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Coordinating the real‐time use of global influenza activity data for better public health planning

Health planners from global to local levels must anticipate year‐to‐year and week‐to‐week variation in seasonal influenza activity when planning for and responding to epidemics to mitigate their impact. To help with this, countries routinely collect incidence of mild and severe respiratory illness a...

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Autores principales: Biggerstaff, Matthew, Dahlgren, Fredrick Scott, Fitzner, Julia, George, Dylan, Hammond, Aspen, Hall, Ian, Haw, David, Imai, Natsuko, Johansson, Michael A., Kramer, Sarah, McCaw, James M., Moss, Robert, Pebody, Richard, Read, Jonathan M., Reed, Carrie, Reich, Nicholas G., Riley, Steven, Vandemaele, Katelijn, Viboud, Cecile, Wu, Joseph T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7040973/
https://www.ncbi.nlm.nih.gov/pubmed/32096594
http://dx.doi.org/10.1111/irv.12705
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author Biggerstaff, Matthew
Dahlgren, Fredrick Scott
Fitzner, Julia
George, Dylan
Hammond, Aspen
Hall, Ian
Haw, David
Imai, Natsuko
Johansson, Michael A.
Kramer, Sarah
McCaw, James M.
Moss, Robert
Pebody, Richard
Read, Jonathan M.
Reed, Carrie
Reich, Nicholas G.
Riley, Steven
Vandemaele, Katelijn
Viboud, Cecile
Wu, Joseph T.
author_facet Biggerstaff, Matthew
Dahlgren, Fredrick Scott
Fitzner, Julia
George, Dylan
Hammond, Aspen
Hall, Ian
Haw, David
Imai, Natsuko
Johansson, Michael A.
Kramer, Sarah
McCaw, James M.
Moss, Robert
Pebody, Richard
Read, Jonathan M.
Reed, Carrie
Reich, Nicholas G.
Riley, Steven
Vandemaele, Katelijn
Viboud, Cecile
Wu, Joseph T.
author_sort Biggerstaff, Matthew
collection PubMed
description Health planners from global to local levels must anticipate year‐to‐year and week‐to‐week variation in seasonal influenza activity when planning for and responding to epidemics to mitigate their impact. To help with this, countries routinely collect incidence of mild and severe respiratory illness and virologic data on circulating subtypes and use these data for situational awareness, burden of disease estimates and severity assessments. Advanced analytics and modelling are increasingly used to aid planning and response activities by describing key features of influenza activity for a given location and generating forecasts that can be translated to useful actions such as enhanced risk communications, and informing clinical supply chains. Here, we describe the formation of the Influenza Incidence Analytics Group (IIAG), a coordinated global effort to apply advanced analytics and modelling to public influenza data, both epidemiological and virologic, in real‐time and thus provide additional insights to countries who provide routine surveillance data to WHO. Our objectives are to systematically increase the value of data to health planners by applying advanced analytics and forecasting and for results to be immediately reproducible and deployable using an open repository of data and code. We expect the resources we develop and the associated community to provide an attractive option for the open analysis of key epidemiological data during seasonal epidemics and the early stages of an influenza pandemic.
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spelling pubmed-70409732020-03-01 Coordinating the real‐time use of global influenza activity data for better public health planning Biggerstaff, Matthew Dahlgren, Fredrick Scott Fitzner, Julia George, Dylan Hammond, Aspen Hall, Ian Haw, David Imai, Natsuko Johansson, Michael A. Kramer, Sarah McCaw, James M. Moss, Robert Pebody, Richard Read, Jonathan M. Reed, Carrie Reich, Nicholas G. Riley, Steven Vandemaele, Katelijn Viboud, Cecile Wu, Joseph T. Influenza Other Respir Viruses View Point Health planners from global to local levels must anticipate year‐to‐year and week‐to‐week variation in seasonal influenza activity when planning for and responding to epidemics to mitigate their impact. To help with this, countries routinely collect incidence of mild and severe respiratory illness and virologic data on circulating subtypes and use these data for situational awareness, burden of disease estimates and severity assessments. Advanced analytics and modelling are increasingly used to aid planning and response activities by describing key features of influenza activity for a given location and generating forecasts that can be translated to useful actions such as enhanced risk communications, and informing clinical supply chains. Here, we describe the formation of the Influenza Incidence Analytics Group (IIAG), a coordinated global effort to apply advanced analytics and modelling to public influenza data, both epidemiological and virologic, in real‐time and thus provide additional insights to countries who provide routine surveillance data to WHO. Our objectives are to systematically increase the value of data to health planners by applying advanced analytics and forecasting and for results to be immediately reproducible and deployable using an open repository of data and code. We expect the resources we develop and the associated community to provide an attractive option for the open analysis of key epidemiological data during seasonal epidemics and the early stages of an influenza pandemic. John Wiley and Sons Inc. 2019-12-03 2020-03 /pmc/articles/PMC7040973/ /pubmed/32096594 http://dx.doi.org/10.1111/irv.12705 Text en © 2019 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle View Point
Biggerstaff, Matthew
Dahlgren, Fredrick Scott
Fitzner, Julia
George, Dylan
Hammond, Aspen
Hall, Ian
Haw, David
Imai, Natsuko
Johansson, Michael A.
Kramer, Sarah
McCaw, James M.
Moss, Robert
Pebody, Richard
Read, Jonathan M.
Reed, Carrie
Reich, Nicholas G.
Riley, Steven
Vandemaele, Katelijn
Viboud, Cecile
Wu, Joseph T.
Coordinating the real‐time use of global influenza activity data for better public health planning
title Coordinating the real‐time use of global influenza activity data for better public health planning
title_full Coordinating the real‐time use of global influenza activity data for better public health planning
title_fullStr Coordinating the real‐time use of global influenza activity data for better public health planning
title_full_unstemmed Coordinating the real‐time use of global influenza activity data for better public health planning
title_short Coordinating the real‐time use of global influenza activity data for better public health planning
title_sort coordinating the real‐time use of global influenza activity data for better public health planning
topic View Point
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7040973/
https://www.ncbi.nlm.nih.gov/pubmed/32096594
http://dx.doi.org/10.1111/irv.12705
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