What We Are Learning from COVID-19 and How it Could Impact Transportation Planning in the San Diego RegionBoard of Directors Meeting | July 24, 2020

2

Regional Plan and Transportation Projects: State and Federal Laws

Climate change and air quality: greenhouse gas emissions, smog, localized air pollution

Social equity: compliance with federal civil rights requirements (Title VI) and environmental justice considerations

SB 743: shift to vehicle miles traveled to evaluate impacts of transportation projects

3

Learning from the COVID-19 Crisis:Re-envisioning Transportation Investments

4

Auto Crisis

Sub-Prime Mortgage Crisis

Global Financial Crisis

Economic Crises in the 21st Century R

eces

sion

Gre

at

Rec

essi

on

CO

VID

-19

Rec

essi

on

2001

2000

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

CoronaVirus“Dot-Com”

Bubble

September 11Attacks

Housing Market Bubble

5

Unemployment

Communities

Economic Sectors

Small Business

Taxable Sales

COVID-19 Impacts Many Aspects of the Lives and Communities in our Region

CoronaVirus

• Families• Geographies• Mental Health• Race & Ethnicity• Transportation

• Tourism & Entertainment• Hospitality• Restaurants/Food & Beverage• Retail

• Closures• Layoffs• Inability to pay bills

• Reduction in Savings• Inability to Pay Mortgage• New Career

• Sales Tax Revenue• Local Jurisdictions• TransNet Revenue

6

Tracking the Reopening

Pre-Covid March April May June July

Unemployment 3% 3% 4% 5% 10% 15% 18% 21% 22% 24% 25% 23% 22% 20% 19% 17% 16% 14%

VMT 100% 101% 93% 70% 54% 54% 49% 54% 58% 62% 66% 69% 72% 72% 75% 81% 83% 85% 81% 84%

Overall Mobility DataRetail and Recreation 100% 103% 98% 71% 54% 55% 49% 45% 41% 46% 51% 51% 54% 57% 60% 66% 67% 67% 69% 69%

Grocery and Drugstore 100% 102% 108% 102% 79% 79% 73% 75% 80% 83% 90% 88% 89% 90% 91% 93% 92% 91% 93% 88%

Foot traffic by type of businessSupermarket 100% 100% 123% 92% 75% 75% 68% 66% 70% 71% 78% 72% 75% 75% 76% 75% 76% 75% 78% 71%

Apparel Stores 100% 96% 81% 35% 23% 22% 20% 21% 23% 25% 26% 26% 29% 37% 45% 58% 60% 61% 57% 55%

New Car Dealers 100% 93% 84% 55% 48% 44% 36% 42% 50% 51% 55% 60% 66% 66% 66% 67% 68% 74% 68% 66%

Building Material and Supply 100% 95% 93% 72% 73% 75% 54% 69% 84% 88% 90% 92% 94% 96% 97% 96% 92% 98% 91% 90%

Home Garden and Equipment 100% 100% 78% 61% 71% 76% 52% 72% 91% 106% 123% 123% 126% 119% 113% 114% 117% 119% 100% 109%

Personal Care Services 100% 88% 76% 49% 40% 39% 31% 33% 39% 40% 42% 43% 44% 49% 52% 52% 51% 55% 58% 58%

Golf Courses and Country Clubs 100% 90% 74% 41% 30% 32% 20% 23% 28% 34% 40% 44% 51% 54% 59% 64% 72% 69% 70% 67%

Fitness and Rec Sports Centers 100% 99% 84% 36% 24% 23% 19% 20% 23% 26% 28% 29% 32% 34% 38% 46% 49% 53% 50% 50%

Airport 100% 96% 80% 40% 15% 10% 7% 6% 8% 9% 11% 13% 17% 19% 20% 24% 26% 31% 34% 38%

Restaurants 100% 98% 84% 39% 33% 33% 28% 32% 35% 39% 41% 41% 46% 51% 55% 61% 61% 63% 64% 63%

Hotels 100% 91% 76% 38% 26% 23% 18% 19% 23% 32% 34% 35% 41% 45% 45% 57% 57% 63% 68% 66%

OthersRestaurant Reservations 100% 99% 70% 13% 0% 0% 0% 0% 0% 0% 0% 0% 2% 18% 23% 30% 36% 43% 36% 34%

SANDAG is monitoring key variables to determine how far each one is from returning back to normal (pre-COVID-19 levels)

Source: SANDAG based on Applied Geographic Solutions, Inc., Thousand Oaks, California; Caltrans PeMS, Google mobility, SafeGraph COVID-19 Response Dataset - Weekly Patterns

