research on the transmission of disease in airports and on aircraft

8/8/2019 Research on the Transmission of Disease in Airports and on Aircraft

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Research on the Transmission of Disease

in Airports and on AircraftSUMMARY OF A SYMPOSIUM

CONFERENCE PROCEEDINgS 4


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TRANSPORTATION RESEARCH BOARD

2010 EXECUTIVE COMMITTEE*

Chair:Michael R. Morris, Director of Transportation, North Central Texas Council of Governments, ArlingtonVice Chair:Neil J. Pedersen, Administrator, Maryland State Highway Administration, BaltimoreExecutive Director: Robert E. Skinner, Jr., Transportation Research Board

J. Barry Barker, Executive Director, Transit Authority of River City, Louisville, KentuckyAllen D. Biehler, Secretary, Pennsylvania Department of Transportation, HarrisburgLarry L. Brown, Sr., Executive Director, Mississippi Department of Transportation, Jackson

Deborah H. Butler, Executive Vice President, Planning, and CIO, Norfolk Southern Corporation, Norfolk, VirginiaWilliam A. V. Clark, Professor, Department of Geography, University of California, Los AngelesEugene A. Conti, Jr., Secretary of Transportation, North Carolina Department of Transportation, RaleighNicholas J. Garber, Henry L. Kinnier Professor, Department of Civil Engineering, and Director, Center for Transportation

Studies, University of Virginia, CharlottesvilleJeffrey W. Hamiel, Executive Director, Metropolitan Airports Commission, Minneapolis, MinnesotaPaula J. Hammond, Secretary, Washington State Department of Transportation, OlympiaEdward A. (Ned) Helme, President, Center for Clean Air Policy, Washington, D.C.Adib K. Kanafani, Cahill Professor of Civil Engineering, University of California, Berkeley (Past Chair, 2009)Susan Martinovich, Director, Nevada Department of Transportation, Carson CityDebra L. Miller, Secretary, Kansas Department of Transportation, Topeka (Past Chair, 2008)Sandra Rosenbloom, Professor of Planning, University of Arizona, TucsonTracy L. Rosser, Vice President, Corporate Traffic, Wal-Mart Stores, Inc., Mandeville, LouisianaSteven T. Scalzo, Chief Operating Officer, Marine Resources Group, Seattle, WashingtonHenry G. (Gerry) Schwartz, Jr., Chairman (retired), Jacobs/Sverdrup Civil, Inc., St. Louis, MissouriBeverly A. Scott, General Manager and Chief Executive Officer, Metropolitan Atlanta Rapid Transit Authority, Atlanta, GeorgiaDavid Seltzer, Principal, Mercator Advisors LLC, Philadelphia, PennsylvaniaDaniel Sperling, Professor of Civil Engineering and Environmental Science and Policy; Director, Institute of Transportation

Studies; and Interim Director, Energy Efficiency Center, University of California, DavisKirk T. Steudle, Director, Michigan Department of Transportation, LansingDouglas W. Stotlar, President and Chief Executive Officer, Con-Way, Inc., Ann Arbor, MichiganC. Michael Walton, Ernest H. Cockrell Centennial Chair in Engineering, University of Texas, Austin (Past Chair, 1991)

Peter H. Appel, Administrator, Research and Innovative Technology Administration, U.S. Department of Transportation(ex officio)

J. Randolph Babbitt, Administrator, Federal Aviation Administration, U.S. Department of Transportation (ex officio)Rebecca M. Brewster, President and COO, American Transportation Research Institute, Smyrna, Georgia (ex officio)George Bugliarello, President Emeritus and University Professor, Polytechnic Institute of New York University, Brooklyn;

Foreign Secretary, National Academy of Engineering, Washington, D.C. (ex officio)Anne S. Ferro, Administrator, Federal Motor Carrier Safety Administration, U.S. Department of Transportation (ex officio)LeRoy Gishi, Chief, Division of Transportation, Bureau of Indian Affairs, U.S. Department of the Interior, Washington, D.C.

(ex officio)Edward R. Hamberger, President and CEO, Association of American Railroads, Washington, D.C. (ex officio)John C. Horsley, Executive Director, American Association of State Highway and Transportation Officials, Washington, D.C.

(ex officio)David T. Matsuda, Deputy Administrator, Maritime Administration, U.S. Department of Transportation (ex officio)Victor M. Mendez, Administrator, Federal Highway Administration, U.S. Department of Transportation (ex officio)William W. Millar, President, American Public Transportation Association, Washington, D.C. (ex officio) (Past Chair, 1992)Robert J. Papp (Adm., U.S. Coast Guard), Commandant, U.S. Coast Guard, U.S. Department of Homeland Security (ex officio)Cynthia L. Quarterman, Administrator, Pipeline and Hazardous Materials Safety Administration, U.S. Department of

Transportation (ex officio)Peter M. Rogoff, Administrator, Federal Transit Administration, U.S. Department of Transportation (ex officio)David L. Strickland, Administrator, National Highway Traffic Safety Administration, U.S. Department of Transportation

(ex officio)Joseph C. Szabo, Administrator, Federal Railroad Administration, U.S. Department of Transportation (ex officio)Polly Trottenberg, Assistant Secretary for Transportation Policy, U.S. Department of Transportation (ex officio)

Robert L. Van Antwerp (Lt. General, U.S. Army), Chief of Engineers and Commanding General, U.S. Army Corps of Engineers,Washington, D.C. (ex officio)

* Membership as of July 2010.


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C o n f e r e n C e P r o C e e d i n g s 4 7

Research on the Transmissionof Disease in Airports

and on AircraftSummary of a Symposium

CHRISTINE L. GERENCHER, Transportation Research BoardRapporteur

September 1718, 2009The Keck Center of the National Academies

Washington, D.C.

Sponsored byAirport Cooperative Research ProgramTransportation Research Board

Washington, D.C.2010

www.TRB.org


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Transportation Research Board Conference Proceedings 47ISSN 1073-1652ISBN 978-0-309-14295-3

Subscriber CategoryV aviation

Transportation Research Board (TRB) publications are available by ordering individual publications directly from the TRB Business

Office, through the Internet at www.TRB.org or national-academies.org/trb, or by annual subscription through organizational or indi-vidual affiliation with TRB. Affiliates and library subscribers are eligible for substantial discounts. For further information, contact theTRB Business Office, 500 Fifth Street, NW, Washington, DC 20001 (telephone 202-334-3213; fax 202-334-2519; or e-mail [email protected]).

Printed in the United States of America.

NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whosemembers are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Instituteof Medicine. The members of the committee responsible for the project were chosen for their special competencies and with regard forappropriate balance.

This report has been reviewed by a group other than the authors according to the procedures approved by a Report Review Committeeconsisting of members of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine.

This project was sponsored by the Airport Cooperative Research Program and the Transportation Research Board.

Committee on Research on the Transmission of Disease in Airports and on Aircraft: A Symposium

Katherine Andrus, Air Transport Association, ChairAlan Black, DallasFt. Worth International AirportAnthony D. B. Evans, International Civil Aviation OrganizationMark Gendreau, Lahey Clinic Medical Center and Tufts University School of MedicineMarc Lipsitch, Harvard School of Public Health, Department of Epidemiology

John C. Neatherlin, Centers for Disease Control and PreventionChris Seher, Department of Homeland Security

John Jack Spengler, Harvard School of Public HealthJennifer Topmiller, National Institute for Occupational Safety and HealthJeanne C. Yu, Boeing Commercial Airplanes

Symposium Planning Committee LiaisonJean Watson, Federal Aviation Administration

TRB StaffMark Norman, Director, Technical Activities

Christine Gerencher, Senior Program Officer for Aviation and EnvironmentFreda Morgan, Senior Program Associate

TRB Publications OfficeCay Butler, Editor

Javy Awan, Production EditorJennifer J. Weeks, Manuscript PreparationJuanita Green, Production Manager

Cover design by Beth Schlenoff, Beth Schlenoff DesignTypesetting by Carol Levie, Grammarians


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The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguishedscholars engaged in scientific and engineering research, dedicated to the furtherance of science andtechnology and to their use for the general welfare. On the authority of the charter granted to it bythe Congress in 1863, the Academy has a mandate that requires it to advise the federal governmenton scientific and technical matters. Dr. Ralph J. Cicerone is president of the National Academy ofSciences.

The National Academy of Engineering was established in 1964, under the charter of the NationalAcademy of Sciences, as a parallel organization of outstanding engineers. It is autonomous in itsadministration and in the selection of its members, sharing with the National Academy of Sciences theresponsibility for advising the federal government. The National Academy of Engineering also spon-sors engineering programs aimed at meeting national needs, encourages education and research, and

recognizes the superior achievements of engineers. Dr. Charles M. Vest is president of the NationalAcademy of Engineering.

The Institute of Medicine was established in 1970 by the National Academy of Sciences to securethe services of eminent members of appropriate professions in the examination of policy matters per-taining to the health of the public. The Institute acts under the responsibility given to the NationalAcademy of Sciences by its congressional charter to be an adviser to the federal government and, onits own initiative, to identify issues of medical care, research, and education. Dr. Harvey V. Finebergis president of the Institute of Medicine.

The National Research Council was organized by the National Academy of Sciences in 1916 toassociate the broad community of science and technology with the Academys purposes of further-ing knowledge and advising the federal government. Functioning in accordance with general policiesdetermined by the Academy, the Council has become the principal operating agency of both theNational Academy of Sciences and the National Academy of Engineering in providing services to thegovernment, the public, and the scientific and engineering communities. The Council is administeredjointly by both the Academies and the Institute of Medicine. Dr. Ralph J. Cicerone and Dr. CharlesM. Vest are chair and vice chair, respectively, of the National Research Council.

