and The Spread of Airborne Infectious Disease Indoor · in the spread of infectious disease; ... The size and duration of air-carriage of respiratory droplets and droplet-nuclei

The Spread of Airborne Infectious Disease

Christopher Chao, PhD Department of Mechanical Engineering

The Hong Kong University of Science and Technology, China

Workplace and Indoor Aerosols 2012

http://www.eat.lth.se/aerosols2012

Motivation of the Work

AMOY garden was the most seriously

affected location during the 2003 SARS

outbreak, with over 300 infected people.

(Li et al. 2004)

A TB outbreak case in an economy cabin on a flight

from Chicago to Honolulu in April 1994. (Kenyon et al.

1996)

Infamous outbreak cases in various environments

Airborne transmission disease

M. Tuberculosis [International Union Against

Tuberculosis and Lung Disease]

Measles [Department of Health, HKSAR Govt,]



http://en.wikipedia.org/wiki/File:Amoy_Gardens.jpg

ASHRAE’s recommendation

• A strategic research agenda has been developed to address the role of HVAC systems in the spread of infectious disease;

• The topic is included in ASHRAE’s future strategic plans;

• Further research should be conducted to understand how reducing the energy footprint of buildings will impact infectious disease transmission;

• Further research should be conducted on engineering controls to reduce infectious disease transmission. The document summarizes the control strategies available and the occupancy categories in which these controls can be used. The research priority for each control is provided. Filtration and UVGI controls research are given top priority because less is known about how these controls can be applied in buildings and HVAC systems to decrease disease events.

WHO NATURAL VENTILATION GUIDELINE

ASHRAE. 2009. ASHRAE Position Document on Airborne Infectious Diseases.

WHO. 2009. Natural Ventilation for Infection Control in Health-Care Settings.

• For natural ventilation, the following minimum hourly averaged ventilation rates should be provided:

• 160 l/s/patient (hourly average ventilation rate) for airborne precaution rooms (with a minimum of 80 l/s/patient) (note that this only applies to new health-care facilities and major renovations);

• 60 l/s/patient for general wards and outpatient departments; and

• 2.5 l/s/m3 for corridors and other transient spaces without a fixed number of patients; however, when patient care is undertaken in corridors during emergency or other situations, the same ventilation rate requirements for airborne precaution rooms or general wards will apply.

Guidelines on Airborne Transmission Disease Control Workplace and Indoor Aerosols 2012


Formulation of the Problem

Infectious Source

Susceptible

Solid Surface

(Fomite)

Inhalation

Pathogen-laden

Aerosols

- Expiratory droplets and droplet nuclei can be airborne carriers for various pathogens (e.g. M. Tuberculosis, measles, influenza, etc).

- Epidemiology studies showed that these infectious diseases can be transmitted indoors following the ventilation air.

[Department of Medical Microbiology,

Edinburgh University]



Epidemiologic Approach

The epidemiology profession has developed a number of widely accepted steps

to investigate disease outbreaks.

Verify the diagnosis

related to the

outbreak

Identify the

existence of the

outbreak

Create a case definition to define

who/what is included as a case

Map the spread of the outbreak

Develop a hypothesis Study & refine hypothesis

Disease

outbreak

Develop and

implement control

and prevention

systems

Prevent



Study of airborne infectious disease

• Size distribution of the exhaled droplets

• How the droplets disperse?

• What are their fates? Deposited? Exhausted?

• Any chance to re-suspend from the surfaces?

• What is the infection risk?

• Any method to reduce the infection risk?



Studies on Expiratory Aerosol Size Distribution

• Expiratory droplets evaporate to nuclei and the diameter may reduce

to around half of the initial size. The smaller nuclei can be

suspended in air.

• Collecting media and microscopic measurement were applied to

reveal the size distribution of expiratory aerosols by numerous

studies, such as Duguid, 1946 and Louden and Roberts, 1967.

• The geometric mean diameter of particles from coughing were 12

μm from Duguid and 14 μm from Loudon and Roberts. (Nicas et al.

2005)

Duguid J.P. 1946. The size and duration of air-carriage of respiratory droplets and droplet-nuclei. J. Hyg, 4, 471–480.

Loudon R.G, and Roberts R.M. 1967. Droplet expulsion from the respiratory tract. Am. Rev. Resp. Dis., 95, 435–442.

Nicas M, Nazaroff W.W, and Hubbard A. 2005. Toward understanding the risk of secondary airborne infection: emission of respiratory

pathogens. Journal of Occupational and Environmental Hygiene, 2:3, 143-154.



Measured by SMPS and particle counter, tidal

breathing flow rate varied from 0.27 to 0.70l/s,

exhaled volume ranged from 0.35 to 1.70l.

The range of Cough flow rate was from 1.6-8.5l/s,

Cough expired volume varied from 0.25-1.60l.

PIV measurement on cough velocity for 29 volunteers:

Maximum velocity of cough at different distances

from mouth ranged from 1.5 to 28.8m/s, with

average of 10.2m/s.

PIV Average cough velocity was 11.2 m/s.

Studies on Expiratory Aerosol Size Distribution

Holmgren H, Ljungstrom E, Almstrand A.C, Bake B, and Olin A.C. 2010. Journal of Aerosol Science, 41, 439-446.

Gupta J.K, Lin C.H, and Chen Q. 2009. Indoor Air, 19:517-525.

VanSciver M, Miller S, and Hertzberg J. 2011. Aerosol Science and Technology, 45:415-422.

Zhu S, Kato S, and Yang J.H. 2006. Building and Environment, 41, 1691–1702.



