Reducing disease burden in an influenza pandemic by targeted delivery of neuraminidase inhibitors: mathematical models in the Australian context
Identifieur interne : 001C00 ( Ncbi/Curation ); précédent : 001B99; suivant : 001C01Reducing disease burden in an influenza pandemic by targeted delivery of neuraminidase inhibitors: mathematical models in the Australian context
Auteurs : Robert Moss [Australie] ; James M. Mccaw [Australie] ; Allen C. Cheng [Australie] ; Aeron C. Hurt [Australie] ; Jodie Mcvernon [Australie]Source :
- BMC Infectious Diseases [ 1471-2334 ] ; 2016.
Descripteurs français
- KwdFr :
- Antienzymes (administration et posologie), Antienzymes (usage thérapeutique), Antiviraux (administration et posologie), Antiviraux (usage thérapeutique), Australie (épidémiologie), Coût de la maladie, Grippe humaine (), Grippe humaine (traitement médicamenteux), Grippe humaine (transmission), Grippe humaine (épidémiologie), Humains, Modèles théoriques, Pandémies (), Sialidase (antagonistes et inhibiteurs), Évaluation des risques.
- MESH :
- administration et posologie : Antienzymes, Antiviraux.
- antagonistes et inhibiteurs : Sialidase.
- traitement médicamenteux : Grippe humaine.
- usage thérapeutique : Antienzymes, Antiviraux, Grippe humaine.
- épidémiologie : Australie, Grippe humaine.
- Coût de la maladie, Grippe humaine, Humains, Modèles théoriques, Pandémies, Évaluation des risques.
English descriptors
- KwdEn :
- Antiviral Agents (administration & dosage), Antiviral Agents (therapeutic use), Australia (epidemiology), Cost of Illness, Enzyme Inhibitors (administration & dosage), Enzyme Inhibitors (therapeutic use), Humans, Influenza, Human (drug therapy), Influenza, Human (epidemiology), Influenza, Human (prevention & control), Influenza, Human (transmission), Models, Theoretical, Neuraminidase (antagonists & inhibitors), Pandemics (prevention & control), Risk Assessment.
- MESH :
- chemical , administration & dosage : Antiviral Agents, Enzyme Inhibitors.
- chemical , antagonists & inhibitors : Neuraminidase.
- chemical , therapeutic use : Antiviral Agents, Enzyme Inhibitors.
- drug therapy : Influenza, Human.
- epidemiology : Australia, Influenza, Human.
- prevention & control : Influenza, Human, Pandemics.
- transmission : Influenza, Human.
- Cost of Illness, Humans, Models, Theoretical, Risk Assessment.
Abstract
Many nations maintain stockpiles of neuraminidase inhibitor (NAI) antiviral agents for use in influenza pandemics to reduce transmission and mitigate the course of clinical infection. Pandemic preparedness plans include the use of these stockpiles to deliver proportionate responses, informed by emerging evidence of clinical impact. Recent uncertainty about the effectiveness of NAIs has prompted these nations to reconsider the role of NAIs in pandemic response, with implications for pandemic planning and for NAI stockpile size.
We combined a dynamic model of influenza epidemiology with a model of the clinical care pathways in the Australian health care system to identify effective NAI strategies for reducing morbidity and mortality in pandemic events, and the stockpile requirements for these strategies. The models were informed by a 2015 assessment of NAI effectiveness against susceptibility, pathogenicity, and transmission of influenza.
Liberal distribution of NAIs for early treatment in outpatient settings yielded the greatest benefits in all of the considered scenarios. Restriction of community-based treatment to risk groups was effective in those groups, but failed to prevent the large proportion of cases arising from lower risk individuals who comprise the majority of the population.
These targeted strategies are only effective if they can be deployed within the constraints of existing health care infrastructure. This finding highlights the critical importance of identifying optimal models of care delivery for effective emergency health care response.