7

Significant Impact on Taxable Sales

Visits to restaurants, cafes, shopping centers, theme parks, museums, libraries, and movie theaters

-70-60-50-40-30-20-10

01020

2/15 3/1 3/16 3/31 4/15 4/30 5/15 5/30

San Diego Regional Economy

$

$200,000,000

$400,000,000

$600,000,000

$800,000,000

$1,000,000,000

$1,200,000,000

$1,400,000,000

3/9 3/16 3/23 3/30 4/6 4/13 4/20 4/27 5/4 5/11 5/18 5/25 6/1 6/8

PRE-COVID-19

MARCH AVERAGE, -25%

APRIL AVERAGE,-44%

MAY AVERAGE,-35%

San Diego Gross Regional Product

-7.1%

4.7%4.1% 2.6% 2.2%

2.0%

2018 2019 2020 2021Source: BEA, SANDAG estimates

Source: SANDAG

Source: Google mobility report

8

UnemploymentImpact of COVID-19 Pandemic and Economic Crisis

9

Population and Employment in the San Diego Region

1,000,000

1,100,000

1,200,000

1,300,000

1,400,000

1,500,000

1,600,000

1,700,000

Jan2000

Jan2001

Jan2002

Jan2003

Jan2004

Jan2005

Jan2006

Jan2007

Jan2008

Jan2009

Jan2010

Jan2011

Jan2012

Jan2013

Jan2014

Jan2015

Jan2016

Jan2017

Jan2018

Jan2019

Jan2020

# Employed Civilian Labor Force

Peak(Jul-07)

Recovery (Nov-13)

76 Months

120 Months

Source: US Bureau of Labor Statistics (BLS), All Employees: Total Nonfarm in San Diego-Carlsbad, CA (MSA); SANDAG 2019 Estimates (2010-2019), SANDAG 2010 Intercensal Population and Housing Estimates (2000-2009)

Gre

at

Rec

essi

on

COVID-19 Stay Home Order

Trough(Mar-10)

10

March 7, 2020 May 9, 2020 June 27, 202014.3% Avg3.3% Avg 25.0% Avg

Impact of COVID-19 on Employment in the San Diego Region

11

Unemployment EstimatesNumber of Unemployed and Rate

3.1% 3.3% 3.6%4.5%

9.9%

14.6%

18.0%

20.7%22.3%

23.9%25.0%

23.5%21.7%

20.1%18.6%

17.0%15.7%

14.3%

0%

5%

10%

15%

20%

25%

30%

Une

mpl

oym

ent R

ate

52,000 56,000

61,000 77,000

169,000

248,000

305,000

351,000 379,000

407,000 425,000

399,000 369,000

341,000 315,000

289,000 266,000

243,000

Source: Applied Geographic Solutions, Inc., Thousand Oaks, California, Weekly Release July 6, 2020

12

San Diego Region Employment by Race and Ethnicity and Frontline WorkersShare of ethnic group in selected industries relative to their share of all employed residents

Esse

ntia

l -fro

ntlin

eN

on-e

ssen

tial

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00

Other frontline

Health Care

Child Care and Social Services

Grocery, Convenience, andDrug Stores

Retail

Food Service

Personal Care

Other (not frontline or highcontact)

Under-represented Over-representedBlack Hispanic Asian White

Asian over-represented

Asian over-represented

Hispanic over-represented

Hispanic over-represented

Hispanic over-represented

Hispanic over-represented

Hispanic over-represented

Black over-represented

Black over-represented

Black over-represented

SANDAG estimates based on Census Bureau ACS PUMS 5 Year 2014-2018 and the methodology by Hye Jin Rho, Hayley Brown, and Shawn Fremstad (2020) approach. See https://cepr.net/a-basic-demographic-profile-of-workers-in-frontline-industries/. Other frontline include employees in Public Transit, Trucking, Warehouse, and Postal Service and Building Cleaning Services.