Methods Size (μm)

Heymann et al. 1899 Solid impaction (glass slide with microscope) 30-500

Strauz et al. 1926 Solid impaction (glass slide with microscope) 70-85

Jennision, 1942 High-speed photography >100

Duguid et al. 1946 Solid impaction (glass slide with microscope) 100-125

Gerone et al. 1966 Solid impaction, Liquid impaction <1.0-1.0

Loudon et al. 1967 Solid impaction (paper with microscope) 55.5

Papineni et al. 1997 Optical particle counter <0.6

Fennelly et al. 2004 Solid impaction (multi-stages impactor) ≦3.3

Yang et al. 2007 APS, SMPS 0.62-15.9

Xie et al. 2009 Solid impaction (glass slide with microscope), Dust monitor 50-75

Wainwright et al. 2009 Solid impaction (multi-stages impactor) ≦3.3

Li et al. 2008 Solid impaction (glass slide with microscope), Dust monitor 50-100

Morawska et al. 2008 APS 0.1-1.0

Chao et al. 2009 IMI 4-8

Morawska et al. 2009 APS 0.4-10.0

Li et al. 2010 APS, IMI, microscope >50

Johnson et al. 2011 APS, droplet deposition analysis 0.7->20

Gralton J, Tovey E, McLaws M.L, and Rawlinson W.D. 2011. The role of particle size in aerosolised pathogen transmission: a

review. Journal of Infection, 62, 1-13.

Studies on Expiratory Aerosol Size Distribution Workplace and Indoor Aerosols 2012


• Cough jet velocity

• Size distribution

– Interferometric Mie Imaging, APS, Droplet Deposition Analysis

– Evaporation of droplets

– Respiratory activities

– Origins

Studies on Expiratory Aerosol Size Distribution Workplace and Indoor Aerosols 2012


80

10 10 15 13

Laser

Laser absorption paper and window for camera

20

Unit: cm

Camera

Expiration Jet Velocity and Size Profile Measurement

PIV (particle image

velocimetry) & IMI

(interferometric Mie

imaging ) Measurements

Droplets captured on an

image by IMI



Coughing Speaking Mouth exhale Nose exhale

Sca

le f

or

cou

gh

ing

Sca

le f

or

oth

er a

ctiv

itie

s

Male

Female

Jet Velocity Measurements by PIV Workplace and Indoor Aerosols 2012


Size Profile Measured by IMI

0

10

20

30

40

50

60

70

80

90

1.5 3 6 12 20 28 36 45 62.5 87.5 112.5 137.5 175 225 375 750 1500

Size Class [micron]

Mea

n n

um

be

r c

ou

nt

pe

r p

ers

on

in

50

co

ug

hs

Coughing 1cm

Coughing 6cm

Error bars show

maximum and minimum

0

10

20

30

40

50

60

70

80

90

1.5 3 6 12 20 28 36 45 62.5 87.5 112.5 137.5 175 225 375 750 1500

Size Class [micron]

Mea

n n

um

be

r c

ou

nt

pe

r p

ers

on

in

50

co

ug

hs

Coughing 1cm

Coughing 6cm

Error bars show

maximum and minimum

0

5

10

15

20

25

30

35

40

1.5 3 6 12 20 28 36 45 62.5 87.5 112.5 137.5 175 225 375 750 1500

Size Class [micron]

Me

an

nu

mb

er

co

un

t p

er

pers

on

aft

er

sp

ea

kin

g '1

-10

0' fo

r 10

tim

es

Speaking 1cm

Speaking 6cm

Error bars show maximum

and minimum

0

5

10

15

20

25

30

35

40

1.5 3 6 12 20 28 36 45 62.5 87.5 112.5 137.5 175 225 375 750 1500

Size Class [micron]

Me

an

nu

mb

er

co

un

t p

er

pers

on

aft

er

sp

ea

kin

g '1

-10

0' fo

r 10

tim

es

Speaking 1cm

Speaking 6cm

Error bars show maximum

and minimum

Coughing Speaking

Chao, Wan, Morawska et al. Journal of Aerosol Science, 40, 122-133, 2009



Exhaled droplets size modes

• Expiratory droplets generation modes

– Breathing: bronchiolar fluid film burst in the respiratory bronchioles (~0.8 μm)

– Laryngeal: vibration of the vocal folds in the larynx (~0.8-1.2 μm)

– Oral: large droplets form between the lips and the epiglottis where saliva is present (~200 μm)

• Coughing, speaking are combinations of the above modes

Johnson et al. Journal of Aerosol Science. 2011.

Morawska L, Johnson G.R, Ristovski Z.D, Hargreaves M, Mengersen K, Corbett S, Chao C.Y.H, Li Y, and

Katoshevski D. 2009. Journal of Aerosol Science, 40, 256-269.



The Fate of the Exhaled Aerosols

• The expiratory droplets may evaporate to half of the initial size within a short time.

• Small droplets can be suspended in air for a long time. Large droplets settle on floor in a few seconds.

• Size change occurs during transport and deposition.



Fluid Dynamical Properties

Boundary layer

Surface

Drag force

Gravitational pull

Deposit onto

surface

Turbulent fluctuation

The transport of aerosols in air is a

multiphase fluid mechanical process

Deposition and resuspension of aerosols is

closely related to air turbulence.

As the droplets are carried by the exhaled air, a number

of forces are involved (gravity, buoyancy, diffusion, drag,

etc).

Parienta D, Morawska L, Johnson G.R, Ristovski Z.D, Hargreaves M, Mengersen K, Corbett S, Chao C.Y.H, Li Y, and Katoshevski D. 2011. Theoretical analysis

of the motion and evaporation of exhaled respiratory droplets of mixed composition. Journal of Aerosol Science, 42, 1–10.

Modeling of the expiratory aerosol transport have

been performed in Eulerian and/or Langrangian

approach.

Eulerian: the properties in terms of time and space at

fixed points in space. E.g. simulation of airflow

Langrangian: following individual particles and

determine the properties. E.g. particle position



Dispersion Characteristics

• Different ventilation strategies

– Mixing

– Displacement

– Downward flow

– Under-floor

– Personalized ventilation

– Neutral ventilation

WHO

Displacement

ventilation

Mixing

Isolation room

Aircraft cabin Downward flow

Supply

Return

Stratification level

Upper

zone

Lower

zone



• Experiment

– Tracer gas, smoke, particle

– bacterium-laden aerosol

• Numerical Simulation

– Multi-phase, discrete phase Zhao, Zhang, and Li. 2005. Building and Environment, 40,1032-1039.

Chao and Wan. 2006. Indoor Air, 16, 296-312

Chao, Wan and Sze-To. 2008. Aerosol Science and Technology, 42, 377-394

Mui, Wong, Wu and Lai. 2009. Journal of Hazardous Materials, 167, 736-744.

Qian, Li, Nielsen, and Hyldgaard. 2008. Building and Environment, 43,344-354.

