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Using Results From Infectious Disease Modeling to Improve the Response to a Potential H7N9 Influenza Pandemic
Author(s) -
Sonja A. Rasmussen,
Stephen C. Redd
Publication year - 2015
Publication title -
clinical infectious diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.44
H-Index - 336
eISSN - 1537-6591
pISSN - 1058-4838
DOI - 10.1093/cid/civ090
Subject(s) - psychological intervention , pandemic , medicine , government (linguistics) , public health , public health interventions , influenza pandemic , infectious disease (medical specialty) , h1n1 pandemic , disease , environmental health , risk analysis (engineering) , covid-19 , nursing , linguistics , philosophy , pathology
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.

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