The influenza pandemic preparedness planning tool InfluSim.
Identifieur interne : 000451 ( Main/Exploration ); précédent : 000450; suivant : 000452The influenza pandemic preparedness planning tool InfluSim.
Auteurs : Martin Eichner [Allemagne] ; Markus Schwehm ; Hans-Peter Duerr ; Stefan O. BrockmannSource :
- BMC infectious diseases [ 1471-2334 ] ; 2007.
Descripteurs français
- KwdFr :
- Absentéisme, Allemagne (épidémiologie), Contrôle des maladies contagieuses (), Flambées de maladies (), Grippe humaine (), Grippe humaine (épidémiologie), Hospitalisation (), Humains, Logiciel, Planification des mesures d'urgence en cas de catastrophe (), Planification en santé (), Prévision, Services de santé (), Simulation numérique.
- MESH :
- épidémiologie : Allemagne, Grippe humaine.
- Absentéisme, Contrôle des maladies contagieuses, Flambées de maladies, Grippe humaine, Hospitalisation, Humains, Logiciel, Planification des mesures d'urgence en cas de catastrophe, Planification en santé, Prévision, Services de santé, Simulation numérique.
English descriptors
- KwdEn :
- Absenteeism, Communicable Disease Control (methods), Computer Simulation, Disaster Planning (methods), Disease Outbreaks (prevention & control), Forecasting, Germany (epidemiology), Health Planning (methods), Health Planning (statistics & numerical data), Health Services (statistics & numerical data), Hospitalization (statistics & numerical data), Humans, Influenza, Human (epidemiology), Influenza, Human (prevention & control), Software.
- MESH :
- epidemiology : Germany, Influenza, Human.
- methods : Communicable Disease Control, Disaster Planning, Health Planning.
- prevention & control : Disease Outbreaks, Influenza, Human.
- statistics & numerical data : Health Planning, Health Services, Hospitalization.
- Absenteeism, Computer Simulation, Forecasting, Humans, Software.
Abstract
BACKGROUND
Planning 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.
RESULTS
InfluSim 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.
CONCLUSION
InfluSim 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.
DOI: 10.1186/1471-2334-7-17
PubMed: 17355639
Affiliations:
Links toward previous steps (curation, corpus...)
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Brockmann</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2007">2007</date><idno type="RBID">pubmed:17355639</idno><idno type="pmid">17355639</idno><idno type="doi">10.1186/1471-2334-7-17</idno><idno type="wicri:Area/Main/Corpus">000474</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000474</idno><idno type="wicri:Area/Main/Curation">000474</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000474</idno><idno type="wicri:Area/Main/Exploration">000474</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">The influenza pandemic preparedness planning tool InfluSim.</title><author><name sortKey="Eichner, Martin" sort="Eichner, Martin" uniqKey="Eichner M" first="Martin" last="Eichner">Martin Eichner</name><affiliation wicri:level="1"><nlm:affiliation>Department of Medical Biometry, University of Tübingen, Germany. martin.eichner@uni-tuebingen.de </nlm:affiliation> <country xml:lang="fr">Allemagne</country><wicri:regionArea>Department of Medical Biometry, University of Tübingen</wicri:regionArea><wicri:noRegion>University of Tübingen</wicri:noRegion><wicri:noRegion>University of Tübingen</wicri:noRegion><wicri:noRegion>University of Tübingen</wicri:noRegion></affiliation></author><author><name sortKey="Schwehm, Markus" sort="Schwehm, Markus" uniqKey="Schwehm M" first="Markus" last="Schwehm">Markus Schwehm</name></author><author><name sortKey="Duerr, Hans Peter" sort="Duerr, Hans Peter" uniqKey="Duerr H" first="Hans-Peter" last="Duerr">Hans-Peter Duerr</name></author><author><name sortKey="Brockmann, Stefan O" sort="Brockmann, Stefan O" uniqKey="Brockmann S" first="Stefan O" last="Brockmann">Stefan O. Brockmann</name></author></analytic><series><title level="j">BMC infectious diseases</title><idno type="eISSN">1471-2334</idno><imprint><date when="2007" type="published">2007</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Absenteeism</term><term>Communicable Disease Control (methods)</term><term>Computer Simulation</term><term>Disaster Planning (methods)</term><term>Disease Outbreaks (prevention & control)</term><term>Forecasting</term><term>Germany (epidemiology)</term><term>Health Planning (methods)</term><term>Health Planning (statistics & numerical data)</term><term>Health Services (statistics & numerical data)</term><term>Hospitalization (statistics & numerical data)</term><term>Humans</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (prevention & control)</term><term>Software</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Absentéisme</term><term>Allemagne (épidémiologie)</term><term>Contrôle des maladies contagieuses ()</term><term>Flambées de maladies ()</term><term>Grippe humaine ()</term><term>Grippe humaine (épidémiologie)</term><term>Hospitalisation ()</term><term>Humains</term><term>Logiciel</term><term>Planification des mesures d'urgence en cas de catastrophe ()</term><term>Planification en santé ()</term><term>Prévision</term><term>Services de santé ()</term><term>Simulation numérique</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Germany</term><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Communicable Disease Control</term><term>Disaster Planning</term><term>Health Planning</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Disease Outbreaks</term><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Health Planning</term><term>Health Services</term><term>Hospitalization</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Allemagne</term><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Absenteeism</term><term>Computer Simulation</term><term>Forecasting</term><term>Humans</term><term>Software</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Absentéisme</term><term>Contrôle des maladies contagieuses</term><term>Flambées de maladies</term><term>Grippe humaine</term><term>Hospitalisation</term><term>Humains</term><term>Logiciel</term><term>Planification des mesures d'urgence en cas de catastrophe</term><term>Planification en santé</term><term>Prévision</term><term>Services de santé</term><term>Simulation numérique</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>Planning 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.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>InfluSim 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.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>InfluSim 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.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">17355639</PMID><DateCompleted><Year>2007</Year><Month>04</Month><Day>10</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>01</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2334</ISSN><JournalIssue CitedMedium="Internet"><Volume>7</Volume><PubDate><Year>2007</Year><Month>Mar</Month><Day>13</Day></PubDate></JournalIssue><Title>BMC infectious diseases</Title><ISOAbbreviation>BMC Infect. Dis.</ISOAbbreviation></Journal><ArticleTitle>The influenza pandemic preparedness planning tool InfluSim.</ArticleTitle><Pagination><MedlinePgn>17</MedlinePgn></Pagination><Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Planning 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.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">InfluSim 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.</AbstractText><AbstractText Label="CONCLUSION" NlmCategory="CONCLUSIONS">InfluSim is an online available software http://www.influsim.info which efficiently assists public health planners in designing optimal interventions against pandemic influenza. 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Brockmann</name><name sortKey="Duerr, Hans Peter" sort="Duerr, Hans Peter" uniqKey="Duerr H" first="Hans-Peter" last="Duerr">Hans-Peter Duerr</name><name sortKey="Schwehm, Markus" sort="Schwehm, Markus" uniqKey="Schwehm M" first="Markus" last="Schwehm">Markus Schwehm</name></noCountry><country name="Allemagne"><noRegion><name sortKey="Eichner, Martin" sort="Eichner, Martin" uniqKey="Eichner M" first="Martin" last="Eichner">Martin Eichner</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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