The online version of this article (doi:10.1186/s12879-016-1866-7) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s12879-016-1866-7
PubMed: 27724915
PubMed Central: 5057455
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PMC:5057455Le document en format XML
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Mccaw</name><affiliation wicri:level="4"><nlm:aff id="Aff1">Modelling and Simulation Unit Centre for Epidemiology and Biostatistics Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie St, Melbourne, 3010 Victoria Australia</nlm:aff><orgName type="university">Université de Melbourne</orgName><country>Australie</country><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation><affiliation wicri:level="4"><nlm:aff id="Aff2">School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia</nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>School of Mathematics and Statistics, The University of Melbourne, Melbourne</wicri:regionArea><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName><orgName type="university">Université de Melbourne</orgName></affiliation><affiliation wicri:level="3"><nlm:aff id="Aff3">Murdoch Childrens Research Institute, Melbourne, Australia</nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Murdoch Childrens Research Institute, Melbourne</wicri:regionArea><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author><author><name sortKey="Cheng, Allen C" sort="Cheng, Allen C" uniqKey="Cheng A" first="Allen C." last="Cheng">Allen C. Cheng</name><affiliation wicri:level="3"><nlm:aff id="Aff4">Infectious Disease Epidemiology Unit, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia</nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Infectious Disease Epidemiology Unit, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne</wicri:regionArea><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation><affiliation wicri:level="3"><nlm:aff id="Aff5">Infection Prevention and Healthcare Epidemiology Unit, Alfred Health, Melbourne, Australia</nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Infection Prevention and Healthcare Epidemiology Unit, Alfred Health, Melbourne</wicri:regionArea><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author><author><name sortKey="Hurt, Aeron C" sort="Hurt, Aeron C" uniqKey="Hurt A" first="Aeron C." last="Hurt">Aeron C. Hurt</name><affiliation wicri:level="3"><nlm:aff id="Aff6">WHO Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute, Melbourne, Australia</nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>WHO Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute, Melbourne</wicri:regionArea><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author><author><name sortKey="Mcvernon, Jodie" sort="Mcvernon, Jodie" uniqKey="Mcvernon J" first="Jodie" last="Mcvernon">Jodie Mcvernon</name><affiliation wicri:level="4"><nlm:aff id="Aff1">Modelling and Simulation Unit Centre for Epidemiology and Biostatistics Melbourne School of Population and Global Health, The University of Melbourne, Level 3, 207 Bouverie St, Melbourne, 3010 Victoria Australia</nlm:aff><orgName type="university">Université de Melbourne</orgName><country>Australie</country><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation><affiliation wicri:level="3"><nlm:aff id="Aff3">Murdoch Childrens Research Institute, Melbourne, Australia</nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>Murdoch Childrens Research Institute, Melbourne</wicri:regionArea><placeName><settlement type="city">Melbourne</settlement><region type="état">Victoria (État)</region></placeName></affiliation></author></analytic><series><title level="j">BMC Infectious Diseases</title><idno type="eISSN">1471-2334</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Antiviral Agents (administration & dosage)</term><term>Antiviral Agents (therapeutic use)</term><term>Australia (epidemiology)</term><term>Cost of Illness</term><term>Enzyme Inhibitors (administration & dosage)</term><term>Enzyme Inhibitors (therapeutic use)</term><term>Humans</term><term>Influenza, Human (drug therapy)</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (prevention & control)</term><term>Influenza, Human (transmission)</term><term>Models, Theoretical</term><term>Neuraminidase (antagonists & inhibitors)</term><term>Pandemics (prevention & control)</term><term>Risk Assessment</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Antienzymes (administration et posologie)</term><term>Antienzymes (usage thérapeutique)</term><term>Antiviraux (administration et posologie)</term><term>Antiviraux (usage thérapeutique)</term><term>Australie (épidémiologie)</term><term>Coût de la maladie</term><term>Grippe humaine ()</term><term>Grippe humaine (traitement médicamenteux)</term><term>Grippe humaine (transmission)</term><term>Grippe