Meeting of Advisory Board: MIT Project on Pandemic Flu Preparedness and Response Richard C. Larson, PI Stan Finkelstein, co-PI Massachusetts Institute of Technology Cambridge, MA September 26, 2008

! To Massachusetts in Early Autumn!

Boston, Home of the…

Thinking of the Red Sox, World Series 1918 World SeriesCHAMPIONS

For current Bostonians, 1918 has meant… World Series victory Yet, we today can celebrate the 90th Anniversary of the Great Influenza, urban epicenter: Boston! How did the Boys-of-October do it in Fenway Park while upwards of 200 Bostonians were dying each day of the flu?

museum/collections/archive s/agalleries/1918flu/Reeve jpg

hives/agalleries/1918flu/Reeve2960.jpg

Advisory Board Meeting: Purposes To address NPI’s as a priority issue in pandemic flu planning. For you to offer constructive suggestions to our MIT team, helping to make our research as useful as possible. To share best practices in pandemic flu planning, especially with respect to NPI’s. To create a community of practitioners and scholars on this subject, a community that can continue dialogue via the Internet after this meeting.

Research Supported by the Sloan Foundation “Decision-Oriented Analysis of Pandemic Flu Preparedness & Response.” Our team includes research physicians, mathematical modelers, policy analysts and MIT students. Our work has included new forms of mathematical modeling to address various behavioral responses to the flu, especially those involved with social distancing and hygienic responses. And we have evaluated a sample of the state pandemic flu plans, as published on the Internet during the past year.

Introductions

Welcome! Advisory Board, MIT Pandemic Flu Project John V Barry Author/historian Margaret “Peggy” Enders MIT Emergency Continuity Planning Office Daniel Ford IBM Research Watson/Almaden Jeffrey Levi Trust for America's Health Kenneth D Mandl MD* Children’s Hospital, Harvard Medical School William P Pierskalla UCLA Anderson Graduate School of Business Kimberly Thompson* Harvard School of Public Health Eric S Toner MD Center for Biosecurity, University Pittsburgh Medical Center William C VanSchalkwyk* MIT Environmental Health & Safety Program Sanford L Weiner MIT Center for International Studies Irving Wladawsky-Berger* IBM, MIT Engineering Systems Division * Unable to be here today.

The MIT Team Richard C. Larson, PI Stan N. Finkelstein, co-PI Karima Nigmatulina - Operations Research PhD student Anna Teytelman - Operations Research PhD student Shiva Prakash - MIT Sloan School student Katsunobu Sasanuma - MIT Masters student, ESD, OR Mandi Holmes - Recent MIT graduate, history Kelley Bailey - MIT undergraduate Scott M. Cooper - writer Joanne McHugh - Stan’s assistant Alison Hearn - Dick’s assistant

Plan for this Morning Introductions & Overview, Goals & Objectives for the Project,8:30 – 9:00 AM Richard C. Larson, Stan Finkelstein Modeling Flu Progression 1: R 0 & Effects of Heterogeneities9:00 – 9:30 AM Richard C. Larson Modeling Flu Progression 2: Community-to-Community Spread9:30 – 10:00 AM Karima Nigmatulina Coffee Break10:00 – 10:30 AM Non-Pharmaceutical Interventions for the Home10:30 – 11:00 AM Stan Finkelstein, Shiva Prakash, An Analysis of the States’ Plans11:00 – 11:20 AM Stan Finkelstein, Karima Nigmatulina, Richard C. Larson A Bit of History in Boston11:20 – 11:30 AM Mandi Holmes Beginnings of Fundamental Research on R 0 11:30 – 11:40 AM Anna Teytelman, with Richard C. Larson MIT’s Plans Karima Nigmatulina, with Peggy Enders & Bill VanSchalkwyk11:40 – 12:00 Noon

Plan for This Afternoon Working Lunch 12:00 – 1:30 PM Open Discussion 1:00 – 3:00 PM. Coffee Break & Adjournment3:00 – 3:30 PM

Influenza Pandemic

SARS, 2003

fao.org cache.dailylife.com

Research being done at the Center for Engineering Systems Fundamentals, within the Engineering Systems Division of MIT

Pandemic Influenza: Social Distancing Richard C. Larson, PI Stan N. Finkelstein, co-PI Karima Nigmatulina Anna Teytelman Shiva Prakash Katsunobu Sasanuma Mandi Holmes Kelley Bailey Summer UROPs (2007) Freshman Advising Seminar: Living Through a Deadly Influenza Pandemic Advisory Board Modeling of the Dynamics of an Influenza Pandemic: Seeking Non-Medical Intervention Strategies to Deter its Progression IBM, Sloan Foundation, and now, CDC

Project Papers - to date Simple Models of Influenza Progression within a Heterogeneous Population, Operations Research, May-June (RCL) Stopping Pandemic Flu: Government and Community Interventions in a Multi- Community Model (Karima Nigmatulina & RCL), to appear in EJOR. Revisiting R 0, the Basic Reproductive Number for Pandemic Influenza, under revision, Medical Decision Making. (RCL). Pandemic Flu: Yes, We Can Do Something About It! To appear in special 'flu issue' of the Cal-OSHA Reporter. (RCL) Empowering Individuals and Families in the Event of a flu Pandemic. Draft. (Stan, Shiva Prakash, Dick) Pandemic Influenza: Preparations and Plans. DRAFT Report John M. Barry, A Conversation with John M. Barry, Oct. 15, Available on MIT World.

