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1 Understanding National Road Safety Performance Kavi Bhalla, PhD Assistant Professor Department of International Health Johns Hopkins Bloomberg School of Public Health

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Page 1: Understanding National Road Safety Performancetripp.iitd.ernet.in/assets/newsimage/Kavi_Safety_Performance.pdf · History of traffic deaths: UK, USA 0 1 2 3 4 5 6 7 8 9 0 10 20 30

1

Understanding National

Road Safety Performance

Kavi Bhalla, PhD

Assistant Professor

Department of International Health

Johns Hopkins Bloomberg School of Public Health

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History of traffic deaths: UK, USA

0

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1950 1960 1970 1980 1990 2000 2010

UK

De

ath

s (

tho

us

an

ds

)

US

A D

ea

ths

(th

ou

sa

nd

s)

USA

UK

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History of traffic death rates: UK, USA

33

USA

UK

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History of traffic death rates: UK, USA

44

USA

UK

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History of traffic death rates: UK, USA

55

USA

UK

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History of traffic death rates: OECD countries

6

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7

Why did road deaths rise and

fall in OECD countries ?

Three explanations:

1. Economic determinism

2. Risk transition

3. Paradigm shift & Transition to a policy era

Page 8: Understanding National Road Safety Performancetripp.iitd.ernet.in/assets/newsimage/Kavi_Safety_Performance.pdf · History of traffic deaths: UK, USA 0 1 2 3 4 5 6 7 8 9 0 10 20 30

8

Why did road deaths rise and

fall in OECD countries ?

Three explanations:

1. Economic determinism*

2. Risk transition

3. Paradigm shift & Transition to a policy era

* For a full critique: Bhalla, K. and Mohan, D., 2016, Understanding the road safety performance

of OECD countries, in Traffic Safety Matters, G. Tiwari, S. Mukherjee, and Mohan D (eds),

Taylor and Francis.

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History of traffic death rates: OECD Countries

9

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10

Road Death Rates and Income

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40

0 10000 20000 30000 40000

Road

TrafficDeathRate,p

er100000popula

on

Income,RealGDPpercapita(PPP)

OECDCountries

10

Environmental Kuznets Curve

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11

Road Death Rates and Income

0

5

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25

30

35

40

0 10000 20000 30000 40000

Road

TrafficDeathRate,p

er100000popula

on

Income,RealGDPpercapita(PPP)

OECDCountries

Road death rates will rise until 2047!

(Kopits & Cropper, World Bank, 2005)

India

(Now)

11

Environmental Kuznets Curve

Income, Real GDP per capita (PPP, $)

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Kuznets Hypothesis: Traffic injury Literature

• Soderlund N, Zwi, AB. Traffic related mortality in industrialized and less developed countries. Bulletin of the

World Health Organization. 1995.

• Van Beeck EF, Borsboom GJ, Mackenbach JP. Economic development and traffic accident mortality in the

industrialized world, 1962-1990. International Journal of Epidemiology. 2000;29(3):503–509.

• Kopits E, Cropper M. Traffic fatalities and economic growth. Accident Analysis and Prevention.

2005;37(1):169–178.

• Garg N, Hyder A. Exploring the relationship between development and road traffic injuries: a case study

from India. The European Journal of Public Health. 2005;16(5):487–491.

• Bishai D, Quresh A, James P, Ghaffar A. National road casualties and economic development. Health

Economics. 2005;15(1):65–81.

• Paulozzi LJ, Ryan GW, Espitia-Hardeman VE, Xi Y. Economic development's effect on road transport-

related mortality among different types of road users: A cross-sectional international study. Accident

Analysis and Prevention. 2007;39(3):606–617.

• McManus W. The Economics of Road Safety: an International Perspective. University of Michigan

Transportation Research Institute, Ann Arbor, MI; 2007.

• Law TH, Noland RB, Evans AW. Factors associated with the relationship between motorcycle deaths and

economic growth. Accident Analysis and Prevention. 2009;41(2):234–240.

• Grimm M, Treibich C. Determinants of road traffic crash fatalities across Indian states. Health Economics.

2012;22(8):915–930.

• Nishitateno S, Burke PJ. The motorcycle Kuznets curve. Journal of Transport Geography. 2014;36:116–

123.

12

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13

Road Death Rates and Income

0

5

10

15

20

25

30

35

40

0 10000 20000 30000 40000

Road

TrafficDeathRate,p

er100000popula

on

Income,RealGDPpercapita(PPP)

OECDCountries

13Income, Real GDP per capita (PPP, $)

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14

Road Death Rates and Income

0

5

10

15

20

25

30

35

40

0 10000 20000 30000 40000

Road

TrafficDeathRate,p

er100000popula

on

Income,RealGDPpercapita(PPP)

OECDCountries

India

(Now)

14Income, Real GDP per capita (PPP, $)

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1515

Vietnam : NowVietnam: Motorizing by motorcycles

Source: www.flickr.com/photos/jkjohnson/3298451423

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Colombia: Motorizing by cars

Source: http://mikesbogotablog.blogspot.com/2014/10/will-subway-bury-bogota.html16

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17

Why did road deaths rise and

fall in OECD countries ?

