NIOSH Pilot Research Program 2010-2011

October 13-14, 2011

Aravind Kishore (P.I., Graduate Student)Urmila Ghia (Mentor, Professor)

Santosh Konangi (Graduate Student) Naveen Goyal (Graduate Student)

Computational Fluid Dynamics Research Lab (CFDRL)School of Dynamic Systems

University of Cincinnati, Cincinnati, OH 45221

Reduction of Health-Care Worker Exposure to Pandemic Flu Virus in Hospital Rooms

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Presentation Outline

Research Objective

Specific Aims

Solution Methodology

Results

Conclusions

Future Work

Acknowledgements

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Inlet vent

Lights (on ceiling)

Main Exhaust

Television Patient (Inclined)

Patient’s Bed

CouchCupboard

Main Door

Health Care Worker

Bathroom door

Schematic of a Typical Hospital Room (Top View)

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Motivation

Air-borne pathogens spread when an infected patient coughs.

Investigate use of engineering control of ventilation systems to contain the airborne infection within the hospital room, and also better protect the Health Care Worker (HCW) present in the room.

Objective

Determine airflow patterns in a regular patient room and an Airborne Infection Isolation Room (AIIR) at a local hospital.

Evaluate effectiveness of the ventilation systems in mitigating Health-Care worker (HCW) exposure to air-borne infections.

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Specific Aims

1. Gather relevant information and design parameters for a typical patient room and an Air-borne Infection Isolation Room (AIIR) at a local hospital in Cincinnati.

2. Construct a CAD (Computer Aided Design) model of the rooms with the physical items like the bed and furniture.

3. Generate computational grids for the CAD model developed in Aim 2 above.

4. Apply appropriate boundary conditions, calculated from the valuesmeasured in Aim 1.

5. Solve the Navier-Stokes equations for the flow field, and track the cough particles using a Lagrangian Particle tracking scheme.

6. Analyze results and recommend alternate ventilation-system configurations that will reduce the risk of exposure of the HCW to cough droplets.

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Data Measured at Local Hospital

Negative Pressure Room Patient Room 1. Volume Flow Rates: SCFM ACFM SCFM ACFM

Bathroom Door ClosedMain Supply Vent 190 202.114 212 227.246Main Exhaust Vent 470 502.143 159 170.436Bathroom Exhaust Vent 65 64.103 68 72.891

Deficit: -345 -364.132 Deficit: -15 -16.081

Bathroom Door OpenMain Supply Vent 190 218Main Exhaust Vent 450 159Bathroom Exhaust Vent 65 68

Deficit: -325 Deficit: -92. Inflow Velocities Around Main Door

RHS gap 340 ft/minLHS gap 390 ft/minTop gap 350 ft/min

3. Pressure Inside the room

Bathroom Room Door Closed 28.9313 in. Hg 28.9072 in. Hg

Bathroom Room Door Open 28.9385 in. Hg 28.9070 in. Hg

Hallway Pressure 28.9187 in. Hg 28.9075 in. Hg

Location of pressure monitor Inside the Room (on the Ceiling)

Distance from side wall 24 in. Distance from Main door 5 in.

SCFM – Standardized Cubic Flow Rate/Minute

ACFM – Actual Cubic Flow Rate/Minute

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AIIR layout

Patient’s BedPatient (Inclined)

Light

Television

Bathroom

Inlet Vents

Couch

Cupboard

Window 2

Window 1 (facing corridor)

Main Door to Corridor

Leakage Gaps around the door

Main ExhaustThrough ceiling

Leakage Gaps around bathroom door

CPU on the wall

Health-Care Worker

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Regular Patient Room layoutTelevision

Window 1 (facing corridor)

Main Door

Leakage Gaps

around MainDoor

Main Exhaust

Patient’s Bed

Light

Couch

CupboardWindow 2

(facing outside )

Leakage Gaps around bathroom door

Patient (Inclined)

Health Care Worker

Inlet Vent with

Diffusers

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Solution Procedure

Unsteady, 3D, Incompressible Navier-Stokes equations are solved. Lagrangian Discrete Phase Model (DPM) model is used to track the

discrete cough droplets. Droplet collision and break-up taken into account.

Droplets are allowed to “coalesce” Droplets are “trapped” on striking solid surfaces;

“escape” on reaching exhaust vents. Solution at each time step is considered converged when scaled

residuals of mass and momentum conservation equations reach the order of 10-6.

The finite-volume based flow solver FLUENT is used. Grids constructed consisted of multi-million cells, and time step

chosen for transient simulation is 0.001 seconds.

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Modeling considerations and Boundary Conditions

Cough:

Mouth is 3 cm. in diameter (Ref. 1).

