Analyzing Spatio-temporal Patterns of Online Public Attentions in Emergency Events: A Case Study of 2009 H1N1 Influenza Outbreak in China

2014 ◽  
pp. 44-50
Author(s):  
Kainan Cui ◽  
Xiaolong Zheng ◽  
Zhu Zhang ◽  
Daniel Zeng
Keyword(s):  
Temporal Patterns ◽  
H1n1 Influenza ◽  
Influenza Outbreak ◽  
2009 H1n1 ◽  
Emergency Events ◽  
Spatio Temporal

Was the Pediatric Emergency Department or Pediatric Urgent Care Center Setting More Affected by the Fall 2009 H1N1 Influenza Outbreak?

2011 ◽  
Vol 50 (8) ◽  
pp. 764-766 ◽  
Author(s):  
Gregory P. Conners ◽  
Tracy Hartman ◽  
Milton A. Fowler ◽  
Lisa L. Schroeder ◽  
Thomas W. Tryon
Keyword(s):  
Emergency Department ◽  
Care Center ◽  
H1n1 Influenza ◽  
Pediatric Emergency ◽  
Urgent Care ◽  
Pediatric Emergency Department ◽  
Urgent Care Center ◽  
Influenza Outbreak ◽  
2009 H1n1

Monitor the 2009-H1N1 Influenza Outbreak

2009 ◽  
Vol 43 (6) ◽  
pp. 14
Author(s):  
MARY ANNE JACKSON
Keyword(s):  
H1n1 Influenza ◽  
Influenza Outbreak ◽  
2009 H1n1

Emergency Preparedness Practices in Correctional Facilities during the 2009 H1N1 Influenza Outbreak

2010 ◽  
Author(s):  
Alice S. Lee ◽  
David M. Berendes ◽  
Anne C. Spaulding ◽  
Katherine G. Seib ◽  
Koo-Whang Chung ◽  
...  
Keyword(s):  
Emergency Preparedness ◽  
H1n1 Influenza ◽  
Correctional Facilities ◽  
Influenza Outbreak ◽  
2009 H1n1

scholarly journals Distribution of vaccine/antivirals and the ‘least spread line’ in a stratified population

2009 ◽  
Vol 7 (46) ◽  
pp. 755-764 ◽  
Author(s):  
E. Goldstein ◽  
A. Apolloni ◽  
B. Lewis ◽  
J. C. Miller ◽  
M. Macauley ◽  
...  
Keyword(s):  
H1n1 Influenza ◽  
Mass Action ◽  
Initial Growth ◽  
Influenza Outbreak ◽  
Mass Action Model ◽  
The Us ◽  
Action Model ◽  
2009 H1n1 ◽  
Influenza Vaccinations ◽  
Prioritization Scheme

We describe a prioritization scheme for an allocation of a sizeable quantity of vaccine or antivirals in a stratified population. The scheme builds on an optimal strategy for reducing the epidemic's initial growth rate in a stratified mass-action model. The strategy is tested on the EpiSims network describing interactions and influenza dynamics in the population of Utah, where the stratification we have chosen is by age (0–6, 7–13, 14–18, adults). No prior immunity information is available, thus everyone is assumed to be susceptible—this may be relevant, possibly with the exception of persons over 50, to the 2009 H1N1 influenza outbreak. We have found that the top priority in an allocation of a sizeable quantity of seasonal influenza vaccinations goes to young children (0–6), followed by teens (14–18), then children (7–13), with the adult share being quite low. These results, which rely on the structure of the EpiSims network, are compared with the current influenza vaccination coverage levels in the US population.

scholarly journals Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke

2014 ◽  
Vol 134 ◽  
pp. 269-279 ◽  
Author(s):  
Nikola Kasabov ◽  
Valery Feigin ◽  
Zeng-Guang Hou ◽  
Yixiong Chen ◽  
Linda Liang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Temporal Patterns ◽  
Spiking Neural Networks ◽  
Spatio Temporal

Spatio-temporal patterns in phytoplankton assemblages in inshore–offshore gradients using flow cytometry: A case study in the eastern English Channel

2016 ◽  
Vol 156 ◽  
pp. 76-85 ◽  
Author(s):  
Simon Bonato ◽  
Elsa Breton ◽  
Morgane Didry ◽  
Fabrice Lizon ◽  
Vincent Cornille ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Temporal Patterns ◽  
English Channel ◽  
Phytoplankton Assemblages ◽  
Spatio Temporal
Sign in / Sign up

Export Citation Format

Share Document