Evidence map›Paper›PMID 38617598›Full record

ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2024

Incorporating testing volume into estimation of effective reproduction number dynamics.

Isaac H Goldstein, Jon Wakefield, Volodymyr M Minin

Abstract read
In one paragraph

Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Isaac H GoldsteinDepartment of Statistics, University of California, Irvine, CA, USA.
Jon WakefieldDepartments of Biostatistics and Statistics, University of Washington, Seattle, WA, USA.
Volodymyr M MininDepartment of Statistics, University of California, Irvine, CA, USA.ORCID https://orcid.org/0000-0002-1917-9288

Funding

STATISTICAL ISSUES IN AIDS RESEARCHR01AI029168 · NIAID · UNIVERSITY OF WASHINGTON · PI HUGHES, JAMES P · 1989 to 2018
$5.3M
Improved understanding of TB transmission by accounting for within-host heterogeneity of M. tuberculosis: A population-based molecular epidemiology study in a high HIV prevalent settingR01AI147336 · NIAID · UNIVERSITY OF CALIFORNIA-IRVINE · PI SHIN, SANGHYUK SAM · 2020 to 2024
$3.3M
NIAID NIH HHS R01 AI029168NIAID NIH HHS R01 AI147336
6 · The paper itself

Abstract

Branching process inspired models are widely used to estimate the effective reproduction number-a useful summary statistic describing an infectious disease outbreak-using counts of new cases. Case data is a real-time indicator of changes in the reproduction number, but is challenging to work with because cases fluctuate due to factors unrelated to the number of new infections. We develop a new model that incorporates the number of diagnostic tests as a surveillance model covariate. Using simulated data and data from the SARS-CoV-2 pandemic in California, we demonstrate that incorporating tests leads to improved performance over the state of the art.

Indexed as

Bayesian inferenceCOVID-19infectious diseasesnowcasting

Identifiers

PMID38617598
PMCPMC11009926

What OpenQuestion holds

Textmetadata
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.