Three explanations:

1. Economic determinism

2. Risk transition*

3. Paradigm shift & Transition to a policy era

*Bhalla, K., Ezzati, M., Mahal, A., Salomon, J., & Reich, M. (2007). A risk-based method for

modeling traffic fatalities. Risk Analysis, 27(1), 125–136.

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18

Imagine a motorizing society …

Increasing car ownership leads to fewer pedestrians

Stage 1 Stage 2 Stage N-1 Stage NStage 0 Stage N-2

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19

What happens to societal risk?Assumptions:

• r is the probability that a pedestrian will be killed by a given car

• car occupants are at negligible (zero) risk

0

0

0

0

0

0

r

r

r

r

r

0

Total 0 5r

Stage 1 Stage 2 Stage N-1 Stage NStage 0 Stage N-2

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20

What happens to societal risk?Assumptions:

• r is the probability that a pedestrian will be killed by a given car

• car occupants are at negligible (zero) risk

Rising risk Falling risk

0

0

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0

r

r

r

r

r

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2r

2r

2r

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2r

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Total 0 5r 8r 8r 5r 0

Stage 1 Stage 2

5r

0

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Stage N-1 Stage NStage 0

4r

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4r

0

Stage N-2

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21

Simulation Simulation

Historic

Data

Historic

Data

21

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22

Simulation Simulation

Historic

Data

Historic

Data

22

1. Risks to car occupants

2. There are always pedestrians

3. Interventions!

4. Other types of vehicles?

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2323

Dealing with mixed-mode motorization

• Pair-wise risks:

• scooters are at risk from cars, pedestrians, buses, other scooters

• environment is a risk-factor

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2424

Modeling deaths: in mixed-mode motorization

Probability of death:= Prob. of crash x Prob. of death in the event of a crash

deathcarped= ccar

ped. rcar

ped

ccarped = f (# of pedestrians, # of cars, vehicle attributes, driver

attributes, roadway infrastructure, systemic attributes)

rcarped = f (vehicle attributes, victim attributes, crash conditions,

post-crash medical care)

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2525

Modeling deaths: in mixed-mode motorization

1. Probability of crash: cveh1veh2

Assume perfect mixing of modes

ccarped= [K. (Number of cars)*(Number of pedestrians)]

CarM/cycle

Pedestrian

Bus

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2626

Pedestrian Motorcycles Cars Bus Environment

Pedestrian 0 0.040 0.080 0.135 0

Motorcycles 0.020 0.021 0.080 0.135 0.053

Cars 0 0.002 0.009 0.090 0.030

Bus 0 0 0.001 0.009 0.037

Environment N.A. N.A. N.A. N.A. N.A.

Modeling deaths: in mixed-mode motorization

2. Probability of death in event of crash: rthreatvictim

rcarbus

threat

vic

tim

Crash Fatality Rate Matrix

CFR in

single

vehicle

crashes

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27

Crash Fatality Rate matrixv

icti

m

threat

Full model :

deaths carped = [K . # Peds . # Cars] . rcar

ped

Pedestrian Motorcycles Cars Bus Environment

Pedestrian 0 0.040 0.080 0.135 0

Motorcycles 0.020 0.021 0.080 0.135 0.053

Cars 0 0.002 0.009 0.090 0.030

Bus 0 0 0.001 0.009 0.037

Environment N.A. N.A. N.A. N.A. N.A.

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28

Crash Fatality Rate matrixv

icti

m

threat

Full model :

deaths carped = [K . # Peds . # Cars] . rcar

ped

Realistic Motorization Scenarios

Pedestrian Motorcycles Cars Bus Environment

Pedestrian 0 0.040 0.080 0.135 0

Motorcycles 0.020 0.021 0.080 0.135 0.053

Cars 0 0.002 0.009 0.090 0.030

Bus 0 0 0.001 0.009 0.037

Environment N.A. N.A. N.A. N.A. N.A.