He, Niu and Gao. 2011. Building and Environment, 46, 397-408.

Lai and Wong. 2011. Aerosol Science and Technology, 45, 909-917.

Dispersion behavior of droplets were studied in different indoor

environments. Various studies indicate that droplets can transport

more than 1m. Different ventilation configurations, thermal plume

effect, etc., were investigated.

Models to predict the performance of ventilation systems in

buildings:

• Analytical / Empirical

Experimental

• Small-scale/ Full-scale

Numerical

• Multi-zone/ Zonal/ CFD

Dispersion Characteristics Workplace and Indoor Aerosols 2012


Droplet Dispersion Measurements

Interferometric Mie Imaging (IMI)

method

Aerosol

spectrometer

Method Instrument Specifications

IMI LaVision SizingMaster

Measurable size range: 2m

(Correspond to 5.1m initial droplet size for 6vol%) Frequency: 10Hz

Aerosol Spectrometer

GRIMM Labortechnik Model 1.108

Measurable size range: 0.3 -

20m in 16 size channels

(Correspond to 0.765 - 51m initial droplet size for 6vol%) Frequency: 1Hz

Measurements with the

aerosol spectrometer

Chao and Wan, Indoor Air, 2006; Wan and Chao, AS&T, 2008



Generation of Simulated Expiratory Droplets

Droplet generator setup

Recipe of ‘simulated saliva’ solution

Regulators and gauges

Droplet generator head

Flowcontroller

Species Molecular

weight /

Atomic

mass

Molar

concentration/

L water

Estimated

mass

concentration

/L water

Na+ 23g 918mM 2.10.2g

K+

39.1g 6011mM 2.30.4g

Cl- 35.5g 10217mM 3.60.6g

Lactate 89g 4417mM 3.61.5g

Glycoprotein N.A. 7618g

Non-volatile content of saliva

[Nicas et al., J. Occup. Environ. Hyg., 2: 143-154, 2005]

Solutes

Molecular

Weight

Concentration

NaCl (salt)

58.5 g/mol

12.0 g/L

Glycerin

92.09

g/mol

76.0 g/L

1 second of puff release is used to

simulate a cough



Computational Fluid Dynamics (CFD) Modeling

Discrete phase (droplets or droplet nuclei) - Lagrangian

g – gravitational acceleration

Fi – Thermophoretic force, Brownian diffusion

ip

p

DpFguu

f

dt

du

687.0Re15.01)(Re ppDf where

Droplet evaporation

)( CCcdt

dns

3

1

2

1

Re6.00.2 ScD

cDNu p

m

p

AB

Surface vapor concentration

Bulk air vapor concentration

Heat transfer due to evaporation

fg

p

pp

p

pp Hdt

dmTTHD

dt

dTcm )(

3

1

2

1

PrRe6.00.2 p

eff

pHDNu

[Ranz and Marshall,

1952]

Carrier phase (Air) - Eulerian

Conservation law

iii Jmumt

)(

Species transport (water vapor):

Turbulence closure:

RNG k- model.

[Chao & Wan, Indoor Air, 2006]

iiSgraddiv

tiii

)()(

Air (continuum)

- Flow (driven by ventilation and temperature gradient)

- Transport of water vapor

Droplets (Discrete)

- Movement driven by the

continuum phase and its own body forces

Droplet-Air interface

- Momentum exchange

- Energy (heat transfer) and mass exchange (evaporation)

Droplet-droplet interactions (coagulations)



Modeling Approach

Stochastic tracking of turbulent motions

'uuu Carrier phase instantaneous

velocity

The particle under the influence of the same eddy

until

1) t > Te (eddy lifetime)

2) d(t) > Le (eddy length scale),

time needed = Tcross (eddy crossing time)

[Gosman & Ioannides, 1981]

u

up0

d(t1)

xp0

xp1

xp0 + ut1

2Le

Time = 0 Time = t1

Fluid flow path

particle flow path

u

up0

d(t1)

xp0

xp1

xp0 + ut1

2Le

Time = 0 Time = t1

Fluid flow path

particle flow path

2'' uu

The fluctuating part

Where is a random number sampled from a

Gaussian pdf with zero mean, unit variance

3

2'2

ku and

[ Crowe et al., 1998; Graham, 1996 ; Lu, 1995; Wang & James, 1999]

Near wall correction for turbulence anisotropy

2'' ufu v )1( 02.0 y

v efwhere

keuk y 202.02 )1('2

3'

define

kewvu y

3

2)1(''' 02.0222

For y+ 80



Dispersion Study in a Hospital ward

Experimental setup

Floor area = 39m2

Ceiling – mixing type ventilation

Room conditions: 21.5oC, 60%RH

Manikins with heating wire

(Stripped for demonstration)

Heat boxes

(75W)

(100W)

(75W)

(100W)

(75W)

(100W)

S

SE

E

y

x

z

y

x

z

(75W)

(100W)

(75W)

(100W)

(75W)

(100W)

S

SE

E

y

x

z

y

x

z

(75W)

(100W)

(75W)

(100W)

(75W)

(100W)

S

SE

E

y

x

z

y

x

z



Airflow Pattern

Numerical simulation

PIV measurement



Parameters

Exhaust Exhaust Exhaust Exhaust

Vertical injection Lateral injection

x x

5.9m 5.9m

Two ‘coughing’ orientations

Two supply airflow rates

- 1060 m3/hr (11.6 ACH)

- 550 m3/hr (6.0 ACH)



0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1 10 100 1000

Time after the 'cough', t [s]

Me

an

vert

ica

l po

sitio

n, z [m

]

1.5 micron, exp, 11.6 ACH 12 micron, exp, 11.6 ACH1.5 micron, num, 11.6 ACH1.5 micron, num, 6.0 ACH12 micron, num, 11.6 ACH12 micron, num, 6.0 ACH

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1 10 100 1000


Me

an

ve

rtic

al p

ositio

n,

z [m

]

28 micron, exp, 11.6 ACH


28 micron, num, 11.6 ACH




Vertical motion Droplet initial size 45m

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1 10 100 1000


Me

an

vert

ica

l po

sitio

n, z [m

]

