Evidence map›Paper›PMID 22195089›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2011

A cloud-based simulation architecture for pandemic influenza simulation.

Henrik Eriksson, Massimiliano Raciti, Maurizio Basile, Alessandro Cunsolo, Anders Fröberg, Ola Leifler, Joakim Ekberg, Toomas Timpka

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Dynamic Multicore Processing for Pandemic Influenza Simulation.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016
    Article
  3. A scoping review of cloud computing in healthcare.BMC medical informatics and decision making · 2015
    Article
  4. 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

8 authors.

Henrik ErikssonDept. of Comp. and Inform. Sci., Linköping University, Sweden.
Massimiliano Raciti
Maurizio Basile
Alessandro Cunsolo
Anders Fröberg
Ola Leifler
Joakim Ekberg
Toomas Timpka

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-fidelity simulations of pandemic outbreaks are resource consuming. Cluster-based solutions have been suggested for executing such complex computations. We present a cloud-based simulation architecture that utilizes computing resources both locally available and dynamically rented online. The approach uses the Condor framework for job distribution and management of the Amazon Elastic Computing Cloud (EC2) as well as local resources. The architecture has a web-based user interface that allows users to monitor and control simulation execution. In a benchmark test, the best cost-adjusted performance was recorded for the EC2 H-CPU Medium instance, while a field trial showed that the job configuration had significant influence on the execution time and that the network capacity of the master node could become a bottleneck. We conclude that it is possible to develop a scalable simulation environment that uses cloud-based solutions, while providing an easy-to-use graphical user interface.

Indexed as

Computer SimulationInternetPandemicsHumansInfluenza, Human

Identifiers

PMID22195089
PMCPMC3243184

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.