Evidence map›Paper›PMID 31558611›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Reply to Bracher: Scoring probabilistic forecasts to maximize public health interpretability.

Nicholas G Reich, Dave Osthus, Evan L Ray, Teresa K Yamana, Matthew Biggerstaff, Michael A Johansson, Roni Rosenfeld, Jeffrey Shaman

Abstract readLetterComment
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Multiscale influenza forecasting.Nature communications · 2021
    Article
  5. Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Nicholas G ReichDepartment of Biostatistics and Epidemiology, University of Massachusetts-Amherst, Amherst, MA 01003; nick@schoolph.umass.edu.ORCID 0000-0003-3503-9899
Dave OsthusStatistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM 87545.
Evan L RayDepartment of Mathematics and Statistics, Mount Holyoke College, South Hadley, MA 01075.ORCID 0000-0003-4035-0243
Teresa K YamanaDepartment of Environmental Health Sciences, Columbia University, New York, NY 10032.
Matthew BiggerstaffInfluenza Division, Centers for Disease Control and Prevention, Atlanta, GA 30333.
Michael A JohanssonDivision of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, PR 00920.ORCID 0000-0002-5090-7722
Roni RosenfeldMachine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213.
Jeffrey ShamanDepartment of Environmental Health Sciences, Columbia University, New York, NY 10032.

Funding

Statistical methods for real-time forecasts of infectious disease: expanding dynamic time-series and machine learning approaches for pandemic scenariosR35GM119582 · NIGMS · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Nicholas G Reich · 2016 to 2026
$4.8M
Development and Dissemination of Operational Real-Time Respiratory Virus ForecastU01GM110748 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2014 to 2018
$2.6M
Influenza Outbreak Prediction: Applying Data Assimilation Methodology to Make...R01GM100467 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHAMAN, JEFFREY L · 2011 to 2015
$1.4M
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NIGMS NIH HHS R01 GM100467NIGMS NIH HHS R35 GM119582NIGMS NIH HHS U01 GM110748
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Influenza, HumanForecastingHumansProbabilityPublic HealthSeasonsUnited States

Identifiers

PMID31558611
PMCPMC6800325

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.