13

CommunitiesImpact of COVID-19 Pandemic and Economic Crisis

14

Communities Most Impacted as of May 30An assessment of communities most impacted by both COVID-19 cases and unemployment

• 91910 (Chula Vista N)• 91911 (Chula Vista S)• 91917 (Dulzura)• 91932 (Imperial Beach)• 91950 (National City) • 91977 (Spring Valley)• 91978 (Rancho San Diego)• 92020 (El Cajon)• 92021 (El Cajon)• 92102 (Golden Hill)• 92105 (City Heights)• 92113 (Logan Heights)• 92114 (Encanto)• 92115 (College)• 92139 (Paradise Hills)• 92154 (Nestor)• 92173 (San Ysidro)

15

COVID-19 Cases and Estimated Unemployment by Race and Ethnicity

Hispanic

AsianWhite

Black

16

Impact of COVID-19 and Unemployment by Race and Ethnicity in the San Diego Region

67%

52%

45%

70%

49%

42%43%

32%

24%

44%

18%14%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Black Hispanic Asian White

Unemployment COVID-19 CasesUnemployment and

COVID-19 Cases

Source: SANDAG Annual Estimates 2019; Applied Geographic Solutions, Inc., Thousand Oaks, California; County of San Diego, Health and Human Services Agency

17

Economic SectorsImpact of COVID-19 Pandemic and Economic Crisis

18

San Diego Region Employment by Key Economic Sector

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

13%

10%

8%

11%

9%

7%

16%

16%

5%3%2%

Tourism

Innovation

Military

Healthcare

Education

Government

Retail

Finance, Insurance, Real EstateManufacturingConstructionTransportation

High Impact

TourismRetailTransportation

Moderate Impact

HealthcareEducationGovernmentManufacturing

Low Impact

InnovationMilitaryFinance Insurance Real EstateConstruction

31%

37%

32%COVID-19 Impacts

31%

27%

42%

19

80

90

100

110

120

130

92

113

125127

123

100

Employment Sector Forecast

Source: CA Employment Development Department (EDD), Labor Market Information Division, Quarterly Census of Employment and Wages; SANDAG

Supporting Sectors• Health Care• Education• Government

Driving Sectors• Tourism• Innovation• Military

Traditional Sectors• Retail/Wholesale

Trade• Professional• Construction• Manufacturing• Transportation &

Utilities2007Peak

2010Trough

2014Recovery

2019

Inde

x 20

07 =

100

This forecast assumes about a loss of 100,000 jobs in 2020 resulting in 9% unemployment rate

20

COVID-19 Impacts to Local Industries

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

1/20 2/10 3/2 3/23 4/13 5/4 5/25 6/15

General Retail

Apparel Stores Department Stores

Florists Furniture and Appliance Stores

Pharmacies Recreation Products

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

1/20 2/10 3/2 3/23 4/13 5/4 5/25 6/15

Transportation

Auto Dealers Auto Repair/Maintenance Gas Stations

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

1/20 2/10 3/2 3/23 4/13 5/4 5/25 6/15

Food and Beverage

Coffee and Snack Bars Fast Food Restaurants

Grocery Stores Sit Down Restaurants

-100%

-80%

-60%

-40%

-20%

0%

20%

40%

1/20 2/10 3/2 3/23 4/13 5/4 5/25 6/15

Construction Materials

Home and Garden Equipment Repair and MaintenanceHome Centers/Hardware Stores

Source: SafeGraph COVID-19 Response Dataset - Weekly Patterns, v2

Down 35% Down 35-40%

Down 25-45%

Up 10-15%

21

High-Contact-Intensity Occupations

387,950 Jobs27%

Low contact-intensity

702,360 Jobs49%

Medium contact-intensity

337,570 Jobs 24%

High-contact-intensity

-

50,000

100,000

150,000

200,000

250,000

300,000

350,000

105,550

56,16024,83092,470

58,560

337,570 High Contact-Intensity JobsRequiring Close Contact by SectorHealthcare – Moderate Job LossMost considered “essential workers” job loss in non-essential healthcare, e.g. dentistry, elective surgeries

Education – Moderate Job LossTechnology like Zoom, enables remote learning and allows for social distancing

Transportation – High Job LossAirline workers, taxi drivers, chauffeurs, delivery drivers and other occupations in transportation are significantly impacted

Food & Beverage Services – High Job LossRestaurant and bar closures, catering companies, social events canceled, significantly impact occupations in this sector

Personal care and services – High Job LossNon-essential services requiring close proximity like fitness workers, childcare, nannies, barber shops, hair dressers, manicurists ordered to curtail operations.