28 micron, exp, 11.6 ACH45 micron, exp, 11.6 ACH 28 micron, num, 11.6 ACH28 micron, num, 6.0 ACH45 micron, num, 11.6 ACH45 micron, num, 6.0 ACH

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1 10 100 1000


Mean

ve

rtic

al po

sitio

n, z [m

]

1.5 micron, exp, 11.6 ACH


1.5 micron, num, 11.6 ACH




Mean vertical positions very similar in both supply

airflow rates. Due to mixing effect of thermal plumes

Larger droplets tended to stay lower at the lower supply airflow rate

Vertical injection

Vertical injection

Lateral injection

Lateral injection

Droplets stayed low

Initial push by

the cough jet



Vertical motion

Droplet initial size 87.5m

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1 10 100 1000


Me

an

vert

ica

l po

sitio

n, z [m

]





137.5 micron, num, 11.6ACH


0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1 10 100 1000

Time after the 'cough', t [s]M

ea

n v

ert

ica

l p

ositio

n,

z [

m]








Changing the supply airflow rate had insignificant effect on the transport due to

the dominance of gravitational settling

Short airborne time



Lateral dispersions Droplet initial size 45m

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

1 10 100 1000


Me

an

la

tera

l d

isp

ers

ion

dis

tan

ce

, |x

| [m

]







0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1 10 100 1000


Me

an

dis

pe

rsio

n d

ista

nce

in

x d

ire

ctio

n,

|x| [m

]

1.5 micron, exp, 11.6 ACH12 micron, exp, 11.6 ACH1.5 micron, num, 11.6 ACH1.5 micron, num, 6.0 ACH12 micron, num, 11.6 ACH12 micron, num, 6.0 ACH

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

1 10 100 1000


Mea

n late

ral d

ispe

rsio

n d

ista

nce

, |x

| [m

]

1.5micron, exp, 11.6 ACH






0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1 10 100 1000


Me

an

dis

pe

rsio

n d

ista

nce

in

x d

ire

ctio

n,

|x| [m

]

28 micron, exp, 11.6 ACH45 micron, exp, 11.6 ACH28 micron, num, 11.6 ACH28 micron, num, 6.0 ACH45 micron, num, 11.6 ACH45 micron, num, 6.0 ACH

Lateral dispersion

became slower at

a lower supply

airflow rate



Initial push by

the cough jet



Lateral dispersion

Droplet initial size 87.5m

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

1 10 100 1000


Me

an

la

tera

l d

isp

ers

ion

dis

tan

ce

, |x

| [m

]







0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1 10 100 1000

Time after the 'cough', t [s]M

ea

n la

tera

dis

pe

rsio

n d

ista

nce

, |x

| [m

]






137.5 mciron, num, 6.0 ACH

•Lateral dispersion was minor due to slow dispersion rate and short airborne time.

•Again, changing the supply airflow rate had insignificant effect due to the

dominance of gravitational settling



Droplet Dispersion in Aircraft Cabin (DTU Study)

‘Coughing’ point

200 L/s

100 L/s 20 L/s

Y



Concentration Contour

No. of Aerosols

/Liter of Air

1s 3s 5s 10s 20s 30s 120s 360s

1s 3s 5s 10s 20s 30s 120s 360s

1s 3s 5s 10s 20s 30s 120s 360s

1s 3s 5s 10s 20s 30s 120s 360s

4-8

micron

16-32

micron

2-4

micron

8-16

micron

50

0

100

250

800

1500

3000

6000

8000

10000

50

0

100

500

1000

2000

5000

15000

50000

200000

50

0

100

500

1000

2000

5000

15000

50000

200000

50

0

100

250

1000

2000

5000

10000

25000

50000

100 L/s, Middle Injection



Droplet Deposition Measurements

Use of fluorescence technique to study

droplet deposition (Thatcher et al. 1996; Lai

and Nazaroff 2005)

Polyethylene film

Simulated expiratory

droplet with

fluorescent dye

Surface covered

with detachable film

Deposition

Solvent

Photospectrometry

Photospectrometry is employed to determine the

amount of fluorescent dye in the solvent so as to

determine the amount of droplets deposited on the

surface under concerned.

Aircraft Cabin (Mock-up of B-767 at Technical University of Denmark )



Droplet Deposition (Aircraft Cabin)

Deposition by percentage mass

Wan, Sze To, Chao, Fang, Melikov. Aerosol Science and Technology, 43, 322-343, 2009

Sze To, Wan, Chao, Fang, Melikov. Aerosol Science and Technology, 43, 466-485, 2009



Exposure and Infection Risk Assessment for Respiratory Diseases

Generation Exposure Transport

Intake (Respiratory

Deposition)

Air Turbulence

-Air turbulence plays an important role on both the

transport and intake of aerosolized pathogen;

-Any estimated exposure level to aerosolized

pathogens should be regarded as an expected value

rather than an exact value;

-Exposure and/or risk assessment models should be

able to consider these randomness.



Modified Wells-Riley Models

Existing Infection Risk Model

Wells-Riley equation

• When each susceptible person inhales a number of infectious droplets or

nuclei equal to a “quantum”, 63.2% of the population of susceptible

people will be infected. [Wells, 1955]

• Adopt the steady-state and well-mixed air assumptions: Infectious

particles are distributed evenly in air.

Q

Iqpt

I eP

1

Non-steady-state and imperfect mixing

[Gammaitoni and Nucci, 1997 ]

Air change rate Total number of

people in the

premises

Average volume fraction of

room air that is exhaled

breath

[Rudnick and Milton, 2003]

2

1exp1

N

eN

V

pIqP

Nt

I

IqtfPI exp1

Gammaitoni L, and Nucci M.C. 1997. Using Maple to analyze a model for airborne contagion. MapleTech, 4, 2–5.

Rudnick S.N, and Milton D.K. 2003. Risk of indoor airborne infection transmission estimated from carbon dioxide concentration. Indoor Air, 13, 237–245.



Dose-Response Model

[Nicas, 1996 ]

For tuberculosis:

Pathogen generation rate

[Sze To et al., 2008]

Q

tIGpPI

exp1

Respiratory deposition fraction

m

j

t

josjjoIo dttftxvcptfrtxP

10

)(,exp1),(

For both airborne and droplet transmission modes:

Dose-response model for airborne disease transmission

rNPI exp1Exponential model:

Fitting

parameter

Intake dose

Beta-Poisson model:

NPI 11

Dose-response type infection risk assessment models require experimentally obtained

infectious dose data to construct the dose-response relationship.