Plus, On April 22, 23, 2008 We gave a 2-day workshop to planners from 10 states (plus CDC, Lisa Koonin, Senior Advisor, CDC Influenza Coordination Unit ): –California –New York –New Jersey –Georgia –Massachusetts –Vermont –Illinois –Colorado –Pennsylvania –Alabama

Goals  Improve the Pandemic Preparedness & Response system.  National  State  City  Business  Family (Educate that much control is in our hands!)  Individual levels  Develop improved procedures for analyzing and creating Pandemic Preparedness & Response plans.

And, now, the Good News! :) Take it away, Dr. Stan Finkelstein….

27 Linking Assessment and Measurement to Public Health Emergency Preparedness Systems (LAMPS) Partnership with Harvard School of Public Health – Howard Koh, M.D. (Associate Dean), Overall Principal Investigator Response to RFA from the CDC. “Core” and Four Projects: 1.“Systems Improvement” 2.“Engineering Systems Analysis” (Finkelstein/Larson) 3.“Risk Communications” 4.“Drills and Exercises” *

28 Linking Assessment and Measurement to Public Health Emergency Preparedness Systems (LAMPS) (continued) Mission Statement “A unique multidisciplinary team will employ a public health systems approach to generate valid and reliable criteria and metrics to assess and ultimately improve public health emergency preparedness in the U.S.” Budget – Approximately $8.6 M over 5 Years

29 LAMPS…. Engineering Systems Analysis Finkelstein & Larson, Principal Investigators Principal AIM – –To develop and test engineering systems models of disease progression and transmission to analyze the behavior and response to the adoption of non-pharmaceutical interventions, as determinants of public health emergency preparedness. Research at Two Levels: - Macro (social distancing measures, school closures, etc.) - Micro (household mitigation practices, technologies) Initial focus on pandemic influenza. Later extension of conceptual frameworks to other public health emergencies.

End Part I

Modeling Flu Progression 1: R 0 & Effects of Heterogeneities

Framing I Social distancing and hygienic steps analysis via mathematical modeling, historical analysis, use of medical research and social science. Large concern with heterogeneous populations. By social distancing & hygienic measures, see how low we collectively can make the ‘flu multiplier’ R 0. Can we get it below 1.0? Long-term goal is to design new decision- oriented Flu Preparedness & Response Plans. Framing I

Framing II Decision makers are at all levels: governments, firms, families and individuals. Time will be of the essence. Lateral alignments, with pre-selected policies will be necessary. Each state is on its own: We will be in a multi-player cooperative ‘game’. –Imagine 50 simultaneous Hurricane Katrina’s with no possibility of Federal Help.

The States Have Been Active!

X-Sieve: CMU Sieve 2.2 Date: Sun, 17 Dec :14: (PST) From: Google Alerts To: Subject: Google Alert - Flu Pandemic Google News Alert for: Flu Pandemic  Arizona has pandemic plan, but gaps remain in preparations Mohave Valley News - Laughlin,NV,USA PHOENIX (AP) - Arizona has a detailed plan to direct the state's response to a possible flu pandemic but major gaps remain in preparations for what could be a...  State readies emergency plan for treating killer flu pandemic The Tennessean - Nashville,TN,USA AP. The coordinator of Tennessee's plan to handle a potential flu pandemic says teaching communities how to respond quickly will be key to saving lives....  Maine Making Preparations For Flu Pandemic WMTW - Auburn,ME,USA AUGUSTA, Maine -- If a flu pandemic strikes, Maine's 3,900 licensed hospital beds would not come close to meeting demand. The state's...  Washington uses flu pandemic money to prepare for any disaster Seattle Post Intelligencer - USA AP WRITER. OLYMPIA, Wash. -- Washington state officials trying to figure out how to spend $7 million this year to prepare for a flu pandemic that may never...  Alabama Readies for Flu Pandemic, Other Disasters WSFA - Montgomery,AL,USA... a pandemic, stockpiling medical supplies, conducting drills and creating educational materials in hopes of lessening the devastation of a deadly flu outbreak...  State acknowledges gaps in flu pandemic plan News-Leader.com - Springfield,MO,USA Jefferson City — Missouri health officials say they're ahead of other states in preparing to respond to a pandemic flu outbreak but acknowledge shortcomings...  US States Prepare Possibility Of Flu Pandemic E Canada Now - Brantford,Ontario,Canada... eCanadaNow) - Many US States and their communities are getting creative as in an attempt to better prepare for the possibility of a widespread flu pandemic....  Wyo stresses local control in pandemic planning Jackson Hole Star-Tribune - Casper,WY,USA... Platte County health officials with an idea of how long it would take to set up a remote immunization clinic against a worldwide flu pandemic that many fear is...  State Says They're Prepared for Pandemic WLNS - Lansing,MI,USA... can pinpoint signs of disease outbreaks. In the case of a flu pandemic, that up-to-the-moment information could prove invaluable.  This once a day Google Alert is brought to you by Google.