22

Small BusinessImpact of COVID-19 Pandemic and Economic Crisis

23

Impacts to Small Business in San Diego Region

76%72%

67%

61%

53% 51%47%

39% 41%

4% 5%10% 11% 10%

15%

22% 25%21%

0%

10%

20%

30%

40%

50%

60%

70%

80%

5/2 5/9 5/16 5/23 5/30 6/6 6/13 6/20 6/27

Change in Revenuein the Last Week

Decreased Revenue in the Last Week Increased Revenue in the Last Week

Source: U.S. Census Small Business Pulse Survey, Week Ending June 27, 2020

24

COVID-19 Impact on Small Business in San Diego Region

73%

25% 20%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Paycheck ProtectionProgram

Economic InjuryDisaster Loans

Not requested financialassistance from any

source since March 13,2020

Since March 13, 2020, has this business requested financial

assistance from any of the following sources?* Select all that apply:

* Some small businesses applied for both PPP and Economic Injury Disaster Loans Source: U.S. Census Small Business Pulse Survey, Week Ending June 27, 2020

15%

3%

82%

Overall, how has this business been affected by

theCOVID-19 pandemic?

Large & ModerateNegative Effect

Little to No Effect

Large & ModeratePositive Effect

25

Taxable SalesImpact of COVID-19 Pandemic and Economic Crisis

26

Impact of Recessions on Taxable Sales

0

10

20

30

40

50

60

7019

9019

9119

9219

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

0320

0420

0520

0620

0720

0820

0920

1020

1120

1220

1320

1420

1520

1620

1720

1820

1920

2020

21

Calendar Year

6 ½ years to recover to 2007 level

“Moderate”Recession

“Severe”Recession

“Mild”Recession

Billio

ns o

f Dol

lars

In Y

ear o

f Col

lect

ion

1991

Rec

essi

on

2001

Rec

essi

on

Gre

at R

eces

sion

CO

VID

-19

Rec

essi

on

Down 13%

27

COVID-19 Impact on San Diego Region Taxable Retail Sales

-18%

-71%

-47%

-28%

-5%

-36%

-8%

-54%

-50%

-14%

-82%

-57%

-19%

-25%

-48%

-24%

-67%

-57%

0 0.2 0.4 0.6 0.8 1 1.2

Food Market and liquor stores

Apparel Stores

Service Stations

Department Stores

Construction

Auto repairs and sales

Other retail

Restaurants

Business To Business

Billions of Dollars

Pre-COVID April May-19

Other Retail

Auto Repairs and Sales

Food Market and Liquor Stores

28

RecoveryImpact of COVID-19 Pandemic and Economic Crisis

29

Economic Recovery Outlook

2017 2018 2019 2020 2021 2022 2023 2024 2025 2026Pre COVID-19 Forecast updated V-long 3-month V-long 4 monthsU-4 months Oxford Economics 6/9 IHS 6/4CBO 7/2 Moodys 6/10 Wells Fargo 6/9Goldman Sachs 6/14 Deloitte 6/15 The economist/EIU 6/16FED 6/10 OECD 6/10 Conference Board 6/10

Fiscal Year

Moderate 4M(V-Long)

Moderate 3M(V-Long)

Moderate 4M(U)Pre-COVID-19

Possible lasting effects beyond 2026• Discouraged workers leaving the workforce• Educational disruptions (students drop out rates)• Less investment in the capital stock• Existing capital less productive given restrictions• Real Estate, Commercial Leasing

Shape of the recovery• V ruled out• Assumption: No return to “normal” until a vaccine is available• Most Likely Scenario: V long or U long depending upon the

speed at which all businesses can reopen

30

TransportationImpact of COVID-19 Pandemic and Economic Crisis

31

Transit Ridership

Trolley MTS Buses COASTER SPRINTER BREEZE

March April May

2020 decrease in ridership (compared to 2019)

-120.00%

-100.00%

-80.00%

-60.00%

-40.00%

-20.00%

0.00%

March April May June

32

• 20% of people who ride transit to work have no vehicles available

• 79% of people who ride transit to work travel 30 minutes or longer

• The median transit travel time is 51 minutes, which is double the travel time for people who drive to work

Essential Workers Depend on Transit

33

• 42% of survey respondents reported that they used transit before and after COVID-19

• 36% said they did not use transit before and will not in the future

• 18% did not use transit before but stated they would after a vaccine

• 4% said they used transitbefore but not after COVID-19

Travel Around the San Diego Region Survey: Public Transit

34

Freeway Travel Trends

Average Decreases in Daily Traffic Volumes at Freeway Hotspots in the San Diego Region (2019 to 2020)

-27%

-43% -42%

-50%

-42% -40%

-33% -31% -29%-25% -23% -21% -20%

-17% -16% -18%

-60%

-50%

-40%

-30%

-20%

-10%

0%

May - June June - JulyApril - MayMarch - April

Source: Performance Measurement System (PeMS), Caltrans

35

Vehicle Miles Traveled

-44%-40%

-30%

-22%

-50%

-45%

-40%

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%Month 1 Month 2 Month 3 Month 4

Percent Change VMT 2019 to 2020

36

Northbound POV CrossingsMay 2020:

-44% below monthly average (Jan 2019-Feb 2020) increase from April 2020 to May 2020:+17% 0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May

2019 2020

Tecate‐TecateOtay Mesa‐Mesa de OtaySan Ysidro‐Puerta México/ Ped West‐El Chaparral

Note: Monthly averages are for Jan 2019-Feb 2020 period. Travel restrictions at the border were implemented in March 2020.