Nicas M. 1996. An analytical framework for relating dose, risk, and incidence: an application to occupational tuberculosis infection,

Risk Anal., 16, 527–538.

Sze To G.N, Wan M.P, Chao C.Y.H, Wei F, Yu S.C.T, and Kwan J.K.C. 2008. A methodology for estimating airborne virus exposures in

indoor environments using the spatial distribution of expiratory aerosols and virus viability characteristics. Indoor Air, 18,

425–438.

Sze To G.N. and Chao C.Y.H. 2010. Review and Comparison between the Wells-Riley and Dose-response Approaches to Risk

Assessment of Infectious Respiratory Diseases, Indoor Air, 20, 2-16.



Indirect Contact Pathway

fs, fh, fm : frequency of coughing/hand-to-contaminated

surface contact/ hand-to-mucous membrane contact.

Nx : amount of pathogen on the contaminated surface

after a cough.

cm, ch : fraction of pathogen transferred to the mucous

membrane from hand/transferred to hand from the

contaminated surface.

b : a constant related to the survivability of the

pathogen on hand.

1 2

3

B

ec

eccA

e

ecN

f

fnE

h

mm

h

h

m

f

b

h

f

b

f

f

hh

f

b

f

b

mx

h

sm

1

11

1

1

2

12

11

1111

m

mmm

f

b

m

f

bn

n

mh

f

b

mh

f

b

mh

ec

eccecnceccnn

mm

hm

m

h

m

hmm

m

hm

m

h

m

h

f

b

mf

f

h

f

b

mf

f

h

f

f

h

f

bn

n

m

f

b

mf

fn

h

f

b

mh

f

f

h

f

fn

h

eccecc

cececcecc

c

c

111111

111111111

11

11

Exposure after nth hand-to-

mucous membrane contact:

A:

B:

t

hmmtm dtNfcE0

,

Integral form:

tbfc

bfcafc

Nffctbfctafc

afcbfc

afc

NfNfc

N mm

mmhh

xshhmmhh

hhmm

hh

xsshh

h

exp1expexp

0



Multiple-pathway Dose-response Model

“Escaping the infection” concept :

where PI,1, PI,2 and PI,m are the infection risk via the 1st, 2nd and mth

exposure pathways respectively.

Beta-Poisson model:

Exponential model:

where r1, r2, rm, N1, N2 and Nm stand for the fitting parameters and

intake doses for the 1st, 2nd and mth exposure pathways, respectively.

Exponential model is used since it only requires a single set of fitting

parameters.

mmI NrNrNrP 2211exp1

mmmmI drdrdrrRrRrRNrNrNrP 2121

1

0

1

0

1

02211exp1

mIIII PPPP ,2,1, 1111

Sze To & Chao. Indoor Air, 20, 2-16, 2009



Parameter Value Remarks Reference

c virus concentration 5 105 TCID50 Median concentration from 7 patients Murphy et al., 1973

r

Fitting parameter

ID50 = 1.8 TCID50

r = 0.385

Infectious dose for aerosols 3 m

(mean value of the range: 0.6-3.0)

β = 0.6.

Alfard et al., 1966

ID50 = 223.5 TCID50

r = 0.0031

Nasal infectious dose, for larger

aerosols and mucous membrane

(mean value of the range: 127-

320)

Douglas, 1975

f(t)

Viability

75% after aerosolization, 1%/min

additional decay within 15

minutes

Extrapolated from Figure 2B. Under

21oC, 5% RH.

Schaffer et al., 1976

fs Cough frequency 18 cough/hr Median cough frequency of 60 patients Loudon & Brown, 1967

fh Hand contact

frequency

3 /hr Assumption

fm

Nasal/eye membrane

contact frequency

0.7 /hr Frequency of eye-rubbing and nose-

picking of 124 adults

Hendley et al., 1973

ch

Hand transfer efficiency

0.00251Af/Ac

Af: Area of the fingerpad

Ac: Area of the contaminated surface.

Transfer efficiency of influenza virus to

fingerpad from porous material is

around 0.251%

Beam et al., 1982

cm

Membrane transfer

efficiency

1 Assumption

b Viability on hand ~6.4 /hr Influenza virus survived on skin for

more than 0.03 day

Walther & Ewald, 2004

Target Pathogen: Influenza A virus Workplace and Indoor Aerosols 2012


Risk Assessment in an Isolation Ward

Case 1

Current

situation

Case 2

Lower ACH

(6ACH)

Case 3

Bed

allocation

Case 4

Inlet vent

position

Case 5

Higher RH

(70% RH)



Estimated infection risk via inhalation at seat Case

A4 A3 A2 A1

100 L/s 0.016 0.013 0.010 0.002

200 L/s 0.005 0.012 0.017 0.016

Fail (20 L/s) 0.032 0.045 0.018 0.014

B4 B3 B2 B1

100 L/s 0.659 0.132 0.050 0.013

200 L/s 0.580 0.070 0.018 0.030

Fail (20 L/s) 0.643 0.127 0.033 0.040

C4 C3 C2 C1

100 L/s 0.094 0.037 0.034

200 L/s 0.024 0.041 0.029

Fail (20 L/s)

Index

patient 0.095

Aisle

0.052 0.023

Risk Assessment in Aircraft Cabin

B3

A4 A3

B4

A2 A1

B1 B2

C3 C1 C2

Index patient

Inhalation Pathway

Estimated infection risk via hand contact at seat Case

A4 A3 A2 A1

100 L/s 1.50 10-7

7.87 10-8

2.74 10-8

3.08 10-8

200 L/s 1.62 10-7

9.06 10-8

2.70 10-7

2.96 10-7

Fail (20 L/s) 1.50 10-7

1.39 10-7

3.36 10-8

2.80 10-8

B4 B3 B2 B1

100 L/s 4.38 10-6

3.63 10-6

1.18 10-7

1.19 10-7

200 L/s 4.51 10-6

3.75 10-6

1.15 10-7

1.10 10-7

Fail (20 L/s) 4.97 10-6

3.56 10-6

1.18 10-7

1.13 10-7

C4 C3 C2 C1

100 L/s 5.34 10-6

1.27 10-7

1.14 10-7

200 L/s 5.57 10-6

1.21 10-7

1.13 10-7

Fail (20 L/s)

Index

patient 5.33 10

-6

Aisle

1.20 10-7

1.10 10-7

Indirect Contact Pathway

-Passengers seated closed to index case have much higher risk than

the others

-Risk contributed by inhalation pathway is higher than the risk

contributed by indirect contact pathway by 4-5 order of magnitude

-Increase in supply air flow rate reduces the average risk of all

passengers, but enhances the dispersion of expiratory droplets; thus,

some passengers seated far from the index case have higher risk under

higher supply air flow rate.