The Transportation Research Board is one of six major divisions of the National Research Council.The mission of the Transportation Research Board is to provide leadership in transportation inno-vation and progress through research and information exchange, conducted within a setting that isobjective, interdisciplinary, and multimodal. The Boards varied activities annually engage about7,000 engineers, scientists, and other transportation researchers and practitioners from the publicand private sectors and academia, all of whom contribute their expertise in the public interest. The

program is supported by state transportation departments, federal agencies including the componentadministrations of the U.S. Department of Transportation, and other organizations and individualsinterested in the development of transportation. www.TRB.org

www.national-academies.org


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Contents

PREFACE ................................................................................................................................................ 1

OVERVIEW............................................................................................................................................. 3Christine L. Gerencher

Session 1UNDERSTANDING HOW DISEASE IS TRANSMITTED VIA AIR TRAVEL

The Aircraft Cabin Environment .............................................................................................................5Jeanne Yu (Presenter)

Human Movement Patterns and the Spread of Infectious Diseases ...........................................................7Ben S. Cooper (Presenter)

Session 2PRACTICAL CASE-RESPONSE APPROACHES TO INVESTIGATING THE SPREAD OFDISEASE IN AIRPORTS AND ON AIRCRAFT

Norovirus Transmission on Aircraft .......................................................................................................12Dan Fishbein (Presenter), Hannah L. Kirking, Jennifer Cortes, Sherry Burrer, Aron Hall,Nicole J. Cohen, Harvey Lipman, Curi Kim, and Elizabeth R. Daly

Swine Flu A/H1N1 Transmission via the Aviation Sector ......................................................................12Itamar Grotto (Presenter), Shepherd Roee Singer, and Emilia Anis

Session 3THEORETICAL MODELING APPROACHES TO INVESTIGATING THE SPREAD OFDISEASE IN AIRPORTS AND ON AIRCRAFT

Summarizing Exposure Patterns on Commercial Aircraft .......................................................................15James S. Bennett (Presenter), Jennifer L. Topmiller, Yuanhui Zhang, and Watts L. Dietrich


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Advance Models for Predicting Contaminants and Infectious Disease Virus Transport inthe Airliner Cabin Environment (Part 1) .................................................................................................21

Qingyan (Yan) Chen (Presenter), Sagnik Mazumdar, Michael W. Plesniak,Stephane Poussou, Paul E. Sojka, Tengfei Zhang, and Zhao Zhang

Advance Models for Predicting Contaminants and Infectious Disease Virus Transport in

the Airliner Cabin Environment (Part 2) .................................................................................................28Byron Jones (Presenter)

Characterizing the Risk of Tuberculosis Infection in Commercial Aircraft by UsingQuantitative Microbial Risk Assessment .................................................................................................35

Joan B. Rose (Presenter) and Mark H. Weir

Session 4EXPERIMENTAL BENCH SCIENCE APPROACHES TO INVESTIGATINGTHE SPREAD OF DISEASE IN AIRPORTS AND ON AIRCRAFT

Interventions for Preventing the Transmission of Influenza Virus ...........................................................39James J. McDevitt and Donald K. Milton

The Role of Fomites in the Transmission of Pathogens in Airports and on Aircraft ...............................41Charles P. Gerba

Session 5POLICIES AND PLANNING TO MINIMIZE THE SPREAD OF DISEASE

Transmission Patterns of Mosquito-Borne Infectious Diseases During Air Travel:Passengers, Pathogens, and Public Health Implications ...........................................................................43

James H. Diaz (Presenter)

Airline Policies and Procedures to Minimize the Spread of Diseases .......................................................48Rose M. Ong (Presenter)

The Practical Application of World Health Organization Travel Recommendations:Some Observations .................................................................................................................................49

Anthony D. B. Evans (Presenter)

Session 6DISCUSSION OF TOPICS FOR FUTURE RESEARCH ....................................................................... 51

Appendix ASYMPOSIUM AGENDA ........................................................................................................................54

Appendix BREFERENCE MATERIALS .................................................................................................................. 56


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1

In September 2009, abut 100 peple assembled inWashingtn, D.C., t participate in a sympsium nresearch n the transmissin disease in airprts

and n aircrat. The sympsium brught tgether indi-viduals rm the public sectr (ederal, state, and lcalagencies including public airprts), private sectr (air-lines and cnsultants with expertise in varius acets airprt emergency respnse), and research institutinst learn abut current research and t cnsider ways tcnduct and und uture research.

The sympsium gals were t examine (a) the status research n r related t the transmissin diseasen aircrat and in airprts, (b) the ptential applicatin research results t the develpment prtcls andstandards r managing cmmunicable disease incidentsin an aviatin setting, and (c) areas where additinalresearch is needed. T plan the event, TRB assembled acmmittee appinted by the Natinal Research Cuncil(NRC) t rganize and develp the sympsium prgram.The planning cmmittee was chaired by Katherine B.Andrus, Air Transprt Assciatin America, Inc.

The sympsium prgram was designed t prvide anpprtunity r the aviatin cmmunity t share data,mdels, and methds; discuss indings and preliminarycnclusins nging research; and identiy gaps tinrm uture research prjects. During the sympsium,cnsecutive sessins were rganized accrding t dier-ent appraches t research as identiied by the planningcmmittee. These appraches included case study investi-gatins, theretical mdeling, and bench science experi-mental methds. A sessin discussing dierent apprachest plicies and planning t minimize the spread disease

alng with an pen dialg amng all attendees n candi-date tpics r uture research was als cnducted.

This summary reprt cntains white papers, authredby the invited speakers t each sessin, that summarizethe presentatins they gave during the sympsium. Itincludes a summary the discussin tpics r utureresearch. The planning cmmittee was slely respnsibler rganizing the sympsium, identiying tpics, andchsing speakers. The respnsibility r the publishedsympsium summary rests with the sympsium rappr-teur and the institutin.

This reprt has been reviewed in drat rm by indi-viduals chsen r their diverse perspectives and techni-cal expertise in accrdance with prcedures apprved bythe NRC Reprt Review Cmmittee. The purpses this independent review are t prvide candid and criti-cal cmments that will assist the institutin in making thepublished reprt as sund as pssible and t ensure thatthe reprt meets institutinal standards r bjectivity,evidence, and respnsiveness t the prject charge. Thereview cmments and drat manuscript remain cniden-

tial t prtect the integrity the prcess.TRB thanks the llwing individuals r their review

this reprt: Katherine B. Andrus, Air Transprt Ass-ciatin America, Inc.; Debrah C. McElry, Air-prts Cuncil InternatinalNrth America; and PhyllisKzarsky, Expert Cnsultant, Centers r Disease Cn-trl and Preventin. Althugh the reviewers prvidedmany cnstructive cmments and suggestins, they didnt see the inal drat the reprt bere its release. Thereview this reprt was verseen by C. Michael Wal-tn, Ernest H. Cckrell Centennial Chair in Engineering,

Preface


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2 RESEARCH oN THE TRANSMISSIoN of DISEASE IN AIRPoRTS AND oN AIRCRAfT

University Texas at Austin. Appinted by NRC, hewas respnsible r ensuring that an independent exami-natin this reprt was carried ut in accrdance withinstitutinal prcedures and that all review cmmentswere careully cnsidered.

The cmmittee extends special thanks t the AirprtCperative Research Prgram oversight Cmmitteer prviding unding supprt r the wrkshp alngwith the visin and encuragement that made the eventthe success that it was.

2


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3

Overview

Christine L. Gerencher, Transportation Research Board

on September 1718, 2009, a diverse grup rep-resenting academia, gvernment, industry, andnnprit rganizatins came tgether t share

insights int the transmissin disease in airprts andn aircrat. The sympsium was the result almst8 mnths planning and discussin by a cmmitteechaired by Katherine B. Andrus, Air Transprt Ass-ciatin America, Inc., that included experts rm thepublic sectr (ederal, state, and lcal agencies includingpublic airprts), private sectr (airlines and cnsultantswith expertise in varius acets airprt emergencyrespnse), and research institutins. When planningbegan n the prgram, the cmmittee knew it was animprtant tpic but had n idea it wuld turn ut t bes timely. The utbreak and rapid spread the H1N1inluenza virus in April 2009 brught renewed attentint cmmunicable diseases.

Althugh the H1N1 pandemic underscred the rlethat travel generally plays in the spread disease, theplanning cmmittee decided t cus n the actual trans-missin disease during air travel. The mvement

inected peple has always cntributed t the spread disease rm ne place t anther, and air travel aectsthe pattern and rate that spread. Hwever, the cmmit-tee determined there was enugh interest in and uncer-tainty abut the spread disease within the aircrat andairprt envirnment t justiy devting the sympsiumt that tpic.

The sympsium pened with an intrductry sessinthat laid the grundwrk r a cmmn understanding hw inectius disease is spread generally, hw air-

crat are ventilated, and hw travel plays a rle in spread-ing disease. Ater that sessin, three panels leadingresearchers in their respective ields presented the sciencethat underlies ur current understanding hw path-gens may be transmitted in the specialized envirnment the aircrat cabin and in airprt acilities. The panelswere rganized by dierent appraches t research: casestudy investigatins, theretical mdeling, and benchscience experimental methds.

on Day 2, the cus shited t the practices and pli-cies that can be inrmed by science but t ten arent. Whether the task is applying pesticides t aircrat inan ert t cntrl vectr-brne diseases, develping air-line and airprt sanitatin measures, r impsing travelrestrictins t stem the spread a pandemic, mre sci-entiic evidence culd help t determine the eectiveness current practices, subjecting them t mre rigrusanalysis. In the cncluding sessin, members the audi-ence jined the sessin mderatrs in identiying areas inwhich mre research is needed t understand and miti-gate the transmissin disease in air travel.

over the curse the sympsium, there were manypprtunities r the exchange ideas, and the resultingdiscussins illustrated the beneits bringing tgetherresearchers rm dierent disciplines alng with ptentialcnsumers that research. The dierent perspectives andexpertise brught t bear n these issues identiied smenew paths t explre, as described in the tables prvidedin Sessin 6: Discussin Tpics r future Research.Perhaps as imprtant, the cnnectins rged ver a dayand a hal prmise t lead t uture cllabratins that


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will leverage available talent and resurces and imprvethe aviatin cmmunitys ability t gain a mre cmpletescientiic understanding the tpic.