Universities Are Creating Flu Plans, Too!

Information About Pandemic Influenza Visit this page for current Stanford-related information on the pandemic influenza. Last Updated: August 15, Public health officials have informed us that one means for minimizing the impact of an infectious disease outbreak in large populations is through “social distancing” of people. This term refers to limiting close contact of individuals so that they are less likely to spread infection. Therefore, our contingency planning includes determining criteria for decisions on issues such as the suspension of classes or the closing of dormitories and asking students to return to their homes.

We Can Learn from SARS

Hong Kong Results: Other Respiratory Infections The SARS epidemic was stopped. “What were the beneficial effects of the population’s hygienic steps & social distancing?” Incidence of other acute respiratory viral diseases during the key months April and May 2003 dropped 90% compared to seasonal norms. (seasonal influenza, parainfluenza, respiratory syncytial virus, & adenovirus). This is best evidence that behavioral modifications can dramatically reduce the spread of respiratory infections. Any modeling analysis that ignores behavioral changes removes our greatest disease-progression control strategies.

Mathematical Complications  Widely different contact patterns  Biologically non-homogenous population  Susceptibility  Infection spread  Behavioral Reactions  We are attempting to create a new adaptive ‘physics model’ of flu progression.

Many Previous Models:  All members of the susceptible population are identical from a modeling point of view.  There is a fundamental input constant for the model, the ‘basic reproductive ratio R 0,’ that characterizes the mean number of new influenza infections created by each newly infected person.  Local groups involving at least one infected person are characterized by homogenous mixing, meaning that each susceptible member of the group is equally likely to become infected from any infected person.  Social behavior does not change during the pandemic.

Flu Fundamentals: R 0 = p  frequency of daily contacts (“lambda”) p=probability of transmitting infection, given contact

Let’s talk about

Let’s talk about p

Issues with R 0 R 0 should be viewed as an output of a model of flu and not as an input. We, collectively and individually, have a large measure of control over the spread of the disease. (R 0 = p) R 0 is a population average and thus suffers from all the problems associated with averages depicting populations.

Issues with R 0 R 0 pertains only to the index patient, often super spreaders R 0 implies acceptance of a type of modeling approach that precludes others. The progression of the disease in a community has emergent properties.

Heterogeneity of Social and Professional Contacts (Fu)

Suppose that each time a person interacts with another, he/she leaves a slip of paper on the ground. Each interaction generates 2 slips - together. There are on average H n H interactions of high activity people on a given day (similarly for low activity) Consider a random interaction pair, with persons R1 and R2. The next interaction pair will be a high activity with another high activity person with probability ( H n H /[ H n H + L n L ]) 2. Similarly for other possibilities. The model uses simple difference equations to trace the evolution of the infection, generation by generation.

Key Points from 1st Model Within the context of attempted social controls, the generation-to-generation ‘reproductive ratio’ should be viewed as an outcome of the model, not an input. The product j p j is the primary determining factor associated with disease spread associated with that subpopulation. Public policies to control the disease may best be devoted to those groups having highest values of the product j p j. “Early separation” is better!

Model II - next Brings in spatial aspects, movements of people from one community to another. Uses both analytics and Monte Carlo simulation. Incorporates ‘personal social distancing functions,’ indicating how people’s behavior will change as the disease progresses through the community.

Spatiotemporal Epidemiological Modeler screenshot Dan Ford is the expert!

Social Distancing & Hygienic Policies to Reduce Prevalence of Infection Summary of Our Approach Research at the intersection of Engineering, Management and Social Science. Aims to inform decision making at multiple levels, esp. preventative decisions relating to reducing prevalence of infection. Creates a dynamic physics, in which epidemiology is merged with social behavior. Embraces population heterogeneity. Links to Social Science and Medical literature, leading to feasible decision policies at all levels.

Project Organization Math Modeling Efforts (Dick Larson) Inputs from Medical Community (Stan Finkelstein) (1) New Flu Physics Models (2) Identification of Needed Data (3) Identification of policies (4) Response plans attributes (5) Assessment of States’ plans (6) STEM implementation (7) Workshops and feedback (8) Wide dissemination ADVISORYPANELADVISORYPANEL Policies and Practices Develop the Physics Inform the Physics and Identify New Policies Understand & Inform Human Decision Makers

Thank You! Richard C. Larson