1.High Car Use

2.High Motorcycle Use

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2929

Motorization Scenarios(that are a bit more realistic)

High car use High Motorcycle use

• Include buses: 40% of all trips

• Each bus trip, requires a pedestrian trip

(i.e. there’re always a lot of pedestrians around)

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3030

Consider 2 Scenarios of Motorization

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Mo

dal S

ha

re

Proportion of trips that are motorized

Scenario: High Car Use

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Mo

dal S

ha

re

Proportion of trips that are motorized

Scenario: High Motorcycle Use

Pedestrians Pedestrians

Cars

Buses Buses

Motorcycles

Cars

Motorcycles

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3131

0

100

200

300

400

500

600

700

800

900

1000

0.0 0.2 0.4 0.6 0.8 1.0

De

ath

s

Proportion of trips that are motorized

Total Road Deaths

Scenario:High Car

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3232

0

100

200

300

400

500

600

700

800

900

1000

0.0 0.2 0.4 0.6 0.8 1.0

De

ath

s

Proportion of trips that are motorized

Total Road Deaths

Scenario: High Car

Scenario: High Motorcycle

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33

Crash Fatality Rate matrixv

icti

m

threatPedestrian Motorcycles Cars Bus Environment

Pedestrian 0 0.040 0.080 0.135 0

Motorcycles 0.020 0.021 0.080 0.135 0.053

Cars 0 0.002 0.009 0.090 0.030

Bus 0 0 0.001 0.009 0.037

Environment N.A. N.A. N.A. N.A. N.A.

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3434

0

100

200

300

400

500

600

700

800

900

1000

0.0 0.2 0.3 0.5 0.7 0.8 1.0

De

ath

s

Prop of trips that are motorized

Scenario:High Car-Use

Other Pedestrian

0

100

200

300

400

500

600

700

800

900

1000

0.0 0.2 0.3 0.5 0.7 0.8 1.0

De

ath

s

Prop of trips that are motorized

Scenario:High Motorcycle-Use

Other Pedestrian

PedestrianPedestrian

Other Other

0

100

200

300

400

500

600

700

800

900

1000

0.0 0.2 0.4 0.6 0.8 1.0

De

ath

s

Proportion of trips that are motorized

Total Road Deaths

Scenario: High Car

Scenario: High Motorcycle

34

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35

Why did road deaths rise and

fall in OECD countries ?

Three explanations:

1. Economic determinism

2. Risk transition

3. Paradigm shift & Transition to a policy era*

*Work in Progress

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36

Road Death Rates and Income

36

0

5

10

15

20

25

30

35

40

0 10000 20000 30000 40000

Road

TrafficDeathRate,p

er100000popula

on

Income,RealGDPpercapita(PPP)

OECDCountries

Income, Real GDP per capita (PPP, $)

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37

Road Death Rates and Income

37

0

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10

15

20

25

30

35

40

0 10000 20000 30000 40000

Road

TrafficDeathRate,p

er100000popula

on

Income,RealGDPpercapita(PPP)

19OtherOECDCountries

USA

UK

Income, Real GDP per capita (PPP, $)

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38

0

5

10

15

20

25

30

35

40

1950 1960 1970 1980 1990 2000 2010

RoadTrafficDeathRate,p

er100000popula

on

Year

Road Death Rates and Time

38

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What happened in time?

Time-Series Cross-Sectional Analysis

39

ln(drit ) =a +b1 ×gdpit + b2 ×gdp2

it + b3 ×urbit + b4 × popdensityit +ui + vt +eitéë

ùûage-sex-gps

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What happened in time?

Time-Series Cross-Sectional Analysis

40

ln(drit ) =a +b1 ×gdpit + b2 ×gdp2

it + b3 ×urbit + b4 × popdensityit +ui + vt +eitéë

ùûage-sex-gps

Kuznets Hypothesis

Country fixed-effects

Time fixed-effects

• Time-Series Cross-Section Methods following Beck & Katz

• Lagged dependent variable to account for serial auto-correlation

• Validation: in-sample & out-of-sample

• 16 separate models for age- sex- groups

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4141

-2

-1.5

-1

-0.5

0

0.5

1

1.5

1950 1960 1970 1980 1990 2000

Co

effic

ien

t o

f T

ime

What happens in time? Mortality effects: elderly

Female Male

Age 80+

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42

What happens in time?

19

72

-2

-1.5

-1

-0.5

0

0.5

1

1.5

1950 1960 1970 1980 1990 2000

Co

effic

ien

t o

f T

ime

19

72

Elderly

42

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4343

-2

-1.5

-1

-0.5

0

0.5

1

1.5

1950 1960 1970 1980 1990 2000

Co

effic

ien

t o

f T

ime

19

72

Elderly

Children

What happens in time?

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4444

-2

-1.5

-1

-0.5

0

0.5

1

1.5

1950 1960 1970 1980 1990 2000

Co

effic

ien

t o

f T

ime

19

72

Elderly

Young

adults

Children

Young

women

What happens in time?

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Mortality trends in OECD countries

45

Something happened!