humaine (épidémiologie)</term><term>Humains</term><term>Modèles théoriques</term><term>Pandémies ()</term><term>Sialidase (antagonistes et inhibiteurs)</term><term>Évaluation des risques</term></keywords><keywords scheme="MESH" type="chemical" qualifier="administration & dosage" xml:lang="en"><term>Antiviral Agents</term><term>Enzyme Inhibitors</term></keywords><keywords scheme="MESH" type="chemical" qualifier="antagonists & inhibitors" xml:lang="en"><term>Neuraminidase</term></keywords><keywords scheme="MESH" type="chemical" qualifier="therapeutic use" xml:lang="en"><term>Antiviral Agents</term><term>Enzyme Inhibitors</term></keywords><keywords scheme="MESH" qualifier="administration et posologie" xml:lang="fr"><term>Antienzymes</term><term>Antiviraux</term></keywords><keywords scheme="MESH" qualifier="antagonistes et inhibiteurs" xml:lang="fr"><term>Sialidase</term></keywords><keywords scheme="MESH" qualifier="drug therapy" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Australia</term><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Influenza, Human</term><term>Pandemics</term></keywords><keywords scheme="MESH" qualifier="traitement médicamenteux" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="usage thérapeutique" xml:lang="fr"><term>Antienzymes</term><term>Antiviraux</term><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Australie</term><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Cost of Illness</term><term>Humans</term><term>Models, Theoretical</term><term>Risk Assessment</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Coût de la maladie</term><term>Grippe humaine</term><term>Humains</term><term>Modèles théoriques</term><term>Pandémies</term><term>Évaluation des risques</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Many nations maintain stockpiles of neuraminidase inhibitor (NAI) antiviral agents for use in influenza pandemics to reduce transmission and mitigate the course of clinical infection. Pandemic preparedness plans include the use of these stockpiles to deliver proportionate responses, informed by emerging evidence of clinical impact. Recent uncertainty about the effectiveness of NAIs has prompted these nations to reconsider the role of NAIs in pandemic response, with implications for pandemic planning and for NAI stockpile size.</p></sec><sec><title>Methods</title><p>We combined a dynamic model of influenza epidemiology with a model of the clinical care pathways in the Australian health care system to identify effective NAI strategies for reducing morbidity and mortality in pandemic events, and the stockpile requirements for these strategies. The models were informed by a 2015 assessment of NAI effectiveness against susceptibility, pathogenicity, and transmission of influenza.</p></sec><sec><title>Results</title><p>Liberal distribution of NAIs for early treatment in outpatient settings yielded the greatest benefits in all of the considered scenarios. Restriction of community-based treatment to risk groups was effective in those groups, but failed to prevent the large proportion of cases arising from lower risk individuals who comprise the majority of the population.</p></sec><sec><title>Conclusions</title><p>These targeted strategies are only effective if they can be deployed within the constraints of existing health care infrastructure. This finding highlights the critical importance of identifying optimal models of care delivery for effective emergency health care response.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/s12879-016-1866-7) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Mytton, Ot" uniqKey="Mytton O">OT Mytton</name></author><author><name sortKey="Rutter, Pd" uniqKey="Rutter P">PD Rutter</name></author><author><name sortKey="Donaldson, Lj" uniqKey="Donaldson L">LJ Donaldson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Mcvernon, J" uniqKey="Mcvernon J">J McVernon</name></author><author><name sortKey="Laurie, K" uniqKey="Laurie K">K Laurie</name></author><author><name sortKey="Nolan, T" uniqKey="Nolan T">T Nolan</name></author><author><name sortKey="Owen, R" uniqKey="Owen R">R Owen</name></author><author><name sortKey="Irving, D" uniqKey="Irving D">D Irving</name></author><author><name sortKey="Capper, H" uniqKey="Capper H">H Capper</name></author><author><name sortKey="Hyland, C" uniqKey="Hyland C">C Hyland</name></author><author><name sortKey="Faddy, H" uniqKey="Faddy H">H Faddy</name></author><author><name sortKey="Carolan, L" uniqKey="Carolan L">L Carolan</name></author><author><name sortKey="Barr, I" uniqKey="Barr I">I Barr</name></author><author><name sortKey="Kelso, A" uniqKey="Kelso A">A Kelso</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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