Use of Risk Assessment Model in

Retrospective Analysis

Risk assessment model can be used to perform retrospective analysis on known cases to

relieve important information.

Known Parameters Spatial Infection RiskRisk Assessment Model

Unknown ParametersSpatial Pattern of

Infection CasesRisk Assessment Model

??? ???

Spatial Distribution of

Infectious Particles



Known Parameters Infection RiskRisk Assessment Model

Unknown Parameters Attack RateRisk Assessment Model

(a)

(b)

Assuming every susceptible person has

the same risk (or assuming a well-mixed

air).

To consider the heterogeneous infection

risk (or to consider the spatial infection

pattern).



Likelihood of Infection

L(p): probability of having p as the infection risk of the susceptible in the outbreak,

ranges from 0 to 1. It is also referred to as the likelihood. The first parenthesis in the

right hand side is the binomial coefficient, N: The total number of susceptible

people. n: number of susceptible who acquired the infection.

The concept can be used to perform retrospective analysis of infection cases. By

grouping different susceptible into different groups according to their risk level, this

method can supplement risk assessment model in analyzing spatial infection pattern.

Sze To, and Chao (2010). Use of Risk Assessment and Likelihood Estimation to Analyze Spatial Distribution

Pattern of Respiratory Infection Cases, Risk Analysis, 31(3), 351-369.

When a person has a certain infection risk, there are two possible

outcomes: the person will either be infected or remain uninfected.

Binomial probability can be used to describe the event:

Infected

Uninfected

Index

case nNn ppn

NpL

1

Unknown

Parameter, α3

Spatial Infection

Risks, P3

Risk Assessment

Model



Spatial Pattern of

Infection Cases

Likelihood

Estimation

Unknown

Parameter, α4

Unknown

Parameter, α5

Unknown

Parameter, α2

Unknown

Parameter, α1

Spatial Infection

Risks, P4

Spatial Infection

Risks, P5

Spatial Infection

Risks, P2

Spatial Infection

Risks, P1

L3

L4

L5

L2 = Lmax

L1



Retrospective analysis on infectious source strength

Information collection of the

outbreak CFD Simulation

Exposure Level & Intake Dose

Fraction

Risk Assessment & Likelihood Estimation

Infectious Source Strength

Future Studies

Data from medical record; Indoor environmental

condition

Geometry construction; Simulation of airflow and droplets injection

Convert the simulation data into intake dose fraction

Adopting Dose-response model for risk

assessment; Likelihood Estimation

MLE is used to estimate the most

likely infectious source strength

The Approach

Impacts of human movements, size profile

of pathogen-laden droplets, etc.



Example using an outbreak case

The case on the Boeing 747-100

(Kenyon et al., 1996)

• The outbreak case happened in the economic cabin on a flight from Chicago to Honolulu in April 1994;

• The flight lasted for 8.75 hours;

• Among the 15 contacts with positive test

results in the investigation afterward, 6 had

no other risk factors which indicated that they

were very likely to be infected by the index

case during the trip.

• Only the blue area in the picture was

simulated in this study because the infectious

strength was substantially weakened beyond

this area due to the spatial distance.

• 3 passengers were considered as secondary

cases infected by the index passenger. Since

the 3 infected passengers seated near the

index case.

• No.12 was a seat for the crew member who

seldom sat there so it was not included in the

simulation.

Kenyon et al., (1996) Transmission of multidrug-resistant mycobacterium tuberculosis during a long

airplane flight”. J.Medicine



CFD Simulation

Supply air slots

(0.04m × 7m, 2Nos.)

Air outlet slots

(0.10m × 7m,

2Nos.)

Geometry modeling of the aircraft cabin

3-D version of simulation cabin part

Photo Showing the air inlet slot in

Boeing 747-100B (Backer et al., 2006)

Backer et al., (2006), Validation for CFD Prediction of Mass Transport in Aircraft Passenger Cabin FAA,

http://www.faa.gov/library/reports/medical/oamtech

Hocking (1998), Indoor air quality: recommendations relevant to aircraft passenger cabins, Am. Ind. Hyg. Assoc. J.

Air Exchange Rate (filtered air)

20.0 h-1 (Hocking, 1998)

Ventilation capacity per passenger (filtered air)

7.9L/s (in simulated cabin)



http://www.faa.gov/library/reports/medical/oamtech

CFD Simulation

Droplet size (Initial Diameter)

[μm]

Measured Number

in one cough

Droplet nuclei

[μm]

3 212 1.2

6 967 2.4

12 363 4.8

20 156 8.0

Simulation of droplet injections

• Droplets size spectrum in a real cough (Chao et al. 2009).

6.7 mg of droplets was generated in a cough on average.

• 10,000 tracer droplets were injected for each size;

Evaporation of droplets was considered in

simulation;

• Transient mode was adopted to tracing droplets

movement in cabin.

Chao, Wan, Morawska, Johnson, Ristovski, Hargreaves, Mengersen, Corbett, Li, Xie, Katoshevski. (2009).

Characterization of Expiratory Air Jets and Droplet Size Distributions immediately at the Mouth Opening,

Journal of Aerosol Science.



Risk Assessment and Likelihood Analysis

Relative intake dose of each susceptible passenger:

• Group the susceptable passengers according to their relative intake dose • Infection Risk:

•Likelihood of infection

Exposure Level

&

Intake Dose Fraction

Risk Assessment

Likelihood Estimation

mm

i

irir pLNPL

1

1

)(exp1),( orpoiI tNQtxP

t i iii

c

rr dttvbd

v

pN )(



• MLE of the infectious source strength: 17.2 millions of viable bacilli/hr

• 95% confidence interval: 2.29 mil – 153.4 mil viable bacilli/hr

• If using Well-mixed air approach

Estimated infectious source strength is 127 quanta/hr.

