Evidence map›Paper›PMID 35937647›Full record

ArticleOpen forum infectious diseases2022

Aggregating Human Judgment Probabilistic Predictions of Coronavirus Disease 2019 Transmission, Burden, and Preventive Measures.

Allison Codi, Damon Luk, David Braun, Juan Cambeiro, Tamay Besiroglu, Eva Chen, Luis Enrique Urtubey de Cesaris, Paolo Bocchini, Thomas McAndrew

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Open forum infectious diseases, 2022. 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

5 · Who and what money

Authors and funding

9 authors.

Allison CodiCollege of Health, Lehigh University, Bethlehem, Pennsylvania, USA.ORCID https://orcid.org/0000-0001-6562-607X
Damon LukCollege of Health, Lehigh University, Bethlehem, Pennsylvania, USA.
David BraunDepartment of Psychology, College of Arts and Sciences, Lehigh University, Bethlehem, Pennsylvania, USA.
Juan CambeiroDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA.
Tamay BesirogluDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA.
Eva ChenGood Judgment Inc, New York, New York, USA.
Luis Enrique Urtubey de CesarisGood Judgment Inc, New York, New York, USA.
Paolo BocchiniDepartment of Civil and Environmental Engineering, P.C. Rossin College of Engineering and Applied Science, Lehigh University, Bethlehem, Pennsylvania, USA.
Thomas McAndrewCollege of Health, Lehigh University, Bethlehem, Pennsylvania, USA.

Funding

MIDAS Coordination CenterU24GM132013 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HOCHHEISER, HARRY S · 2019 to 2023
$8.1M
NIGMS NIH HHS U24 GM132013
6 · The paper itself

Abstract

Aggregated human judgment forecasts for coronavirus disease 2019 (COVID-19) targets of public health importance are accurate, often outperforming computational models. Our work shows that aggregated human judgment forecasts for infectious agents are timely, accurate, and adaptable, and can be used as a tool to aid public health decision making during outbreaks.

Indexed as

coronavirus disease 2019forecastinghuman judgment

Identifiers

PMID35937647
PMCPMC9348614

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.