The llwing papers are summaries the presen-tatins that were written and prvided by the invited

speakers t the sympsium. These papers have nt beenpeer reviewed and are intended nly as written summa-ries the research discussed in the presentatins dur-ing the sympsium. Nt all speakers prvided papers, snly thse received are included in this dcument.


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5

SESSIoN 1

Understanding How Disease Is Transmittedvia Air Travel

Jeanne Yu, Boeing Commercial Airplanes (Presenter)Ben S. Cper, United Kingdom Health Protection Agency (Presenter)

The AircrAfT cAbin environmenT

Jeanne Yu (Presenter)

Travel is all abut peple mving! The verall travelexperience includes many elements as a persn mvesrm ne lcatin t anther; we think abut the travelexperience in the cntext a dr-t-dr experi-ence. Travelers can experience many envirnments,mving rm grund transprt t an airprt t an air-plane t anther airprt and t mre grund transprtbere arriving at their inal destinatin. T urther urunderstanding disease transmissin at airprts andn aircrat, it is imprtant t recgnize that the airplanelight is just ne phase the verall travel experienceand that disease transmissin can ccur during all phases the dr-t-dr experience.

This white paper describes the aircrat cabin envirn-ment part the travel experience and hw airplane sys-tems wrk t prvide the air yu breathe in the aircratcabin envirnment. This paper als addresses items that

shuld be cnsidered r aircrat cleaning and disinec-tin i a signiicant disease transmissin event ccurs.

Airplanes typically ly at 36,000 t. T put this num-ber in cntext, Mt. Everest is abut 29,000 t high. Theenvirnment is extreme at 36,000 t:

Verycd:245f (243C) t 285f (265C); Verydry:esshan1%hdy; Verypressre;and Narayccrrnzne.

T sustain human lie, advanced envirnmental cn-trl systems (ECSs) are needed. They cntrl multipleimprtant unctins: cabin pressure, ventilatin, tem-perature, anti-icing, and ire and smke prtectin.

Aircrat ECS designs must meet fAA regulatryrequirements r saety and health, such as cabin pres-sure (8,000 t maximum) and ventilatin (0.55 lb/min/persn) and shuld nt exceed threshld maximumsr carbn mnxide, carbn dixide, and zne. Theaircrat cabin envirnment als strives t meet bjec-tives r cmrt based n industry standards: Tempera-ture (T) [65f t 85f, DT< 5f within a temperaturecntrl zne, SAE Aerspace Recmmended Practices(ARP) 85]=

Raesfpressrzan(cb.500f/n;descen.300 t/min, SAE ARP 1270);

Cabnarveces(


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lytic zne cnverter t remve the naturally ccurringzne at altitude. The air then travels t the air cn-ditining pack, which huses many cmpnents, suchas its wn cmpressr, turbine, and heat exchanger.once the air is cnditined t the apprpriate pressureand temperature, it ges t the mix manild where it

is mixed with highly iltered recirculated air in abut a50/50 rati. Being aircrat use high-eiciency particu-aear(HEPA)fershaneffcencyf99.97%aa particle size 0.3 micrmeter (m) in diameter. Infigure 1, the vertical axis shws ilter eiciency, andthe hrizntal axis shws particle size. HEPA iltersare 99%effcenveraparceszerannfr0.003 t 10 m, which encmpasses a single virus andbacteria.

Air rm the mix manild is supplied t the cabinthrugh the air distributin system via riser ducts t theverhead cabin regin and then thrugh dwner ductsint air supply nzzles that intrduce the air int the

aircrat cabin. The ECS is ully autmated and air distri-butin is set by aircrat design.

The ECS design gal r air supplied t the cabin is tgenerate a tw-dimensinal prile in a seat rw t mini-mize drats, temperature gradients, and dr migratin.Hwever, sme three-dimensinal aisle lw is inherentin the design and can be aected by mvements suchas galleys and ccupants mving in the aisle. Air lwscntinuusly int the cabin thrugh the air distributinsystem and leaves the cabin thrugh return air grilles thatrun the length the cabin n bth sides where the sidewall meets the lr. The Harvard 1997 transprtatinstudy and ther studies rm 1987 t 1998 have measuredthe micrbial level in dierent indr envirnments. Themeasured levels cntaminants in aircrat cabin air arelw cmpared with ther indr envirnments.

Air als lws cntinuusly ut the airplanethrugh the utlw valve. The utlw valve regu-lates utlw air and thus cabin pressure. The cabinpressure system cntrls the cabin pressure s that asthe airplane climbs t its maximum certiicatin alti-tude (40,000 t 45,000 t depending n airplane type),

the cabin pressure climbs t abut 8,000 t. Airplanesd nt usually ly at their maximum altitude; typi-cally, they ly at an altitude abut 36,000 t. Theresulting aircrat cabin pressure is arund 6,000 t,which is similar t being in a tall building in Denver,Clrad.

Mre detail and an animatin shwing hw the air isprvided t the cabin can be und at www.being.cm/cmmercial/cabinair/.

ECSs are ully autmated s that air lw rates t thecabin and t the light deck are set by aircrat design.flight decks n sme aircrat receive a 50/50 rati utside-t-recirculated air and sme receive all utside

air depending n the requirements and challenges the light deck air distributin design: electrnic cl-ing, high slar lading rm windshields, and higherpressure required in the event smke r ire.

Pressurized carg cmpartments can carry live ani-mals. Depending n the mdel, systems t heat ven-tilate and air-cnditin carg hlds are standard rptinal.

Being deers t apprpriate authrities r disin-ectin aircrat: the Centers r Disease Cntrl andPreventin (CDC), the U.S. Envirnmental PrtectinAgency, and the United Natins Wrld Health organi-zatin (WHo)

CDCrecendans frarnes: ar raveindustry;

Particle size in micrometers

Efficiency

(percent)

.01 .02 .03 .04 .05 .1.08 .2 .3 .4 .5 .6 .8 1.2 .3 .4 .5 .6 .8 1 2 3 4 5 6 8 10

Good

.003

99.97% efficiency

airplanes and critical

wards of hospitals **

94% efficiency

airplanes **80 85% efficiency

trains *

90 95% efficiency

hospitals *

60 65% efficiency

office buildings *

25 30% efficiency

office buildings *

* ASHRAE 5276 ** (IEST) Filter type B VERV17

Common type filters

not tested at smaller

particle size

Single virus

Tobacco smoke

Bacteria10

20

30

40

50

60

70

80

90

100

FIGURE 1 Comparative analysis of HEPA filters used in Boeing aircraft versus other applications.


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7uNDERStANDiNgHowDiSEASEiStRANSmittEDViAAiRtRAVEl

wHo:ebseanddcen,gdeHyeneand Sanitatin in Aviatin; and

inernanaArtransprAsscan:ebser Health & Saety r Passengers and Crew.

Being als supprts the llwing:

Researchandrknhheu.S.DeparenfAgriculture Animal and Plant Health Inspectin Servicet develp cnsistent guidelines with all riginal equip-ment manuacturers n inspecting, cleaning, and disin-ecting cntaminated aircrat; and

Arneevenrespnseharcrafceannanddisinectin guidelines, including an apprved material-cmpatible cleaners list.

Aircrat cleaning and disinectin require substancesthat will nt degrade aircrat materials. Being tests rmaterial cmpatibility but des nt test r substance

eicacy against disease agents. Disinectin materialsmanuacturers and gvernment agencies are respnsibler eicacy testing.

Being utlines requirements in the llwing:

Arcrafanenanceanashancdesafeyinstructins;

Bendcen,CeanninerrsfCer-cial Aircrat; and

Bendcen,EvaanfmanenanceMaterials.

Being research and cllabratin are nging withacademia and industry t urther ur understanding.We cntinue t wrk with the American Sciety Heating, Rerigerating and Air Cnditining Engineers(ASHRAE) and industry cllabratin t understandptential leverage pints in ASHRAEs strategic researchagenda being develped t address the rle heating,ventilatin, and air cnditining systems in the spread inectius disease.

We als are wrking tward maturing cmputatinalmdeling capabilities. With Purdue University, we aredevelping mdel characterizatin exhaled airlwrm varius mdes human respiratin, including

breathing, talking, and cughing. With the fAA AirlinerCabin Envirnment Research partners, we are studyingadditinal mdeling capabilities mving bdies in theaircrat cabin.

In summary, travel is a phenmenn peple mv-ing; the aircrat light is ne part a travelers dr-t-dr experience. Aircrat ECSs are ully autmatedand designed t meet unique requirements r passengersaety and cmrt. Aircrat disinectin must take mate-rial cmpatibility issues int cnsideratin. further inte-grated cllabrative research is needed.

humAn movemenT PATTernsAndThe sPreAdof infecTious diseAses

Ben S. Cooper (Presenter)

Patterns human mvement are undamental t the

persistence, spatial distributin, and dynamics humaninectius diseases. Research aimed at teasing apart thecmplex relatinship between human mvement pat-terns and inectius disease dynamics has intensiied inrecent years, particularly since the 20022003 epidemic crnavirus assciatin with severe acute respiratrysyndrme (SARS) and with cncerns abut a pssibleinluenza H5N1 pandemic. Hwever, the rts thisresearch g back much urther.

one way t appreciate the rle travel in the spread inectius disease is t cnsider what wuld happeni peple did nt mve amng cmmunities. Researchbased n mathematical mdels in the 1950s and 1960s

shws that withut such mvements immunizing inec-tins such as measles wuld nt be able t persist belw acritical ppulatin size: in the trughs between epidemicpeaks the numbers inected wuld all t zer, and nurther cases wuld ccur withut reintrductin rmutside the cmmunity (1, 2). fr measles, this criticalppulatin size was und t be abut 300,000. The the-ry predicts that island ppulatins belw this size wuldbe t small t sustain measles epidemics, and extendedperids with n measles cases (until reintrductin thevirus) wuld be likely. Abve this size, such stchasticadeuts are unlikely and ppulatins are large enught maintain a cntinual presence the pathgen. Lateranalysis measles data rm island ppulatins haslargely cnirmed these predictins rm mathematicalmdels (3).