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History of road safety in the US

• 1900 – 1950s:

– Road safety is about “nut behind the wheel”

– Research: primarily in driver psychology

• 1950s-1960s:

– Road safety: shifts towards biomechanical tolerance of human body

– Research: shifts towards engineering the vehicle

• mid 1960s:

– Ralph Nader writes “Unsafe at Any Speed”; GM’s response causes

scandal

– 1967 US Congress enacts Motor Vehicle Safety Act => NHTSA

• 1970s onwards:

– Increasing regulation of roads and road users => an era of interventions!

46

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Mortality trends in OECD countries

47

Paradigm Shift

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4848

• 1967 (September): Sweden shifts from left to right hand driving

• 1968: Sweden established a new authority, the Road Safety Agency

• 1975: Front seat belts become mandatory

• 1975: Helmet law for motorcyclists

• 1976: Driving test for motorcycle

• 1977: Daytime running lights

• 1978: Moped helmet

• 1979: Cycle light in nighttime

• 1982: All slow moving vehicles shall have a warning sign

• 1986: Reflectors on cycles (front, back and wheels)

• 1987: Speed fines increased

• 1988: mandatory seat belts for children

• 1990: Blood Alcohol Content limit lowered from 0.05 to 0.02%; Start trials with automatic speed enforcement

• 1994: Limit for serious intoxicated: 0.1 %; Number of random breath tests doubled; Speed limit enforcement by laser.

• 1995: Median steel wire barriers; (speed limit increased for heavy vehicles)

• 1996: airbags standard in all new cars;

• 1997: “Vision Zero” is taken by Parliament

• 1998: roadside steel wire barriers

• 1999: Seat belt law expanded (taxi drivers, lorry occupants); winter tyresmandatory in winter conditions

Policy history - Sweden

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Policy History: Sweden

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1999: winter tires mandatory in winter conditions

1968: New road safety agency established

1975: Front belts and helmet use mandatory1976: Driving tests for motorcycles

1977: Daytime running lights1978: Moped helmets required

1979: cycle lights required for night

1982: Signs for slow moving vehicles

1986: Reflectors on cycles

Speed fines increased: 1987

mandatory restraints for children: 1988

BAC limits lowered, 0.05 to 0.02%: 1990

Auto speed enforcement trials: 1990

# of random breath tests doubled: 1994

Median steel wire barriers: 1995Airbags standard in all new vehicles: 1996“Vision Zero” is adopted by Parliament: 1997

Roadside steel wire barriers: 1998

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Policy History: UK

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1970: Heavy vehicle: driving tests & limits on driving

hours1972: 16 years olds limited to riding mopeds

1974: helmets; vehicle lighting regulations

Mini roundabouts

introduced:1976

Helmet standards: 1977

Hvy veh hours adjusted: 1978Fog lamps on new vehicles

Higher stds for helmets: 1980

Braking stds for heavy veh: 1982

Front belt use mandatory: 1983

1984: Spray reducing devices: Trucks

1987: National road safety targets;

Slow vehicle amber lights

1991: Highway safety audits;

20 mph zones1992: 60 mph limiters, trucks

New traffic calming regulations: 1993

Speed limit lowered for buses/trucks: 1994Driving test strengthened: 1996

2000: New road safety

strategy & targets

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Policy History: Netherlands

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1971: Mandatory seat belts in new cars

1972: Mandatory helmets for motorcycles

1974: Speed limits reset; Alc limit set to 0.05%

1975: Mandatory helmets for mopeds

1976: Rules for children in cars (e.g.

forbidden on laps in front)

1977: Heavy vehicles, trailers must have

reflective markings

1979: Moped/bike pedal reflectors

1983: 30 km/h zones

Vehicle inspections required: 1985

Moped/bike side reflectors: 1987

Rear seatbelts fitted in new cars: 1990Belt use in lorries, vans, car rear seats:1992

1995: Speed limiters bus

& truck

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Lessons: Poor countries need not wait

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Paradigm Shift:Birth of institutions

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Summary: History of road safety performance

The “income” explanation• More cars kill more people road deaths initially rise with income

• At some income level countries begin to care about the rising death toll

and implement policies Road deaths later fall with income

The “mode shift” explanation• As people move from being pedestrians to car occupancy, total societal

risks rises initially due to threat from cars and later falls as pedestrians

are eliminated from the system.

The “policy era” explanation• Starting in the 1960s, countries established national road safety agencies,

gave them legislative “teeth”. Over successive years, interventions were

implemented, compliance was improved, deaths came down.

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For more information, please contact:

Kavi Bhalla, PhD

Assistant Professor,

Leon Robertson Faculty Development Chair

Department of International Health

Johns Hopkins School of Public Health

615 N. Wolfe Street, E8138, Baltimore, Maryland 21205

Phone: 954.849.8692, [email protected]

Thank You!