Clemson, SC 29634, USA.
Gerardo ChowellDepartment of Population Health Sciences, Georgia State University, Atlanta, GA 30303, USA.ORCID 0000-0003-2194-2251

Funding

U.S. National Science Foundation 2125246Wellcome Trust 202679
6 · The paper itself

Abstract

One difficulty that arises in tracking and forecasting real-time epidemics is reporting delays, which are defined as the inherent delay between the time of symptom onset and the time a case is reported. Reporting delays can be caused by delays in case detection, symptom onset after infection, seeking medical care, or diagnostics, and they distort the accurate forecasting of diseases during epidemics and pandemics. To address this, we introduce a practical nowcasting approach grounded in survival analysis and actuarial science, explicitly allowing for non-stationarity in reporting delay patterns to better capture real-world variability. Despite its relevance, no flexible and accessible toolbox currently exists for non-stationary delay adjustment. Here, we present

Indexed as

EpidemicsEpidemiological MonitoringSoftwareCOVID-19Disease NotificationForecastingHemorrhagic Fever, EbolaHumansSARS-CoV-2Time Factorsnon-stationary reporting delaysnowcastingreporting delaysshiny appsurvival analysistoolbox

Identifiers

PMID41472268
PMCPMC12737790

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.