Such cnsideratins apply nt nly t actual islandsbut als t inland islands: the cities, twns, and villageswhere we live. over the last 20 years theretical epide-milgists have extensively studied the spread diseasent just in a single ppulatin, but in metappulatins, rppulatins ppulatins cupled by travel links (4). Inthese cities and twns, ppulatin size plays a rle simi-lar t that bserved n islands, althugh cupling (duet human mvement) between ppulatin centers tends

t be strnger. Large ppulatins have a suicient inlux peple susceptible t inectin (either thrugh birth,as in the case measles, r thrugh lss immunity)t maintain the pathgen thrughut the year, typicallyresulting in a regular seasnal epidemic pattern (5). Thesmaller the ppulatin the mre likely stchastic adeut(epidemic extinctin) is t ccur. This situatin is due tthe relative size the stchastic luctuatins being largerr smaller ppulatins, and the chance the numberinected reaching zer and the epidemic ending is cr-respndingly greater. I these small ppulatins are nt


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linked by travel t ther ppulatin centers, transmis-sin in these settings will end. Cnversely, as cuplingvia transprt netwrks strengthens, epidemics becmemre synchrnized in the dierent ppulatin centers.Recent studies have shwn hw epidemic synchrnybetween dierent ppulatin centers can be explained

by human mvement patterns (6). At a mre undamen-tal level, many human pathgens (including measles andinluenza) are believed t have made the transitin rmtheir riginal animal hsts with the advent agricul-ture, when humans began t change rm living in smallrelatively islated grupings hunter gatherers t largercmmunities (7).

Air travel has an eect similar t that any thermeans human mvement: by cnnecting gegraphi-cally islated ppulatins, it allws disease t spreadbetween them and enables pathgens t persist by reduc-ing the chance lcal stchastic adeut. What makesair travel unique is its speed, which allws links between

ppulatins separated by large distances t be main-tained r pathgens with shrt generatin times. Usinginluenza (which has a generatin time abut 3 days)as an example, bere the advent the steamship, a pas-senger traveling rm Eurpe t America inected imme-diately bere embarkatin wuld have had virtually nchance transprting the virus between cntinents. HadClumbus been latently inected with inluenza when set-ting ut in 1492 r his 70-day Atlantic crssing, abut23 generatins inluenza transmissin n his carrackwuld have been required r the epidemic t spread tthe Americas. With a crew 70 men, this eat wuldhave been almst impssible. In cntrast, smallpx, witha generatin time 15 days, wuld have required nlyur r ive generatins transmissin n the ship tcrss cntinents, making intercntinental spread quiteeasible.

With the advent the steamer, Atlantic crssingtimes decreased t just a ew days (a trp ship crss-ing the Atlantic in 1918 tk abut 7 days) and nlyabut tw generatins transmissin were requiredt transmit inluenza between cntinents, ensuring ei-cient glbal disseminatin the 20th centurys irstpandemic. Air travel nw represents by ar the mstimprtant means r the rapid glbal disseminatin

human pathgenspartly because it is the predminantmeans transprting peple ver large distances butals because the shrt transit times make it an extremelyeicient means ensuring that even pathgens withvery shrt generatin times can be transprted ver verylarge distances. These cncerns led t wrk carried utat the United Kingdms Health Prtectin Agency tdetermine whether practical measures culd be taken treduce this internatinal spread in the event a majrpandemic with a virulent pathgen, particularly pan-demic inluenza.

first, we examined the ptential rle airprt entryscreening. Entry screening passengers with thermalimaging technlgy was used by a number cuntriesduring the SARS epidemic and als by sme during the2009 H1N1 pandemic. A very simple analysis was ablet shw that, even i the sensitivity and speciicity the

imaging technlgy used t detect symptmatic SARSr inluenza inectin were perect (which is very arrm being the case), the practice wuld have almst nvalue in prtecting ppulatins rm inluenza r SARS

(8). This cnclusin resulted rm an elementary cn-sideratin light times and incubatin perids r thepahens.ony1%6%fpassenersncba-ing SARS when barding a plane wuld be expected tdevelp symptms by the time they arrived in the UnitedKingdm (the higher percentage crrespnding t thelnger light times), s almst all cases arriving in theUnited Kingdm wuld be missed, even with perectscreening. fr inluenza, which has a shrter incubatin

perd,hecrrespndnraneas4%17%.thelarge number passengers inected with inluenza whileravendeanhaevenf17%cdbedeecedand islated, there wuld be n detectable impact n theepidemic in the destinatin cuntry.

Given that entry screening had been shwn nt t bean eective strategy, we cnsidered whether cancelinglights rm aected cities culd signiicantly alter thepattern glbal spread in an inluenza pandemic (9).Althugh we did nt expect light cancelatin t be ablet stp the glbal spread inluenza (the virus spreadarund the wrld quite eiciently in 1918 withut thehelp air travel), an imprtant questin was whetherglbal disseminatin culd be delayed suiciently tallw time r the develpment and prductin a vac-cine that wuld prtect against the pandemic virus (aprcess expected t take abut 6 mnths). T addressthis questin, we built n wrk started by Rvachev andclleagues wrking in the rmer Sviet Unin in the1960s(10). Rvachev had develped meta-ppulatinmdels t study the spatial disseminatin inluenza.originally, this wrk cnsidered ppulatin centerslinked by rail netwrks, but it was then extended byRvachev and Lngini t accunt r the glbal spread inluenza thrugh the internatinal aviatin netwrk

(11). our wn wrk urther extended these early ertsby recasting the deterministic glbal metappulatinmdels int a mre realistic stchastic ramewrk (whichis imprtant because at the beginning the epidemicin each city, the numbers inected are small, stchasticeects are dminant, and the times seeding new epi-demics in each city are expected t shw cnsiderablechance variatin). In cntrast t earlier wrk, we paidparticular attentin t a careul parameterizatin themdel by cmparing air travel and inluenza data rmthe 19681969 pandemic. This cmparisn was impr-


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9uNDERStANDiNgHowDiSEASEiStRANSmittEDViAAiRtRAVEl

tant r arriving at plausible values r the reprductin pandemic inluenza [bere undertaking this wrk,n reliable estimates had been published, but estimatespublished cncurrently with ur analysis yielded resultssimilar t thse btained with ur mdel(12)]. Thisprcess als inrmed the mdeling seasnal varia-

tin in the transmissin ptential and dierences in sea-snal variatin between trpical and temperate regins(all actrs that culd have imprtant eects n mdelpredictins). This wrk was the irst t evaluate explic-itly interventins that invlved altering the internatinalaviatin netwrk with the aim slwing the glbalspread pandemic inluenza (figure 2). We cnsideredtw pssible cntrl plicies: irst, we evaluated a pl-icy that canceled a prprtin,p, all air travel rmcuntries nce they had experienced a certain number,q, inluenza cases (where bthp and q were varied);secnd, we cnsidered plicies that did nt invlve can-celing lights but that reduced lcal transmissin rates

in aected cuntries. Such interventins culd includescial distancing measures (such as clsing schls andprmting hand hygiene) and antiviral treatment andprphylaxis (13, 14).

Cmparisn with the lcal epidemic peaks rm the19681969 pandemic shwed that the mdel, thugh

relatively simple, was able t capture the timing theglbal spread that pandemic with a high degree accuracy, althugh sme cities, such as Tky (where theepidemic peaked mre than a mnth later than predictedby the mdel), did shw departures rm the mdel thatwere nt cnsistent with chance eects. This analysis

als shwed that, with cntemprary air travel vlumes(2002 data), the timing the epidemic peaks in 1969wuld have been expected t ccur smewhat earlier, insme cases (r suthern hemisphere cities) shiting t anearlier inluenza epidemic seasn.

Results the interventin analysis shwed that restric-tins n air travel rm aected cities were likely t havelittle value in delaying epidemics unless almst all travelceased almst as sn as epidemics were detected in eachcy(Fre3).Frexape,f90%farravefraected cities were canceled ater the irst 100 inluenzacases, the arrival time inluenza in ther cities typicallywuld be delayed by nly 2 r 3 weeks. Thugh these

delays shwed sme sensitivity t the city where the pan-demic irst emerged and the timing this event, in ncase was the delay achieved clse t the 6 mnths neededdevepandprdceavaccne.Evenf99%fjr-neys rm aected cities culd have been stpped, weund the delays in the timing the epidemic peaks were

FIGURE 2 Global dissemination of a simulated influenza pandemic originating in Hong Kong at the begin-

ning of June to 105 cities, under the assumption that 99.9% of air travel from affected cities is canceled

after the first 100 cases in each affected city (and after 1,000 cases in Hong Kong). City shading indicates

the probability that each city has experienced a significant epidemic (based on 100 stochastic simulations).

Flights connecting cities are shown as blue lines when there is at least a 5% chance that they have not been

suspended due to travel restrictions. [Figure adapted from Cooper et al. (9).]


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nly 40 t 50 days, t shrt t have a signiicant practi-cal beneit. only i almst all travel rm aected citiesculd be stpped almst as sn as inluenza arrived wasthe interventin able t achieve delays likely t have asigniicant practical beneit in managing the pandemic.These results are smewhat cunterintuitive but can beseen t be a unctin the very shrt generatin time inluenza, which results in a rapid initial rate epidemicgrwth. I, at the beginning the epidemic each caseinected tw ther cases ater 3 days, we wuld expectabut 10 cases within 10 days the irst case and 100within 20 days. Thus, even i travel rm the city werereduced by a actr 100 rm Day 1, within abut3 weeks there wuld be the same number pepleinected with inluenza lying ut as there wuld have

been n Day 1 in the absence any interventin.In cntrast, it was und that interventins t reduce

lcal transmissin were likely t be mre eective atreducing the rate glbal spread and less vulnerablet implementatin delays. Nevertheless, under the mstplausible scenaris, achievable delays were und t besmall cmpared with the time needed t accumulate sub-stantial vaccine stcks.

other researchers, wrking with slightly dierentsets assumptins, have reached similar cnclusinsabut the limited rle air travel restrictins in cn-

trlling inluenza pandemics (i the natural histryparameters are similar t thse r inluenza strainswe have seen bere), and these results have directlyinrmed bth natinal and WHo recmmendatinsr pandemic respnses(1517). While these cnclu-sins have been challenged by a crrelatin undbetween a reductin in internatinal travel t andrm the United States ater the terrrist attacks in Sep-tember 2001 and the timing the seasnal inluenzapeak in the United States the llwing winter(18),the mdeling wrk shws that a direct causal relatin-ship between the relatively mdest reductins in airtravel that year and the inluenza epidemic timing isextremely unlikely(19). Ntably, the timing inlu-enza peaks rutinely shws cnsiderable year-t-year

variatin that cannt be explained by changes in thenumber internatinal air travelers.

