A workshop and conference –
"Mitigating the spread of A/H1N1 Flu:
Lessons Learned from Past Outbreaks"

INTRO

A new A/H1N1 influenza (flu) strain was first reported/identified in Mexico City on April 13 2009 and over a period of two-weeks, the World Health Organization moved the pandemic alert classification from level 3 to 5.

As of May 5th, 590 confirmed cases with 26 deaths had been confirmed in Mexico. There have been 140 cases in Canada and 403 in 38 states across the USA. So far about 1500 cases have been confirmed in twenty-five nations in Europe, Canada, New Zealand, and Asia. Preliminary reports suggest there is some "evolutionary pathway" similarity between the current H1N1 outbreak and past serious outbreaks or pandemics. Past pandemics patterns have often included two outbreaks, an initial outbreak followed by a second wave. The first wave, driven by what appeared to be a mild virulent strain in the spring, have been followed by a more explosive outbreak in the fall. It has been estimated that, during the 1918 outbreak, the second waves may have been responsible for over 90 percent of the deaths linked to the entire pandemic.

Whether or not the final course of this current outbreak will resemble the patterns of the 1918, 1957 or 1968 outbreaks, or simply die out after the initial outbreak, this is a matter of grave concern and the subject of intense public discussion.

Currently, influenza or its consequences are responsible for about 35,000 deaths during the winter season in the US alone, with the majority of the victims being older than 65. Vaccine, antiviral drugs, and improved health practices and services have reduced the risks associated with influenza and its complications.

Advances in disease surveillance, particularly those following the tragic events of 9/11, are being used to track influenza's morbidity and mortality while our ability to conduct timely influenza tests has expanded to the point that we can now quickly identify specific strains. The continuous explosion in computational advances (software and hardware) makes it possible to handling and sharing of large data sets in real-time. This means we have the means, tools and expertise to explore a large number of intervention possibilities as epidemics unfold.

Workshop/Conference

This workshop brings together the members of the Southwest Consortium and members of the international community of influenza experts thanks to the support of local and national US organizations.

The workshop will review the lessons learned from previous epidemics and pandemics of influenza—including the ongoing outbreak, with three goals:

1. Preparing for possible challenging issues if it cycles around
   
2. Assessing current thinking/models against the real world data coming in
   
3. Connecting longer term framing/preparedness to efficacy in the decision-making process in order to reduce the likelihood of introducing policies that increase the fragility of a highly interconnected global economy.

Questions and Topics that would drive the workshop include:

1. What have we learned from previous pandemics/epidemics?
2. Is the current use/management of antiviral drugs sustainable?
3. Can we quantify the role of animal reservoirs, including migratory birds on global influenza epidemics — southern versus northern hemisphere dynamics?
4. What is the impact of local and global transformation systems?
   
5. Can we efficiently and securely manage public health department data so that it can drive real-time surveillance systems?
6. What advances can we expect in the development influenza and pneumonia vaccines and how can we assess their impact?
7. What are the lessons learned from the ongoing local, national and international health efforts driven by the current H1N1threat.

Partial List of Speakers

• Julien Arino (Department of Mathematics, University of Manitoba, CA)
• H. T. Banks (Center for Quantitative Sciences in Biomedicine, North Carolina State University)
• Fred Brauer (Department of Mathematics, University of British Columbia, Canada)
• Roy Curtiss III (Center for Infectious Diseases and Vaccinology, Biodesign Institute, ASU)
• Gerardo Chowell-Puente (School of Human Evolution and Social Change, ASU)
• Zhilan Feng (Department of Mathematics, Purdue University)
• John Glasser (Centers for Disease Control and Emory University)
• Mac Hyman (Theoretical Division, Los Alamos National Laboratory)
• Yang Kuang (School of Mathematical and Statistical Sciences, ASU)
• Tim Lant (The Decision Theater, ASU)
• Miriam Nuño (Department of Neurosurgery, Cedars-Sinai Medical Center)
• George Poste (Complex Adaptive Systems Initiative, ASU)
• Eunha Shim (Yale School of Public Health, Yale University)
• Carl Taylor (Center for Strategic Health Innovation, College of Medicine, University of South Alabama )
• Xiaohong Wang (Mathematical, Computational and Modeling Sciences Center, ASU)
• James Watmough (Department of Mathematics and Statistics, University of New Brunswick, CA)
• Glenn Web (Department of Mathematics, Vanderbilt University)
• Laura White (Department of Biostatistics, Harvard School of Public Health)
• Jianhong Wu (MITACS, York University, Canada)
• Ping Yan (Public Health Agency of Canada) and more.

Local Organizing Committee

• Miriam Nuño (Department of Neurosurgery, Cedars-Sinai Medical Center),
• Tim Lant (The Decision Theater, ASU),
• Gerardo Chowell-Puente (School of Human Evolution and Social Change, ASU),
• Megan Jehn (Health Management and Policy Department, W.P. Carey School of Business),
• Carlos Castillo-Chavez (Mathematical, Computational and Modeling Sciences Center, ASU),
• George Basile (School of Sustainability, ASU), and James J Elser (School of Life Sciences, ASU)

Scientific Advisory Board

• H. T. Banks (Center for Quantitative Sciences in Biomedicine, North Carolina State University),
• Fred Brauer (Department of Mathematics, University of British Columbia, Canada),
• Roy Curtiss (Center for Infectious Diseases and Vaccinology, Biodesign Institute, ASU),
• Alison Galvani (Yale School of Public Health, Yale University),
• John Glasser (Centers for Disease Control and Emory University),
• Simon A Levin (Center of BioComplexity, Princeton University),
• Marcello Pagano (Department of Biostatistics, Harvard School of Public Health),
• George Poste (Complex Adaptive Systems Initiative, ASU),
• Ping Yan (Public Health Agency of Canada);
• Jianhong Wu (MITACS, York University, Canada)

Internal Sponsors

• The Decision Theater
• The Mathematical, Computational and Modeling Sciences Center
• The School of Human Evolution and Social Change
• The School of Mathematical and Statistical Sciences
• The School of Life Sciences
• The Office of the Vice President for Research and Economic Affairs
• The Offices of the Provost and President
• The Southwest Consortium for Theoretical and Mathematical Biology

External Co-sponsors

• Center for Bio-Security Science at LAN
• Institute for Mathematics and its Applications (IMA)
• Mathematical Biosciences Institute (MBI)
• The Mathematics for Information Technology and Complex Systems
• Centre for Disease Modeling and Public Health Agency of Canada