Evidence map›Paper›PMID 17355639›Full record

ArticleBMC infectious diseases2007

The influenza pandemic preparedness planning tool InfluSim.

Martin Eichner, Markus Schwehm, Hans-Peter Duerr, Stefan O Brockmann

Abstract read
In one paragraph

Article in BMC infectious diseases, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Considerations for acute care staffing during a pandemic.Best practice & research. Clinical anaesthesiology · 2021
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  17. Influenza--insights from mathematical modelling.Deutsches Arzteblatt international · 2009
    Article
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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

4 authors.

Martin EichnerDepartment of Medical Biometry, University of Tübingen, Germany. martin.eichner@uni-tuebingen.de <martin.eichner@uni-tuebingen.de>
Markus Schwehm
Hans-Peter Duerr
Stefan O Brockmann

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPlanning public health responses against pandemic influenza relies on predictive models by which the impact of different intervention strategies can be evaluated. Research has to date rather focused on producing predictions for certain localities or under specific conditions, than on designing a publicly available planning tool which can be applied by public health administrations. Here, we provide such a tool which is reproducible by an explicitly formulated structure and designed to operate with an optimal combination of the competing requirements of precision, realism and generality.

resultsInfluSim is a deterministic compartment model based on a system of over 1,000 differential equations which extend the classic SEIR model by clinical and demographic parameters relevant for pandemic preparedness planning. It allows for producing time courses and cumulative numbers of influenza cases, outpatient visits, applied antiviral treatment doses, hospitalizations, deaths and work days lost due to sickness, all of which may be associated with economic aspects. The software is programmed in Java, operates platform independent and can be executed on regular desktop computers.

conclusionInfluSim is an online available software http://www.influsim.info which efficiently assists public health planners in designing optimal interventions against pandemic influenza. It can reproduce the infection dynamics of pandemic influenza like complex computer simulations while offering at the same time reproducibility, higher computational performance and better operability.

Indexed as

Computer SimulationInfluenza, HumanSoftwareAbsenteeismCommunicable Disease ControlDisaster PlanningDisease OutbreaksForecastingGermanyHealth PlanningHealth ServicesHospitalizationHumans

Identifiers

PMID17355639
PMCPMC1832202

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.