An bvius limitatin mdeling studies evaluat-ing the rle the aviatin netwrk in the internatinalspread human pathgens is the ailure t accunt rther mdes travel. Hwever, excluding such travelrm glbal disseminatin mdels will bias mdel ind-ings in avr interventins that restrict air travel; byignring land and sea travel, the mdels will veresti-mate the impact air travel restrictins n epidemicspread. Thus, the inding that air travel restrictin

Percent reduction in air travel from affected cities

FIGURE 3 Impact of air travel restrictions on timing of epidemic peaks in

the 105 cities shown in Figure 2 during a simulated influenza pandemic.

Dots show timing of epidemic peaks in individual cities in the northern

temperate zone (red), the tropics (black), and the southern temperate zone

(green), where the area of each dot is proportional to the population size.

Results from three stochastic simulation runs are shown for reductions in

air travel between 0% (far left) and 99.9% (far right).


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12

SESSIoN 2

Practical Case-Response Approachesto Investigating the Spread of Diseasein Airports and on Aircraft

Dan fishbein, Centers for Disease Control and Prevention (Presenter)Hannah L. Kirking, Centers for Disease Control and Prevention

Jennier Crtes, Centers for Disease Control and PreventionSherry Burrer, Centers for Disease Control and Prevention and New Hampshire Department of

Health and Human ServicesArn Hall, Centers for Disease Control and PreventionNicle J. Chen, Centers for Disease Control and PreventionHarvey Lipman, Centers for Disease Control and PreventionCuri Kim, Centers for Disease Control and PreventionElizabeth R. Daly, New Hampshire Department of Health and Human ServicesItamar Grtt, Israel Ministry of Health (Presenter)Shepherd Ree SingerEmilia Anis

norovirus TrAnsmissionon AircrAfT

Dan Fishbein (Presenter), Hannah L. Kirking,Jennifer Cortes, Sherry Burrer, Aron Hall, NicoleJ. Cohen, Harvey Lipman, Curi Kim, and ElizabethR. Daly

An utbreak gastrenteritis amng members atur grup n an airplane resulted in an emergencydiversin. An investigatin was cnducted t determinethe etilgy the utbreak, assess whether transmis-sin ccurred nbard the airplane, and describe riskactrs r transmissin. Case patients, deined as pas-sengers r crew members with vmiting r diarrhea,

were asked t submit stl samples r nrvirus lab-raryesn.Ffeen(41%)rrpebersethe case deinitin, with mst illnesses ccurring bererdrnhefh.Seven(8%)passenersherent tur grup members met the case deinitin aterthe light. Nrvirus gengrup II was detected byreverse transcriptinplymerase chain reactin (PCR)in stls rm case patients in bth grups. Multivari-ate lgistic regressin analysis shwed that sitting inan aisle seat and sitting near any tur grup memberwere assciated with develping illness. Transmissin

nrvirus likely ccurred during the light, despiteits shrt duratin.

swine flu A/h1n1 TrAnsmissionviAThe AviATion secTor

Itamar Grotto (Presenter), Shepherd Roee Singer,and Emilia Anis

Pandemic inluenza A/H1N1 2009 is nw well estab-lished in all cuntries. While the nrthern hemisphereprepares t mitigate the eects an anticipated secndwave, it is inrmative t lk back at the early stages

the pandemic when cntainment was still a centralstrategy. This presentatin describes the case an Israelitraveler returning rm Central America with inluenzaA/H1N1 2009 and cnsiders the implicatins in-lighttransmissin.

The irst case inluenza A/H1N1 2009 was diag-nsed in Israel n April 24, 2009, in a 26-year-ld manwh returned that day rm Mexic. Israel was the sixthcuntry in the wrld t cnirm a case the disease.

The irst steps taken by the Israeli Ministry Healthwere deined as the cntainment phase. They included


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13PRACTICAL CASE-RESPoNSE APPRoACHES

mainly hspitalizatin and treating all patients with sel-tamivir, adding swine lu t the list ntiiable diseasesin Israel, and epidemilgic investigatin each case.The bjectives the investigatin were t identiy thepssible surce inectin as well as cntact tracing. Asr travelers, a special clinic was pened at Israels nly

internatinal airprt, and travelers rm Mexic wereexamined rutinely and asked t stay in vluntary quar-antine r 7 days and t g t an emergency rm i theydevelped ever. The Israeli Ministry Health recm-mended that peple pstpne travels t Mexic.

Case A

This case invlves a 22-year-ld Israeli wman whreturned rm Mexic thrugh Madrid (May 2, 2009).on a light rm Madrid t Tel Aviv, she had ever, shiv-ers, cugh, sre thrat, rhinrrhea, weakness, and head-

ache. Upn landing, she did nt reprt t the airprtclinic but went directly t an emergency rm, where shetested psitive r inluenza A/H1N1 2009 by using thePCR technique n her naspharyngeal specimen.

The Ministry Health cntrl measures included arecmmendatin t all travelers n Case As Madrid tTel Aviv light t stay at hme r 7 days (vluntaryquarantine) and t reprt t an emergency rm imme-diately i they had inluenza-like symptms and ever.The recmmendatin was publicized in the Israeli media(televisin, radi, and Internet).

Case B

This case invlves a 59-year-ld Israeli wman whbecame ill in Israel n May 4, 2009. She had ever,cugh, sneezing, and jint pain. She tested psitive rinluenza A/H1N1 2009 by PCR n May 5, 2009.

The epidemilgic investigatin disclsed that thewman had let Israel traveling t Guatemala viaMadrid n April 10, 2009. Ater turing Guatemala, shelew t Havana, Cuba, n April 22. Her return light tIsrael let Cuba n April 30 and she made a brie stp-ver in Madrid. Ater spending 9 h n May 1 in the city

Madrid and at varius lcatins in the Madrid air-prt, including 90 min in the prelight waiting area, shebarded a 23:30 light t Israel that arrived in Tel Avivn the mrning May 2. on the light rm Madrid tTel Aviv, she sat ne rw in rnt Case A.

Outcome

Bth wmen were hspitalized r 7 days with mild ill-ness, were treated with seltamivir, and ully recvered.

N additinal transmissin rm the tw patients wasidentiied (including Case As byriend, wh sat next ther during the light).

Discussion

Case A was symptmatic during the light and wastherere certainly inectius at that time. Given herclse prximity t Case B, and the lack any therpurprted surces cntagin, in-light transmissin isviewed as the mst likely cause the inectin spread-ing t Case B. Cntagin in Havana r Madrid r in thewaiting rms the respective airprts cannt be ruledut; hwever, n sustained cmmunity transmissinwas recrded in Cuba r Madrid at the time, and theepidemilgic investigatin did nt uncver any knwncntact with ptentially inectius individuals in thsesettings.

Aircrat manuacturers have made great advances incabin saety, and the risk transmissin inectiusdisease abard aircrat is very lw. Cabin air systemsndernarcrafprvdeab50%fhearfrutside; the remainder is rm recirculated air. Airlwis supplied at a rate 20 t 30 air changes per hur.High-eiciency particulate air ilters, similar t thseused in hspital perating theatres and intensive carens,capre>99%fbacera,fn,andvrses( 1,2). Hwever, n ventilatin can cmpletely prevent air-brne transmissin inectius particles, particularlyrm passengers sitting in clse prximity. Thus, despitethe eectiveness mdern iltratin systems, airlinepassengers remain at sme risk direct inectin in thecabin as well as in prelight waiting areas and n shuttlebuses.

Thugh rare, tuberculsis transmissin has beendcumented (3, 4) and remains a lng-standing cn-cern amng public health icials. Mre recently, ivelights were assciated with prbable in-light transmis-sin severe acute respiratry syndrme, aecting 37peple (5, 6). In-light transmissin measles has beenreprted (7), as has inluenza (810). Hwever, Han andclleagues demnstrated a lack airbrne transmissinduring an utbreak inluenza A/H1N1 2009 amng

tur grup members in China (11).

Conclusion

Airlines have undertaken a variety measures ver theyears t minimize the risk in-light transmissin inectius agents. These measures cannt eliminate thatrisk entirely. Passengers shuld cnsult travel experts,ensure that they have cmpleted recmmended pre-travel immunizatins, and inquire abut current health


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guidelines r travelers. Peple wh are unwell shuldalways cnsult a dctr bere traveling. There is aneed r internatinal guidelines t deal with medicaland ethical issues related t pretravel screening andrestrictins.

References

Cabin Air QualityRisk of Contagious Viruses1. . Inter-

natinal Air Transprt Assciatin, Mntreal, Quebec,

Canada. www.iata.rg/NR/rdnlyres/E81DEB5C-f3C5-

4Cf7-8208-9E96123D4781/0/cabin_air_quality.pd.

International Travel and Health2. . Wrld Health organiza-

tin, Geneva, Switzerland, 2009. www.wh.int/ith/chap

ters/en/index.html.

Kenyn,t.A.,S.E.Vaay,w.w.ihe,i.m.onra,3.

and K. G. Castr. Transmissin Multidrug Resistant

Mycobacterium tuberculosis During a Lng Airplane

flight. New England Journal of Medicine,V.334,1996,

pp. 933938.

Expsure Passengers and flight Crew t4. Mycobacte-

rium tuberculosis n Cmmercial Aircrat, 19921995.

Morbidity and Mortality Weekly Report,V.44,1995,

pp. 13740.

olsen, J. A., H.-L. Chang, T. Y.-Y. Cheung, A. f.-U. Tang,5.