Duration of cough and velocity of air-droplet mixture obtained from Ref. 2. Mean Peak Flow Rate: 300 lit/min. Average Cough Volume: 2.4739 lit. Stroke Length: 3.5 m. Average Velocity: 6.9 m/s.

Time interval of one cough occurrence: 0.5 seconds Mixture of cough droplets and air is “injected” from patient’s mouth for a

duration of 0.5 seconds.

Size of cough droplets: 1 μm. Ref. 1: VanSciver, M., “Particle Image Velocimetry of Human Cough,” M.S Thesis,

Mechanical Engineering Dept., Univ. of Colorado, Boulder, CO.

Ref. 2: Mahajan, R.P., Singh, P., Murthy, G.E., Aitkenhead, A.R., 1994, Relationship Between Expired Lung Volume, Peak Flow Rate and Peak Speed Time During a Voluntary Cough Maneuver," British Journal of Anaesthesia, 72(3), pp. 298-301.

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HCW and Patient Model

Ref. 3: NASA/SP-2010-3407, Man-Systems Integration Standard,, “Anthropometrics and Biomechanics,” Vol. 1, Human Integration Design Handbook (HIDH), 2010.

Dimensions (Ref. 3):

Head: 0.38 x 0.16 x 0.283 m

Trunk: 0.5 x 0.25 x 0.652 m

Hands: 0.1 x 0.1 x 0.783 m

Legs: 0.13 x 0.13 x 1.05 m

Mouth: 3cm. diameter

Patient lies in bed, inclined at 45o

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Inlet Diffuser Configuration

Towards PatientAway from Patient

Linear Slot Diffuser

Pattern Controllers

4 inlet slots

Inflow angle: 45o (Ref. 4)

Patient

HCW

Ref. 4: Chen and Srebric, “Simplified Numerical Models for Complex Air Supply Diffusers,” 2002

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ResultsDispersal of cough-droplets during a patient-cough – droplets initially symmetric about the patient’s mouth

t = 0.1 s t = 0.15 s

t = 0.2 s t = 0.25 s

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t = 0.35 st = 0.30 s

t = 0.40 s t = 0.50 s

Results (contd.)

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Comparison of cough-droplet dispersal in the AIIR and patient room: droplets follow the airflow patterns set-up by the ventilation systems

AIIR Regular Patient Room

t = 5 s t = 5 s

t = 15 s t = 15 s

AIIR Regular Patient Room

t = 25 s t = 25 s

t = 35 s t = 35 s

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Key Observations and Conclusions

Isolation Room:

Air flow pattern is ‘from the patient, towards the HCW’ cough droplets are carried towards the HCW.

Main exhaust on ceiling: draws air towards it. location causes droplets to remain airborne for a long time.

Cough droplets from the patient move upwards, and remain airborne above the HCW. At 35 seconds after the cough, most droplets still remain suspended in air above the

HCW.

Patient Room:

Air flow pattern is ‘from the patient, towards the HCW’ cough droplets move across the HCW, on to the left side.

Most cough droplets are present in the region near the HCW and patient bed. Major portion of cough droplets either settle on the floor or are seen at a level lower than

the bed (contrary to the isolation room where most droplets are airborne).

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Key Observations and Conclusions (Contd.)Isolation Room:

Flow pattern seems to be effective in containing the infection within the room, not allowing it to spread to hallway/adjoining areas.

HCW is exposed to infection from patient: Air flows from patient towards HCW, carrying emitted cough/infection. Cough droplets are not removed from vicinity of HCW immediately.

Room Type HCW Protection ContainInfection within

RoomIsolation Room

Patient Room

Patient Room:

Similar to Isolation room, HCW is exposed to infection: Most cough droplets dispersed in the vicinity of HCW/patient

Unlike isolation room, droplets reach the floor, or are suspended in air in level with patient’s bed.

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Proof of Concept - Alternate Ventilation Configuration Inlet vent placed on the ceiling, above foot of patient bed.

Exhaust vent placed behind head of patient bed, and close to the floor.

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Preliminary Recommendations Ground Level Exhaust(s) near patient’s bed

Repositioning Health Care Worker (HCW) “upstream” of patient

Future work

Conduct a grid-independence study.

Perform numerical simulation of the flow pattern in the patient room and the AIIR with alternate ventilation arrangements.

HCW

Patient

Air-flow direction

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Acknowledgements

NIOSH Pilot Research Program (PRP) for funding this study

Dr. Amit Bhattacharya

Cyndy Cox

Colleagues at Computational Fluid Dynamics Research Lab, UC

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Thank You!