(1 quantum = 1 viable bacillus for TB (Huebner et al. 1993) )

Risk Assessment & Likelihood Analysis

Maximum Likelihood Estimation Curve

• Average TB infection rate of hospital

employees was about 1% (Price et al. 1987).

In these nosocomial cases, the exposure time

of employees to infector was much longer

than in the aircraft cabin case. Short

exposure time and high infection rate

indicated that the index case in the cabin was

very probably a super spreader.

• Some TB patients can have more than 30

millions TB bacilli/ml in their respiratory

fluid (Yeager et al. 1967). It is possible for

an infector to generate millions of bacilli per

hour.

• The difference between the two approaches

may be caused by:

Only small infectious particles can remain

suspended in air, which only constitute

1/5000 volume in the total droplets volume

generated by coughing. However, the well-

mixed air approach considers all sizes.

The gas phase assumption in Well-mixed

air approach ignores the respiratory

deposition of infectious particles in alveolar

region. In fact, only 1%-10% of droplet

nuclei could be deposited and to commence

infection.

Q

Iqpt

S

CPI exp1

Huebner et al. (1993) The tuberculin skin test, Clinical Infectious Disease.

Price et al. (1987) Tuberculosis in Hospital Personnel, Infection Control.

Yeager et al. (1967) Quantitative studies of mycobacterial populations in

sputum and saliva. American Review on Respiratory Disease.

Lik

elih

oo

d

Q (viable bacillus/hr)



Use of Bacteriophage in Exposure & Risk Assessment

Plaques formed by E. Coliphage

0

10

20

30

40

50

60

70

0 0.5 1 1.5 2 2.5 3

Lateral distance from aerosol injection point (m)

Ba

cte

rio

ph

ag

e e

xp

osu

re (

pfu

)

Proposed method (Along Supply Vent)

Biological sampling (Along Supply Vent)

Proposed method (Along Exhaust Vent)

Biological sampling (Along Exhaust Vent)

Electron micrograph of multiple

bacteriophages [Adrian, 1985]

The

infecto

r

Sze To, Wan, Chao et al. Indoor Air, 18, 425-438, 2008

Validating an exposure assessment model Assessing infection risk of a hypothetical

case



Use of Benign Bacteria in Containment Assessment

Layout of one cubicle E. Coli collected and cultured on a plate

New isolation ward with the highest standard in Hong Kong.

Each cubicle has an anteroom with interlock system. 100% fresh air supply, 5-10 Pa negative pressure, upper room

UVGI, and at least 12 Air Change Per Hour are maintained.

Containment performances against tuberculosis (TB) bacilli and influenza virus are concerned.

Leakages of the airborne pathogens during door open/door close/entry and exit of health care worker were

assessed.

Tuberculosis bacilli are rod-shape bacteria. A benign strain of E. Coli bacteria, also rod-shape, was used to

simulate TB-laden aerosols.



Transport of pollutant by human

entering isolation room


• Artificial saliva with E. coli was aerosolized and the droplets were collected by an viable impactor at the adjacent zone

• Transport of aerosols by door opening, human movement

Impactor

Particle counter

Aerodynamics particle size

Nozzle




Results

Case

Injection Point

Measurement Location

Door Closed

Door Opened

With Entry/Exit

1 Cubicle Anteroom 0.06% 0.28% 0.46%

2 Anteroom Corridor 1.0% 1.0% 2.7%

3 Corridor Anteroom 6.9% 3.0% 3.2%

4 Anteroom Cubicle 20.0% 18.3% 20.7%

5 Corridor Nurse Station 0.001% 0.001% 0.003%

Inter-zone transport of bacteria was observed in all situations.

Human movement enhances the leakage of airborne pathogen.

Anteroom, negative pressure, high ACH, etc, cannot 100% prevent inter-zone transport of airborne

pathogen.

Due to negative pressure, airborne pathogens leaking out from one cubicle will be drained into another

cubicle efficiently.

Nurse station of the ward is quite well-protected, since it is under positive pressure with respect to the

corridor. However, the health care workers may still be exposed to pathogen in a greater magnitude when

they travel through the corridor.

Use of bacteriophage to assess the containment performance against aerosolized virus, e.g. influenza virus,

can be a good tool for assessing health risk.

Leung, Sze-To, Chao, Yu, and Kwan. 2012. Study on the Inter-zonal Migration of Airborne Infectious Particles in an Isolation

Ward using Benign Bacteria. Indoor Air. Revised Version Submitted.



Treatment Technology and Their Effectiveness

• UVGI (254nm UVC) in

isolation room, exhaust duct to inactivate pathogens

• HEPA filter to remove airborne infectious particles/ Air cleaning, etc.

Xu P, Peccia J, Fabian P, Martyny J.W, Fennelly K.P,

Hernandez M, and Miller S. 2003. Efficacy of

ultraviolet germicidal irradiation of upper-room air in

inactivating airborne bacterial spores and

mycobacteria in full-scale studies. Atmospheric

Environment, 37, 405-419

Only inactivate pathogens in

upper part of the room?

Beggs C.B, Noakes C.J, Sleigh P.A, Fletcher

L.A, and Kerr K.G. 2006. Methodology for

determining the susceptibility of airborne

microorganisms to irradiation by an upper-

room UVGI system. Journal of Aerosol

Science, 37, 885-902.

CFU decreased by 30-40% after

the UV lamps were switched

on.

Kowalski W.J, and Bahnfleth W.P. 2000. UVGI

design basics for air and surface disinfection.

Heating/Piping/Air Conditioning Engineering.

72, 100-110.

Approximate market share of

different UVGI systems

About 60% of UVGI systems were

used in health care facilities.

UVGI can inactivate airborne bacteria

with effectiveness ranging from 46-

98%. Linear relationship was found

between the UVGI inactivation rate

and UV irradiance level.

In-duct systems 27%

Upper roomair 25%

Room circulation 17%

Microbial growth control 32%

0

10

20

30

40

50

hospitals shelters prisons clinics other

%

Wu, C.L., Yang, Y., Wong, S.L., and Lai, A.C.K. 2011.

