Evidence map›Paper›PMID 38603425›Full record

ArticleThe international journal of high performance computing applications2023

Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support.

Parantapa Bhattacharya, Jiangzhuo Chen, Stefan Hoops, Dustin Machi, Bryan Lewis, Srinivasan Venkatramanan, Mandy L Wilson, Brian Klahn, Aniruddha Adiga, Benjamin Hurt and 13 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The international journal of high performance computing applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Mathematical modelling for pandemic preparedness in Canada: Learning from COVID-19.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2024
    Article
  6. Article
  7. COVID-19 data and modeling: We need to learn from and act on our experiences.Canadian journal of public health = Revue canadienne de sante publique · 2024
    Article
  8. Article
  9. Fighting COVID-19 with HPC.Nature computational science · 2021
    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

23 authors.

Parantapa BhattacharyaBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.ORCID https://orcid.org/0000-0002-3626-9939
Jiangzhuo ChenBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Stefan HoopsBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Dustin MachiBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Bryan LewisBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Srinivasan VenkatramananBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.ORCID https://orcid.org/0000-0002-0874-8692
Mandy L WilsonBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Brian KlahnBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Aniruddha AdigaBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Benjamin HurtBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.ORCID https://orcid.org/0000-0002-3803-2900
Joseph OuttenBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Abhijin AdigaBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Andrew WarrenBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.ORCID https://orcid.org/0000-0003-2660-0103
Young Yun BaekBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Przemyslaw PorebskiBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.ORCID https://orcid.org/0000-0001-8012-5791
Achla MaratheBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Dawen XieBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Samarth SwarupBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Anil VullikantiBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Henning MortveitBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Stephen EubankBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Christopher L BarrettBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.
Madhav MaratheBiocomplexity Institute and Initiative, University of Virginia, Charlottesville, VA, USA.ORCID https://orcid.org/0000-0003-1653-0658

Funding

Systems Analysis of Social Pathways of Epidemics to Reduce Health DisparitiesR01GM109718 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI MARATHE, ACHLA, VULLIKANTI, ANIL · 2014 to 2022
$3.6M
NIGMS NIH HHS R01 GM109718
6 · The paper itself

Abstract

This paper describes an integrated, data-driven operational pipeline based on national agent-based models to support federal and state-level pandemic planning and response. The pipeline consists of (

Indexed as

Agent-Based ModelsAICOVID-19Data ScienceEpidemic SimulationHigh Performance ComputingNetwork SciencePandemicsPolicyVaccination

Identifiers

PMID38603425
PMCPMC9596688

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.