Using results from infectious disease modeling to improve the response to a potential H7N9 influenza pandemic.
Identifieur interne : 000554 ( PubMed/Checkpoint ); précédent : 000553; suivant : 000555Using results from infectious disease modeling to improve the response to a potential H7N9 influenza pandemic.
Auteurs : Sonja A. Rasmussen [Géorgie (pays)] ; Stephen C. Redd [Géorgie (pays)]Source :
- Clinical infectious diseases : an official publication of the Infectious Diseases Society of America [ 1537-6591 ] ; 2015.
Descripteurs français
- KwdFr :
- Contrôle des maladies contagieuses, Grippe humaine (), Grippe humaine (transmission), Grippe humaine (épidémiologie), Humains, Maladies transmissibles (transmission), Maladies transmissibles (épidémiologie), Modèles théoriques, Pandémies, Planification des mesures d'urgence en cas de catastrophe (), Sous-type H7N9 du virus de la grippe A (pathogénicité).
- MESH :
English descriptors
- KwdEn :
- Communicable Disease Control, Communicable Diseases (epidemiology), Communicable Diseases (transmission), Disaster Planning (methods), Humans, Influenza A Virus, H7N9 Subtype (pathogenicity), Influenza, Human (epidemiology), Influenza, Human (prevention & control), Influenza, Human (transmission), Models, Theoretical, Pandemics.
- MESH :
- epidemiology : Communicable Diseases, Influenza, Human.
- methods : Disaster Planning.
- pathogenicity : Influenza A Virus, H7N9 Subtype.
- prevention & control : Influenza, Human.
- transmission : Communicable Diseases, Influenza, Human.
- Communicable Disease Control, Humans, Models, Theoretical, Pandemics.
Abstract
As the Centers for Disease Control and Prevention (CDC) and other government agencies prepared for a possible H7N9 pandemic, many questions arose about the virus's expected burden and the effectiveness of key interventions. Public health decision makers need information to compare interventions so that efforts can be focused on interventions most likely to have the greatest impact on morbidity and mortality. To guide decision making, CDC's pandemic response leadership turned to experts in modeling for assistance. H7N9 modeling results provided a quantitative estimate of the impact of different interventions and emphasized the importance of key assumptions. In addition, these H7N9 modeling efforts highlighted the need for modelers to work closely with investigators collecting data so that model assumptions can be adjusted as new information becomes available and with decision makers to ensure that the results of modeling impact policy decisions.
DOI: 10.1093/cid/civ090
PubMed: 25878303
Affiliations:
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Public health decision makers need information to compare interventions so that efforts can be focused on interventions most likely to have the greatest impact on morbidity and mortality. To guide decision making, CDC's pandemic response leadership turned to experts in modeling for assistance. H7N9 modeling results provided a quantitative estimate of the impact of different interventions and emphasized the importance of key assumptions. 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In addition, these H7N9 modeling efforts highlighted the need for modelers to work closely with investigators collecting data so that model assumptions can be adjusted as new information becomes available and with decision makers to ensure that the results of modeling impact policy decisions. </AbstractText><CopyrightInformation>Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2015. 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