A new mathematical model for prediction irradiance

field of upper-room ultraviolet germicidal systems.

Journal of Hazardous Materials, 189, 173-185.



• Personalized ventilation – Provide clean and cool air close to the

occupants

– Improve perceived air quality

– Improve peoples’ thermal comfort

– Protection from and minimizing of airborne transmission of infectious agents

– Individual control

Kaczmarczyk J, Melikov A, and Fanger P.O. 2004. Human response to personalized ventilation and mixing ventilation. Indoor Air, 14, 17-29.

Melikov A.K. 2004. Personalized ventilation. Indoor Air, 14, 157-167.

-Dissatisfied percentage decreased

-Acceptability of air increased

-Reported SBS symptoms decreased

-Local thermal comfort increased

PV improves perceived air quality when

compared to mixing ventilation

Personalized

ventilation

Treatment Technology and Their Effectiveness Workplace and Indoor Aerosols 2012


Pantelic J, Sze To G.N, Tham K.W, Chao C.Y.H,

and Khoo Y.C.M. 2009. Personalized ventilation

as a control measure for airborne transmissible

disease spread. J.R. Soc. Interface, 6, S715-S726.

Melikov A.K. 2004. Personalized ventilation. Indoor Air, 14, 157-167.

Probability of infection decreased

27%-65% with PV

Air distribution, applicability and energy:

Transport of pollution with PV and other

ventilation system. Energy saving by using

PV.

Control strategies for PV (and other

ventilation systems)



• Coating on surface to inactivate

pathogens

• Survival time of bacteria, virus

– day? Week?

• Surface with antimicrobial coating to inactivate pathogens and reduce the infection risk from indirect contact

• Surfaces:

– Lift buttons, door handles, keyboards

1

2

3

Li Y, Leung W.K, Yeung K.L, Lau P.S, and Kwan J.K.C. 2009. A

multilevel antimicrobial coating based on polymer-encapsulated

ClO2. Langmuir, 25(23), 13472-13480. Reduce infection risk

from indirect contact

B. subtilis S. aureus E. coli

Requirement:

Response to body temperature,

moisture, light, etc.

Long duration: refill monthly?

Easy to refill the coating?

Non-toxic, etc

Inactivate 99% of bacteria in 1min



Recent work: Resuspension of infectious droplets

• Re-suspension of infectious particle, ultrafine particle

– Origin - Walking, vacuum cleaning, sweeping, bed making

• Wind turbulence, vibration

– Mechanism - Lifting/ Sliding/ Rolling

– Material - Solid particle, droplet, pathogen-laden droplet



Roadmap to investigate Resuspension of infectious droplets

Resuspension of infectious droplets by human activities

Wind turbulence Vibration

Wind tunnel experiment Vibration experiment

Require the removal forces in normal and tangential directions

Centrifuge experiment



Centrifuge Experiment

(Removal force/ weight)

Centrifuge experiment to determine the removal forces distribution.

The removal force is smaller in tangential direction than normal

direction.

Smaller removal force to weight ratio for larger particles.

0

25

50

75

100

1 100 10000 1000000

Rrm

ain

ing

frac

tio

n (

%)

log10 (RW2/g)

Normal (51um)

Tangential (51 um)

Normal (16um)

Tangential (16um)

Polystyrene

Particle (PS) 51um 16um



Centrifuge Experiment

Remaining volume fraction of 30μm

glycerol droplets from acrylic substrate

Change of average size of droplets at

initial size of 30μm

Unlike solid particle, droplets may split into two portions

and only one portion detaches from the substrate.



Resuspension Modeling by Wind Turbulence

• Assume resuspension by rolling, angular velocity is described by

•Adhesion force Fa was found by centrifuge

experiments with normal force

•Ratio of a to b is the ratio of tangential force to

normal force by Centrifuge experiments

cos2

sin22

mga

bmgFa

Fa

bFdt

dI aLD

P

dp

x

a

b

Fa

FL

FD

mg

Angular velocity is modeled by Langevin equation.

The fluctuating angular velocity is represented by a white noise Wiener process.

tdWTT

dtttd

22

Timescale for energy

dissipation during rolling Model constant

(Drag)

(Lift)



• Resuspension occurs when ω is

larger than a critical value

• A better fit than the RRH model

(Reeks, Reed & Hall 1988) and

Rock’n Roll model (Reeks & Hall 2001)

10-1

100

101

0

0.2

0.4

0.6

0.8

1

friction velocity (m/s)

frac

tio

n r

emai

nin

g a

fter

1s

Rock'n Roll model

C0=0

RRH model

C0=1e-3

Particle at rest, = 0

> 0?

Particle is resuspened

Yes

Yes

No

No

Find.

Particle unmoved, = 0

Particle rolling

> c?

t t+t

Fu, Chao, et al. 2012. Particle Resuspension in a Wall Bounded Turbulent Flow. Journal of Aerosol Science,

under revision after review.

Algorithm of the Monte Carlo simulation

Resuspension modeling by Wind Turbulence



Wind tunnel Experiment

Wind

Wind tunnel Microscope

with camera

Cross-section: 20mm X

200mm

The wind tunnel is 3m long

before the test section to

have a fully developed

turbulence at the test

section. The particles were

assumed to be in the viscous

sub-layer.

Test

section

The particles were aerosolized using a nebulizer

and deposited on a substrate. The substrate was

put in the test section for the experiment



Wind tunnel Experiment Wind

direction

51μm PS

particles on

acrylic

substrate in

the wind

tunnel

After 1min of about 20m/s

wind flow in the wind

tunnel

Wind turbulence

Force acting on

the particle

The particle resuspends when the moment

is larger than a critical value.

Some particles

were resuspended

from the

substrate

P

dp

x

a

b

Fa

FL

FD

mg



• Different thoughts between medical community and engineering community

Collaboration

between

different

expertise Scientists

Education

Architects,

engineers

Medical

expert,

clinicians

Final Remark Workplace and Indoor Aerosols 2012


Documents

and The Spread of Airborne Infectious Disease Indoor · in the spread of infectious disease; ... The size and duration of air-carriage of respiratory droplets and droplet-nuclei