T. L. fisk, S. P.-L. oi, H.-W. Ku, D. D.-S. Jiang, K.-T.

Chen, J. Land, K.-H. Hsu, T.-J. Chen, and S. f. Dwell.

Transmissin the Severe Acute Respiratry Syndrme

n Aircrat. New England Journal of Medicine,V.349,

2003, pp. 24162422.

V,t.m.,m.A.gerra,E.w.Fa,t.g.Ksazek,S.6.

A. Lwther, and P. M. Arguin. Risk Severe Acute Respi-

ratry SyndrmeAssciated Crnavirus Transmissin

Abard Cmmercial Aircrat.Journal of Travel Medicine,V.13,2006,pp.268272.

Slater, P. E., E. Anis, and A. Bashary. An outbreak 7.

Measles Assciated with a New YrkTel Aviv light.

Travel Medicine International,V.13,1995,pp.9295.

Marsden, A. G. Inluenza outbreak Related t Air Travel.8.

Medical Journal of Australia,V.179,2003,pp.172

173.

Mser, M. R., T. R. Bender, H. S. Marglis, G. R. Nble,9.

A. P. Kendal, and D. G. Ritter. An outbreak Inluenza

Abard a Cmmercial Airline. American Journal of Epi-

demiology,V.110,1979,pp.16.

Klntz, K. C., N. A. Hynes, R. A. Gunn, M. H. Wilder, M.10.

W. Harmn, and A. P. Kendal. An outbreak Inluenza

A/Taiwan/1/86 Inectins at a Naval Base and Its Asscia-

tin with Airplane Travel. American Journal of Epidemi-

ology,V.129,1989,pp.341348.

Han, K., X. Zhu, f. He, L. Liu, L. Zhang, H. Ma, X. Tang,11.

T. Huang, G. Zeng, and B.-P. Zhu. Lack Airbrne

Transmissin During outbreak Pandemic (H1N1)

2009 Amng Tur Grup Members, China, June 2009.

Emerging Infectious Diseases,V.15,N.10,2009.


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15

SESSIoN 3

Theoretical Modeling Approaches toInvestigating the Spread of Disease inAirports and on Aircraft

James S. Bennett, National Institute of Occupational Safety and Health (Presenter)Jennier L. Tpmiller, National Institute of Occupational Safety and HealthYuanhui Zhang, University of Illinois at UrbanaChampaignWatts L. Dietrich, National Institute of Occupational Safety and HealthQingyan (Yan) Chen, Purdue University (Presenter)Sagnik MazumdarMichael W. PlesniakStephane PussuPaul E. SjkaTengei ZhangZha ZhangByrn Jnes, Kansas State University (Presenter)

Jan B. Rse, Michigan State University (Presenter)Mark H. Weir, Michigan State University

summArizing

exPosure

PATTerns

on

commerciAl AircrAfT

James S. Bennett (Presenter), Jennifer L. Topmiller,Yuanhui Zhang, and Watts L. Dietrich

Natinal Institute occupatinal Saety and Health(NIoSH) research int the aircrat cabin envirnmentbegan with a request rm the fAA t study healtheects amng aircrat crew. A review previus studiesshwed that emale light attendants may be at increasedrisk adverse reprductive utcmes (1). Expsureassessments and epidemilgic studies in the areas

radiatin and cabin air-quality studies llwed (13).Diiculties in cnducting studies in the passenger air-crat cabin envirnment during light led t the decisinthat urther wrk be dne using realistic cabin mck-upsand cmputatinal luid dynamics (CfD) t understandthe behavir any air cntaminants present.

The aircrat cabin envirnment is maintained duringlight by the envirnmental cntrl system (ECS). It isn small accmplishment t prvide a sae atmsphereat cruise altituder example, 35,000 t. In additint pressurizatin, the ECS prvides clean utside air t

the cabin, which has a high-ccupancy density cmparedwith, r example, ice buildings and classrms. Inneerarcraf,ab50%fhearsppedhecabin has been recirculated and passed thrugh a high-eiciency particulate air (HEPA) ilter, with the remain-ing supply vlume cming rm the utside. The ECS isdesigned, as shwn in figure 1, t use the length thecabin as a plenum, s that air is supplied and exhaustedat a velcity that is cnstant with respect t the length the plane. Als, the directin lw ut the supplyand int the exhaust slts is in the seat rw directin,perpendicular t the aisle. The mvement air betweenseat rws is thus minimized in the ECS design cncept.

While the airlw cming rm the supply utlet canbe cnsidered tw dimensinal, the lw in the penspace the cabin is reer and smewhat turbulent,insar as it is characterized by luctuatins in velcity(speed and directin). A lw can be decnstructed intits Reynlds averaged velcity cmpnents:

(1)

where each instantaneus cmpnent, U(t), is the sum a time average and a luctuatin with a time average

U t U u t ( ) ( )= +


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zer (4). Air cntaminants, such as small drplets rman exhaled breath r a cugh, are transprted by theluctuatins, even thugh the average the luctuatinsis zer. The ECS, then, creates tw cmpeting prcesses,ne that is intended and anther that is perhaps imps-sible t avid: (a) remval ptentially cntaminatedcabin air int the exhaust and replacement with cleanair, and (b) mvement cntaminants within cabin airby lw luctuatins. fluctuatins are present, even in

the hypthetical absence bstructins, mving bdies,and thermal plumes.

Airlw and cntaminant transprt research has takenplace in cllabratin with many expert partners (figure2). The data generated by cllabratins have been lwields measured by experiments with realistic mck-upsr calculated by using CfD. The lw ields have cn-sisted velcity, turbulence parameters, and either gasr aersl cntaminant cncentratin.

Airflow is a criticalfactor that influences

air quality, diseasetransmission, and

airbornecontamination.

FIGURE 1 Aircraft environmental control system design concept attempts to

minimize the movement of air between seat rows.

FIGURE 2 Aircraft Air Quality Partners: Sandia National Labs (SNL);

University of Illinois (UI); Purdue University; Boeing Commercial Airplanes;

Federal Aviation Administration (FAA); Kansas State University (KSU);

University of Tennessee (UT); and American Society of Heating, Refrigerating,

and Air Conditioning Engineers (ASHRAE).


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17THEoRETICAL MoDELING APPRoACHES

CfD simulatins tk place in cllabratin with Be-ing, Inc. (5, 6).At the University Illinis, experimentsin a ive-rw B767 mck-up delivered vlumetric particletracking velcimetry images cabin lw seeded withhelium bubbles and tracer gas (carbn dixide) cncen-tratin ields generated by three surce lcatins and three

ventilatin rates (79)., Sandia Natinal Labs prvided amassively parallel cmputing platrm r the BeingNIoSH CfD simulatins, including large eddy simulatin.figure 3 prvides snapshts the Illinis, Being, andSandia erts. Sandia als prvided advice and evaluatin the cabin airlw research and suggested that tracer gasexperiments wuld be useul. Data r a real Being 747,including velcity and turbulence ields, were gatheredby the University Tennessee, at the fAA Aer-medicalResearch Institute. They als created detailed CfD simu-latins the luctuating cabin lw. NIoSH prvided areview the University Tennessee reprt t the fAA.

Kansas State University (KSU) was a pineer in aircrat

cabin research. KSU, alng with Purdue University, hascntinued t advance the ield in part thrugh the fAACenter--Excellence r Aircrat Cabin Envirnmental

(a)

(c) (d)

(b)

ISOsurface for 1 measles/m^3 @ t - 1 sec

FIGURE 3 (a) Boeing 767 mock-up at the University of Illinois; (b) large eddy simulation CFD

model of a velocity field conducted by Boeing, NIOSH, and Sandia; (c) unstructured mesh for a

Reynolds-Averaged NavierStokes (RANS) CFD model of a Boeing 767, conducted by Boeing;

and (d) time evolution of an aerosol cloud from a point source, using a RANS CFD model of a

Boeing 767.

Research. KSU has a Being 767 mck-up with manyseat rws and Purdue has dne large-scale CfD simula-tins, including the wake eect a mving bdy. Smecllabratrs, including KSU and Purdue, and NIoSHresearchers were invlved in research prjects spnsredby the American Sciety Heating, Rerigerating and

Air-Cnditining Engineers (ASHRAE) and develpment an ASHRAE standard r aircrat cabin ventilatin.

Much wrk has been dne, yet the rle ventila-tin in cntrlling disease transmissin in aircrat cab-ins remains paque. There is cnsensus that the issue iscmplex because the many variables invlved. figure4 diagrams pssible mdes transmissin and variablesdiscussed during the sympsium.

In an ert t pull immediately useul inrmatinrm the detailed, high-quality studies dne t date, asimple mdel and a mdeling ramewrk are presentedhere. The general aircrat-cabin air-cntaminant transprteect (GAATE) mdel seeks t build expsurespatial

relatinships between cntaminant surces and recep-trs, quantiy the uncertainty, and prvide a platrm rincrprating uture studies. T put this mdel in cntext,


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the many variables presented in figure 4, the GAATEmdel invlves nly the three variables indicated by bluebxes. Thus, it prvides expsure inrmatin.

Knwledge the inectin risk t light crews andpassengers is needed t rm a cherent respnse t anunlding epidemic. An essential part inectin riskis expsure, and expsure may have an airbrne cm-pnent. The inectin light attendants n Air Chinaand Singapre Airlines with severe acute respiratry syn-drme (SARS) in 2003 is evidence the risk aced bythese wrkers, wh in sme situatins ind themselvesin the rle irst respnders. Mrever, the Asscia-tin flight Attendants asked the fAA r prtectin

rm SARS. The gal the GAATE mdel, then, is tprvide useul inrmatin t authrities r addressingexpsure incidents invlving SARS, avian lu, H1N1,and ther ptentially lethal agents and t prvide guid-ance t emergency respnse persnnel.

