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COVID-19 Threatens Nation’s Largest Public Transit Systems

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  1. Assess the pandemic trajectory using advanced modeling that naturally captures the empirically observed asymmetry in cases over time;
  2. Notice later-occurring (second wave) cases that arise from new infections and variations in institutional records management (such as expanded testing, reclassification, double-counting of test results, expansion to include probable cases, and other factors); and
  3. Understand delays caused by distance, especially in large areas with multiple population centers.

Early September COVID-19 Commentary:
COVID-19 Threatens Nation’s
Largest Public Transit Systems

Plummeting ridership and tax revenues lead to unprecedented budget shortfalls

September 3, 2020–Chicago, IL: As COVID-19 swept across many of the county’s major metropolitan areas this past spring, public transportation ridership and fare revenues plummeted to unprecedented lows. Now, as these same cities look toward a future with fewer cases, their transit systems face mounting long-term budget shortfalls that must be addressed.

Brian Peterson, Anderson Economic Group’s director of public policy and economic analysis, notes that while COVID-19 case growth is slowing in many of these metropolitan areas, a return to full ridership and fiscal solvency is still a long way off for most public transit systems. “Despite a precipitous decline in farebox revenues, many transit agencies continued to operate at or near capacity over the past six months in order to maintain proper social distancing for riders,” Peterson said. “This model is not sustainable over the long term, and providers will have to grapple with what comes next. That will likely be a combination fare increases and service cuts, which could further discourage riders from returning to transit.”

The following commentary explores the progression of COVID-19 in the five metropolitan areas with the country’s largest public transit systems. We utilize our novel “two-wave” epidemiological model to chart historical data and project the spread of the virus in coming weeks (see below for charts).

New York City. In the New York City metropolitan area, COVID-19 cases peaked in mid-April before steadily declining over the following months. Case numbers have been consistently low since mid-June, and our current projections suggest that case numbers will remain low in the near future.

New York City’s Metropolitan Transportation Authority (MTA), which provided over 2 billion rides in 2019, has struggled to generate enough operating revenue to sustain its current operations and planned upgrades. Even as the city’s COVID-19 case numbers have fallen, MTA’s August subway ridership was down about 75% from the previous year. MTA is now projecting a $16.2 billion dollar deficit over the next four years.

Washington, D.C. In Washington D.C., COVID-19 cases reached an initial peak in mid-May. Cases then declined for two months, when the region saw the beginning of a second wave of infections. Our model projects that this second wave peaked in early August, and that new daily case counts will decline in the coming weeks.

Washington Metropolitan Area Transit Authority is the nation’s second largest public transit system by ridership and is losing an estimated $2 million each weekday due to the pandemic. In May, the agency issued a new 2021 budget with $1.2 billion dollars in cuts, including a reversal of earlier plans to increase late-night service.

Chicago. The Chicago area saw COVID-19 cases peak in early May. The number of new cases steadily declined until early July, when the city experienced a second wave of infections. Our model shows that this second wave peaked in mid-August, and our currently projections suggest that cases will continue to slowly decline.

In Chicago, regional transit agencies experienced a 60-70% decline in ridership in August compared to 2019 figures. The Chicago Transit Authority has projected a 64% decline in farebox revenues for this fiscal year, and the Regional Transportation Authority anticipates a $600 million deficit over the next two years for Metra, the region’s commuter rail agency.

Boston. COVID-19 cases peaked in mid-April in Boston and have remained low since early June. Our model shows there was a small second wave of infections in late July through August, and currently projects that the number of new cases will remain steady over the next several weeks.

The Massachusetts Bay Transportation Authority (MBTA), responsible for most public transportation in the Boston region, is facing a $400 million projected budget deficit next year. The two busiest MBTA train lines have seen an 85% decline in weekday ticket validations since June, relative to 2019 peak hours. The agency is gearing up for cost-saving measures, such as freezing new projects and potential fare increases.

San Francisco. The San Francisco metropolitan area saw relatively low COVID-19 case numbers in the spring but experienced a larger second wave that began in late June. The number of new cases in the region remains elevated and highly variable from day to day, resulting in insufficient data for us to reliably predict the path of the virus at this time.

The San Francisco Municipal Transportation Agency (SFMTA) is forecasting a ‘transit death spiral,’ as its light rail ridership collapsed by 70-90 % this summer due to the pandemic. SFMTA has experienced repeated service closures due to public health concerns and is set to lose more than $500 million of revenue over the next four years.

Further analysis and focused commentary will be added here as it becomes available.

About Anderson Economic Group

Anderson Economic Group, LLC, is a US-based research and consulting firm that specializes in economics, public policy, commercial damages, market analysis, and tax and regulatory policy. The firm, founded in 1996, is one of the most recognized boutique consulting firms in the US.

With over 20 years of experience in economic impact modeling, Anderson Economic Group is one of the original pioneers in assessing the economic impacts of higher education. To date, we have completed over 40 such analyses for small and large institutions across the country, including Big Ten institutions such as University of Michigan and Michigan State University.

Also available:The Costs & Consequences of the Coronavirus Pandemic: Three Lessons” presented to the Western Economics Association, June 26 Conference. Patrick Anderson’s analysis considers the dominance of empirical over simulation models, the huge cost of stay-at-home orders, and a discussion of the future of empirical models that includes a focus on AEG’s innovative two-wave models.

See the notes at bottom and the associated memorandum regarding a significant update to our forecasting methodology.

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Transit Cities

Modeling the COVID-19 Pandemic

Since February, Anderson Economic Group LLC, together with the data analytics firm Supported Intelligence, has been gathering data from multiple countries and U.S. states to model the path of the COVID-19 pandemic. We identified the situation as a crisis as early as our February 10 release, and began to release selected regional analyses in late March. Since then, we have implemented the following practices in our improved model:

  1. We use a two-wave generalized logistic model in conjunction with non-linear curve fitting.
  • We use an improved version of the same mathematical function used for disease growth (including but not limited to the SIR model).
  • Our improvements to the function include but are not limited to the ability to measure asymmetric growth, as well as secondary waves.
  • We compare results across multiple states and countries.
  1. We show the actual data.
  • We focus on a tangible concept: the number of people cases with the disease.
  • We show uncertainty, units, dates, and past prediction errors.
  • We use data compiled by the New York Times for most of the United States, and World-o-Meter for much of the rest of the world.
  1. We describe our methodology, data sources, and limitations.

See the memorandum describing the methods, data, limitations, and Terms of Use for this information.