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A pandemic influenza modeling and visualization tool()

The National Strategy for Pandemic Influenza outlines a plan for community response to a potential pandemic. In this outline, state and local communities are charged with enhancing their preparedness. In order to help public health officials better understand these charges, we have developed a visua...

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Autores principales: Maciejewski, Ross, Livengood, Philip, Rudolph, Stephen, Collins, Timothy F., Ebert, David S., Brigantic, Robert T., Corley, Courtney D., Muller, George A., Sanders, Stephen W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. Published by Elsevier Ltd. 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7128504/
https://www.ncbi.nlm.nih.gov/pubmed/32288454
http://dx.doi.org/10.1016/j.jvlc.2011.04.002
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author Maciejewski, Ross
Livengood, Philip
Rudolph, Stephen
Collins, Timothy F.
Ebert, David S.
Brigantic, Robert T.
Corley, Courtney D.
Muller, George A.
Sanders, Stephen W.
author_facet Maciejewski, Ross
Livengood, Philip
Rudolph, Stephen
Collins, Timothy F.
Ebert, David S.
Brigantic, Robert T.
Corley, Courtney D.
Muller, George A.
Sanders, Stephen W.
author_sort Maciejewski, Ross
collection PubMed
description The National Strategy for Pandemic Influenza outlines a plan for community response to a potential pandemic. In this outline, state and local communities are charged with enhancing their preparedness. In order to help public health officials better understand these charges, we have developed a visual analytics toolkit (PanViz) for analyzing the effect of decision measures implemented during a simulated pandemic influenza scenario. Spread vectors based on the point of origin and distance traveled over time are calculated and the factors of age distribution and population density are taken into effect. Healthcare officials are able to explore the effects of the pandemic on the population through a geographical spatiotemporal view, moving forward and backward through time and inserting decision points at various days to determine the impact. Linked statistical displays are also shown, providing county level summaries of data in terms of the number of sick, hospitalized and dead as a result of the outbreak. Currently, this tool has been deployed in Indiana State Department of Health planning and preparedness exercises, and as an educational tool for demonstrating the impact of social distancing strategies during the recent H1N1 (swine flu) outbreak.
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spelling pubmed-71285042020-04-08 A pandemic influenza modeling and visualization tool() Maciejewski, Ross Livengood, Philip Rudolph, Stephen Collins, Timothy F. Ebert, David S. Brigantic, Robert T. Corley, Courtney D. Muller, George A. Sanders, Stephen W. J Vis Lang Comput Article The National Strategy for Pandemic Influenza outlines a plan for community response to a potential pandemic. In this outline, state and local communities are charged with enhancing their preparedness. In order to help public health officials better understand these charges, we have developed a visual analytics toolkit (PanViz) for analyzing the effect of decision measures implemented during a simulated pandemic influenza scenario. Spread vectors based on the point of origin and distance traveled over time are calculated and the factors of age distribution and population density are taken into effect. Healthcare officials are able to explore the effects of the pandemic on the population through a geographical spatiotemporal view, moving forward and backward through time and inserting decision points at various days to determine the impact. Linked statistical displays are also shown, providing county level summaries of data in terms of the number of sick, hospitalized and dead as a result of the outbreak. Currently, this tool has been deployed in Indiana State Department of Health planning and preparedness exercises, and as an educational tool for demonstrating the impact of social distancing strategies during the recent H1N1 (swine flu) outbreak. Elsevier Ltd. Published by Elsevier Ltd. 2011-08 2011-05-07 /pmc/articles/PMC7128504/ /pubmed/32288454 http://dx.doi.org/10.1016/j.jvlc.2011.04.002 Text en Copyright © 2011 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Maciejewski, Ross
Livengood, Philip
Rudolph, Stephen
Collins, Timothy F.
Ebert, David S.
Brigantic, Robert T.
Corley, Courtney D.
Muller, George A.
Sanders, Stephen W.
A pandemic influenza modeling and visualization tool()
title A pandemic influenza modeling and visualization tool()
title_full A pandemic influenza modeling and visualization tool()
title_fullStr A pandemic influenza modeling and visualization tool()
title_full_unstemmed A pandemic influenza modeling and visualization tool()
title_short A pandemic influenza modeling and visualization tool()
title_sort pandemic influenza modeling and visualization tool()
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7128504/
https://www.ncbi.nlm.nih.gov/pubmed/32288454
http://dx.doi.org/10.1016/j.jvlc.2011.04.002
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