Methods

The GAATE mdel can be thught as a metamdelthat is, a mdel built rm ther mdels r studies. As

such, the irst step is slicitatin cntaminant trans-prt data r aircrat cabin envirnments rm researchpartners. These data sets must be placed n a cmmnting and nrmalized t remve meaningless surces variability. The large metadata set thus rmed is ame-nable t statistical analysis. The mdel chsen currentlyis regressin analysis, where the dependent variable iscncentratin gradient and the independent variable(s)describes lcatin within the cabin.

Varabeshasbenrazedareassessnrate the surce and air change rate the cabin. Putanther way, the rati these tw terms is held cnstant.In the current study, this nrmalizatin was achieved by

dividing the measured cncentratin at a given seat lca-tin by a reerence cncentratin

(2)

where CAVE

is the spatial average cncentratin verall measurement lcatins and C

Sis the cncentratin

measured nearest the surce. As the cabin air is nt wellmixed, the inclusin C

Shelps t make C

REfmre rep-

resentative. The cncentratin variable used in the anal-

Hostinfectivity

Largeparticle

Aerosol Contact

FomiteNear airspace

Far airspace

Viability

Behavior

Dose

Susceptibility

Disease

FIGURE 4 Aircraft cabin air quality research (blue high-

light) in the context of disease pathways discussed at the

symposium.

CC CS

REfAVE

=+

2


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yses is then the rati the measured cncentratin t thereerence cncentratin, C

MEAS/C

REf,

(3)

Thus ar, the GAATE mdel has been applied t adata set rm the University Illinis. Measurements carbn dixide as a tracer gas were taken in a ive-rwBeing 767 mck-up. Data were generated ver threeair change rates and three surce lcatins, in which themeasured utcme was the cncentratin at each 35seat lcatins. The cncentratins measured at 2-s inter-vals were time-averaged ver 1,000 s ater the systemhad stabilized. N exhaust air was recirculated, and thegaspers were . These data sets relect an isthermalscenari. A CfD simulatin was perrmed r the sameset cnditins. These results were nt included in theGAATE mdel, because they did nt it the same regres-

sin equatin as the experiments, which were cnsideredmre reliable. In principle, data generated by CfD arereasnable candidates.

The regressin equatin had the llwing generalrm:

(4)

where

Yi

= bserved quantity (cntaminant rpathgen cncentratin);

b0

and b1

= y intercept and slpe regressin line,respectively;

Xi

= independent randm variable; ande

i= residual r the ith bservatin.

CC

C=

MEAS

REf

FIGURE 5 Time slice of contaminant dispersion, source location, 2B: (a) measured and (b) simulated.

(a) (b)

Varsfncnafrserechsenaepaft the data by inspecting a plt cncentratin versusdistance rm the surce r all three surce lcatins.Distinguishing between the seat letter crdinate direc-tin and the rw number crdinate directin did ntprvide a better it than using the simple variable dis-

tance, r.

Results

figure 5 shws the cntaminant dispersin pattern attime Tr bth the experiment and the simulatin. Thecncentratin pattern in the experiment resembles is-trpic diusin, while in the simulatin the pattern isrmed mre by directinal cnvectin.

The speciic rm Equatin 4 that prvided thebest it t the experimental tracer gas data was

(5)

The regressin line shwn in figure 6 has an intercept,b

0, 1.055 and a slpe, b

1, 0.493. With an R2 value

f0.476,canbesadha47.6%fhevarabyin the cncentratin data is explained by the regressinmdel. While the regressin passed the nrmality test(P = .141), it ailed the cnstant variance test, which isnt surprising given that the cncentratin is mre vari-able near the surce.

theanaysscarresannceranyf95%.thsuncertainty applies in tw dierent ways. b

0and b

1bth

have95%cnfdencenervas(0.9906#b0# 1.1194

and 0.4204 #b1# 0.5660), and these intervals are nt

independent, which is why the blue cnidence bands in


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figure 6 are curved. The red bands indicate uncertaintyin predictin the relatin between C and ln(1/r) r anymember the ppulatin r values. Put anther way,the cnidence band addresses the questin whetherthis regressin line is the best ne pssible, while the pre-dictin band addresses the value this regressin line asa predictive mdel.

Because the cncentratin variability is greater nearerthe surce, a tw-segment linear regressin (figure 7)was als dne t see i the it culd be imprved. Bththe slpes the tw lines and the breakpint betweenthem, r = 2.48 m, were determined in the regressin.

Thus, a physicalitythe near-znear-zne distinctinwas identiied by the statistical analysis. The reedm tadjust r this phenmenn increased the R2 value rm0.476 t 0.502, nly a small imprvement. Here als, theanalysis passed the nrmality test (P = .375) but ailedthe cnstant variance test. The near surce behavir isperhaps nt well described by any kind mdel basedn the istrpic assumptin. Hwever, perrming theregressin n nly the ar-ield data >2.48 m rm thesurceactually lwered the R2 value. The beneit mre data pints was apparently greater than the cst the increased variance.

ln (1/r)2 1 0 1

Concentration

0.5

0.0

0.5

1.0

1.5

2.0

2.5

Regression lineTracer gas data95% confidence band95% prediction band

e2 e 1 1/er

(meters)

FIGURE 6 Regression analysis of (source distance, concentration)

data pairs, with 95% confidence and prediction bands.

Radial distance

(meters)

0 1 2 3 4 5

0.0

0.5

1.0

1.5

2.0

Regression lineTracer gas data

Nearfield

Farfield

2.48

Concentration

FIGURE 7 Two-segment regression, with breakpoint between near

and far fields.


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emergence (www.wh.int/csr/disease/swinelu/updates/en/index.html). These cases illustrate the dramatic rle glbalizatin and air travel in the disseminatin an emerging inectius disease. other cases airbrneinectius diseases transmitted in airliners in recent yearsinclude tuberculsis, inluenza, measles, and mumps.

CfD is a very attractive tl t study the transmissin airbrne cntaminants in an airliner cabin as it is inex-pensive and lexible in changing thermluid cnditinsinside the cabins cmpared with experimental measure-ments. The results presented here illustrate the ptential using CfD in mdeling gaseus and particulate cn-taminant transprt inside airliner cabins. CfD was alsused t mdel the SARS transmissin case in Air Chinaflight 112 rm Hng Kng t Beijing in 2003 wherea cntagius passenger inected sme 20 ellw passen-gers, as shwn in figure 9(11). Sme seated as ar asseven rws rm the cntagius passenger were inected.The mvement passengers and crew members may

play a rle in transmissin.

CFD Modeling

The cmmercial CfD stware fluent 6.2. (www.lu-ent.cm) was used r the studies. The CfD mdel useda secnd-rder upwind scheme and the SIMPLE alg-rithm. The renrmalizatin grup k-e mdel was used tsimulate the turbulent lw inside the cabin mck-ups.

Tw dierent cabin gemetries were used in thisinvestigatin t understand the eects mving crewand passengers n cntaminant transmissin inside air-liner cabins. Initial CfD studies were dne with a sectin a ur-rw, twin-aisle cabin mdel as shwn in figure10a. The cabin sectin had 28 seats in ur rws, repre-senting a sectin ecnmy-class cabin. The cabin wasully ccupied. The air entered thrugh linear diusersat the ceiling level and was exhausted thrugh utletsplaced in the side walls clse t the lr. The airlw

rate in the cabin was 10 L/s per passenger. Bx-shapedmanikins were used t represent passengers. A mvingpersn was mdeled as a rectangular bx height 1.7 mand was assumed t mve alng the aisle. T investigatethe eects a mving persn n cntaminant trans-prt in the cabin, tw scenaris were cnsidered: ne in

which the persn walked cntinuusly rm the rnt tthe rear end the cabin withut stpping and the therwith intermittent stps 5 s at each rw.

A secnd case used a 15-rw, single-aisle cabin rstudying SARS transmissin in the light rm HngKng t Beijing in 2003 r Rw 4 t 18 as shwn infigure 9. figure 10b shws nly ne rw the cabinand the remaining rws are identical. The air enteredthe cabin thrugh ur linear diusers: tw placed atthe ceiling abve the aisle injected air dwnward andthe ther tw at the side walls lcated belw the stragebins injected air inward t the aisle. The ttal supply air-lw rate 10 L/s per passenger was distributed equally

amng the ur inlets. The air was exhausted thrughutlets n the side walls clse t the lr. The cnta-gius passenger sat in Rw 11 the 15-rw cabin. Twcntaminant release scenaris were cnsidered: ne witha pulsed release r 30 s and the ther with a cntinuusrelease. The bdy mved alng the aisle rm the rearend the cabin and stpped seven rws in rnt thecntagius passenger.

The mvement was simulated by using a cmbinatin static and dynamic meshing schemes. fr example,the cmputatinal dmain the ur-rw twin-aisle air-liner cabin was mdeled using tw separate gemetries:a sectin r the aisle with the mving bdy and thether sectin r the rest the cabin, as shwn in figure11. The meshes r the irst sectin were dynamic; thereannesheseresac.Hence,ny3.7%fhettal meshes inside the dmain were dynamic, which canreduce the cmputing csts r remeshing. The mve-ment inside the 15-rw, single-aisle mdel r the SARStransmissin case was mdeled similarly.

FIGURE 9 A contagious passenger with SARS virus infected some 20 passengers on the flight from Hong Kong to

Beijing in 2003 (11).


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CFD Modeling Results

figure 12 shws the airlw pattern and airbrne cn-taminant cncentratin at 1 m abve the cabin lr asthe bdy mved cntinuusly rm the rnt t the rearend the cabin. The results were r a cntaminantreleased rm Passenger 2A seated in the right windwseat n the secnd rw. The results at t= 0 s shw theinitial steady-state air velcity and cntaminant distribu-tin bere the bdy started mving. The airlw patternsillustrate that the lw disturbance created by the mv-ing persn was rather lcal. The impact mvement nairlw n the let hal the cabin was minimal. Themving bdy created a lw pressure zne behind it andhence air was induced rm the sides. The mving bdyals pushed the air at its rnt. Hence, the bdy culdcarry the cntaminant behind t the rear the cabin.

figure 13 shws the eect an intermittently mv-ing bdy r the same cntaminant surce. The bdystpped r 5 s in each rwthat is, it stpped rm0.7 t 5.7 s in Rw 2 and rm 6.6 t 11.6 s in Rw 3,which simulated a mving crew member wh stppedat each rw t prvide service. The airlw pattern and

cntaminant cncentratin at 1 m abve the cabin lr

are shwn at t= 0.7, 5.7, 6.6, and 11.6 s in the igure.The area near the cntaminant surce became heavilycntaminated when the mving persn stpped at Rw2, because it brke the near symmetric lw vrtices atthe crss sectin that aided in rmatin the high-cn-taminant-cncentratin zne.