Source: U.S. Customs and Border Protection (CBP)

0

250,000

500,000

750,000

1,000,000

1,250,000

1,500,000

Tecate‐TecateOtay Mesa‐Mesa de OtaySan Ysidro‐Puerta México/ Ped West‐El Chaparral

May 2020:

-65%below monthly average (Jan 2019-Feb 2020)increase from April 2020 to May 2020: +44%

Northbound Pedestrian Crossings

Border Crossing Volumes

37

Travel Around the San Diego Region Survey: Vehicle Travel and Telework

• 89% reported driving less during the health crisis– 81% expect their vehicle travel to increase

over the next six months

• 78% reported using online shopping and delivery more– 42% expect to continue at a higher rate

• 48% reported driving less for work because of telework– About half of those who teleworked said

they saw it continuing

89%

78%

48%

38

said they have had employees who have teleworked during the COVID-19 health crisis

Employer Telework Trends During the COVID-19 Health CrisisOf the 137 employers surveyed

55%

When asked if they would offer telework after COVID-19

26%Said yes

28%46%Said no Said maybe

39

Employers' Future Telework Plans

Of those companies who said they would offer telework post-COVID-19, 9% said they would offer it full-time

The most common response (71%) was to offer telework 2-3 times a week

When asked what percent of their workforce would continue to telework, the most common response was less than 25%

40

• Increased job satisfaction (67%)• Productivity (55%)• Improved work / life

balance (55%)• Helping the

environment (50%)• Cost savings in leasing

commercial space (30%)

Employers' Top 5 Reasons for Offering Telework

41

What is the Potential for Telework in the San Diego Region?

61% Stock photo of construction worker?

Stock photo of grocery worker?

64%

of occupations are not conducive to telework

of occupations are considered essential jobs– 42% of essential jobs

are not conducive to telework

42

Jobs that Can be Done at HomeTypically Earn Higher Wages

43

Who Teleworks in San Diego Region?

44

Telework Targets in Regional Plans

0%

5%

10%

15%

20%

25%

30%

2011 RP targets 2015 RP targets 2019 RTP targets Proposed 2021 RPtargets

2035 2050

Alwaysworks

at home (7%)

*2016 Regional Transportation Study (baseline)

Baseline*

Teleworksat least

1 day/week (8%)

45

• 23% of households earning less than $50,000/year do not have a broadband subscription

• 20 – 40% of students in many local districts are under-connected or lack home internet access

• 42% of people who live in the County’s rural areas have fixed internet, versus 97% of the people who live in urban areas

Broadband Connectivity and Internet Access

46

• 14% are biking more – 85% will continue biking more

for recreation, exercise,shopping, and errands

• 50% are walking more – 82% will continue walking

more for recreation, exercise,shopping, and errands

Travel Around the San Diego Region Survey: Active Transportation

47

• 91% increase in bike volumes on eight regional bikeway corridors

• Data collected May 2020 and compared to May 2019 volumes

Source: SANDAG Eco-Counters

Cycling on the Rise in the Region

48

San Marcos Inland Rail Trail +211% Solana Beach Coast Highway +109%

Rose Canyon Bike Path +107%Chula Vista Bayshore Bikeway +158%

Cycling on the Rise in the Region

University Avenue +88% 4th & 5th Avenues +63%

Landis Street +52% 30th Street +54%

Source: SANDAG Eco-Counters

49

• SANDAG Shared Streets Pilot Program awarded$95,000 to 11 jurisdictions to create safe spaces for biking, walking, scooting, and more

Shared Streets

50

Toward a more inclusive, sustainable and resilient economy and society

What We Are Learning from COVID-19 and How it Could Impact Transportation Planning in the San Diego RegionBoard of Directors Meeting | July 24, 2020

This relates to Item No. 12

This relates to Item No. 12

This relates to Item No. 12

This relates to Item No. 12

This relates to Item No. 12

This relates to Item No. 12

This relates to Item No. 12

This relates to Item No. 12