The intermittently mving bdy als enhanced thecntaminant cncentratin level t passengers sittingnear the aisle when it stpped at Rw 3. When themving persn stpped, the highly cntaminated air itcarried at its back was pushed t the sides. Hence, thecntaminant cncentratin can be higher than that witha cntinuusly mving persn.

The results rm the ur-rw, twin-aisle cabin shwa signiicant impact a mving persn n cntaminanttransprt. Thus, this investigatin used the methd tstudy why the SARS virus culd be transprted as ar asseven rws away in the Air China 117 light rm HngKng t Beijing in 2003. figure 14 shws the cntami-nant distributin at the breathing level in the Air Chinacabin r a pulse cntaminant release rm the inectedpassenger, such as a cugh. The high-cncentratin zne

(a) (b)

FIGURE 10 Two different cabins used in the study: (a) section of four-row, twin-aisle cabin,

and (b) one-row model of the 15-row, single-aisle cabin.

FIGURE 11 Mesh layout of the four-row, twin-aisle cabin section.


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was initially within tw rws the inected passenger,which appears t be in gd agreement with cmmn

sense because the lw in the lngitudinal directinshuld be small. When a persn mved alng the aisle,the wake culd carry the cntaminant t seven rws inrnt the inected passenger, where the bdy stppedits mvement. The cntaminant carried in the wake wasthen distributed t the passengers seated near the aisle.A similar phenmenn was bserved r the scenariwith a cntinuus cntaminant release. The CfD resultsshwed that bdy mvement may have caused the trans-missin SARS pathgen rm the inected passengert ellw passengers seated as ar as seven rws away

n the Air China light rm Hng Kng t Beijing in2003.

Thus, CfD mdeling appears t be a pwerul andeective tl r predicting airbrne cntaminant trans-prt in airliner cabins. Because CfD mdels use apprxi-matins, the predictins shuld always be validated withhigh-quality experimental data.

CFD Model Validation

It is expensive and time-cnsuming t cnduct experi-mental measurements airbrne cntaminant cncen-

t = 0 s

t = 0.7 s

t = 1.6 s

t = 2.5 s

FIGURE 12 Velocity distribution and contaminant transport trends from the move-

ment of a person in the four-row, twin-aisle cabin mock-up.


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tratins in a ull-scale airliner cabin with passengers.Hence, this study used a 1/10th-scaled, water-based

experimental test acility cnsisting an upside-dwncabin mckup as shwn in figure 15a. The cabin wasmade by a transparent semicircular pipe 45 cm in diam-eter and 2.44 m lng. The mck-up, ully submerged ina water tank, was equivalent t a cabin with 28 rws ecnmy-class seats. The interir the mdeled cabinwas empty s n seats and passengers were mdeled.T simulate the ECS, water was injected thrugh anverhead duct the inlet diuser assembly. T achievea unirm inlw in the cabin, the water entered a set-tling chamber thrugh 23 pipe ittings and was then

supplied t the cabin thrugh 48 elngated peningscut alng the length, where a T-shaped diuser diverted

the luid laterally t bth sides the cabin crss sec-tin. Water was extracted rm tw utlets lcatednear the side walls the cabin at lr level. T simu-late a mving persn, an autmated mechanism placedabve the experimental acility traversed the mvingbdy (0.02 m thick 0.05 m wide 3 0.17 m tall) alngthe lngitudinal directin the cabin. Particle imagevecery(PiV)assedeasrehevecyds-tributin inside the water tank. The camera and laserwere psitined t capture crss-sectinal and lngi-tudinal lw images. The crrespnding CfD mdel

t = 0.7 s

t = 5.7 s

t = 6.6 s

t = 11.6 s

FIGURE 13 Velocity distribution and contaminant transport trends from an intermit-

tently moving person in the four-row, twin-aisle cabin mock-up.


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was built r the water mdel as shwn in figure 15b.The mdel was cnstructed t simulate as clse t theexperimental mdel as pssible. Thus, the inlet started

at the water supplying pipe t eliminate the diicultiesin speciying inlet cnditins in the cabin.

figure 16a shws the measured mean lw ields atframes 4 and 7, which were acquired when the bdymved 8.25 and 15.5 cm, respectively, past the lasersheet. A strng dwnwash in the wake the mvingbdy was bserved, which is prduced by the tw sym-metric eddies arund the tp crners. As the tw eddiesapprached the cabin lr, they spread t the sides anddissipated. The disturbance created by the mving bdydiminished very rapidly ater this prcess. figure 16b

shws the crrespnding cmputed lw ields. Side-by-side cmparisn indicates that the CfD mdel wasable t qualitatively predict the develpment the tw

eddies. The predicted cre size, lw pattern, and struc-ture are in reasnable agreement with the experimentalvalues, althugh nticeable dierences exist with respectt vrtex aspect rati.

figure 17a shws nly a small area the measuredfdeheedaeszecapredbyhePiV.The cmparisn between the measured and cmputedvelcity in the midsectin alng the lngitudinal direc-tin in figure 17 shws reasnable agreement betweenthe tw results. flw recirculatin due t lw separa-tin culd be bserved rm the results. Hwever, the

t = 30 s

t = 32.6 s

t = 35.2 s

t = 36 s

Infected passenger

FIGURE 14 Contaminant transport process from a persons movement along the

aisle with a pulse release of contaminant from the infected passenger in the single-aisle

SARS transmission cabin mock-up.


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lngitudinal lw cmputed behind the mving bdy ismuch strnger than that measured, with verpredictin lngitudinal mmentum transer. This result maybe due t less mmentum transer in lateral directins,resulting in vertically elngated eddy rings in the cabincrss sectin. overall, the CfD mdel can capture theundamental lw mechanisms und in such a simu-lated cabin.

Conclusions

CfD, a pwerul tl r predicting the transprt airbrne cntaminants in airliner cabins, shws that themvement a persn culd have a signiicant eect. Themvement a persn may have resulted in the spread SARS virus t passengers seated ar rm the cntagiuspassenger n Air China flight 112 rm Hng Kng t

(a) (b)

Outlets

T-shapedslots

Traversemechanism

Body

Cabin

Overhead ductof inlet diffuser

Inletlocation

Cabin

Body

FIGURE 15 (a) Small-scale experimental test facility of the cabin mock-up, and (b) CFD

model of the test facility.

Frame 4: Measured Frame 4: Computed

Frame 7: Measured

(a)

Frame 7: Computed

(b)

FIGURE 16 (a) Measured and (b) computed mean flow fields at Frames 4 and 7 from

movement inside the small-scale cabin mock-up.


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Description of Experiments

The irst set experiments used carbn dixide (Co2)

tracer gas t measure cntaminant dispersin. The Co2tracer gas was mixed with helium t generate a mix-ture with a mlecular weight equal t that air. Thetracer gas was at the same temperature as the cabin airwhen injected. As Co

2is much denser than air, negative

plume buyancy gives distrted results i these measuresare nt taken t ensure neutral buyancy. Calculatinsand experimental results shw that turbulent diusinis several rders magnitude greater than mleculardiusin, s the mlecular diusin is expected t be anegligible cnsideratin in these experiments. The tracergas was injected cntinuusly at lw velcity thrugha vertical tube in the center the right r let aisle ata height 1.2 m (48 in.) as shwn in figure 18. Theair was sampled thrugh a seven-prt sample tree thatcan be seen near the rnt the cabin in figure 18. Allmeasurements reprted are at a height 1.5 m (60 in.).Air was sampled rm ne prt at a time r a minimum 30 min bere prceeding t the next prt. once allprts were sampled, the entire tree was mved t thenext lcatin.

The secnd set measurements used talcum pwderas a representative slid particle cntaminant. The peaknumber density r this pwder ccurred at apprxi-mately 1.5 m and the data presented are r the ttal

particle numbers between 0.5 and 5.0 m. Injecting slidparticles in a cntrlled manner withut disrupting thecabin airlw is diicult. T accmplish this eat, a pugeneratr was develped. A measured amunt tal-cum pwder was placed in a small cup. A small cp-per tube cnnected t a surce pressurized air wasdirected dwnward at the cup. The airlw was turnedn and quickly with a slenid valve t generate ashrt but intense pu air that aerslized the talcumpwder withut generating a large airlw. figure 19shws seven the devices being tested simultaneusly.

fr the experiments, the injectin ccurred in Rw 2 andwas dne simultaneusly at all seven seats in the rw.Particle cncentratin was measured with a TSI 3321

aerdynamic particle sizer (APS) with the instrumentplaced in the seat as shwn in figure 20. A straight tubewas used t cllect air samples at a height 1.18 m(46.5 in.). Bere the talcum pwder was injected, theAPSs were mnitred t veriy that the air was ree particles and the cunt rate was near zer. Data werethen cllected r 15 min ater injectin, at which timethe cunts had returned t near zer. The data reprtedhere are the 15-min sums.

The third set measurements used aerslized Lac-tococcus lactis as a surrgate bacteria. The bacteria wereaerslized by using a handheld mister (figure 21a) andthe mist was released arund head height the seatedpassengers. Cllectin plates were lcated n tp the seat backs as shwn in figure 21b. The cllectinplates were pened r 30 min r cllectin ater the L.lactis was released. Additinally, air samples were takenat selected lcatins. The data presented here includenly the cllectin plates. Cntrls were als run withn bacteria aerslized t veriy that near-zer cunts

FIGURE 18 Aircraft cabin mock-up. FIGURE 19 Solid particle inject

research on the transmission of disease in airports and on aircraft

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