Category Archives: current

Visualizing the Progression of COVID-19 in the United States

Through 31 March 2020, the United States has tested over 1.1 million Americans for COVID-19 infections in all 50 states and the territories of Puerto Rico and the District of Columbia. The known results of that testing, including the number of positive, negative and pending test results for the SARS-CoV-2 coronavirus, the number of deaths, and also the reported cases severe enough to require hospitalization, are visualized below in the tower chart showing the daily progression of COVID-19 infections in the U.S. since 10 March 2020.

Daily Progression of COVID-19 in the United States, 10 March 2020 through 31 March 2020

In the following chart, we've combined the skyline tower charts illustrating the daily progression of positive COVID-19 infections, hospitalizations, and deaths for each of the 50 states and the territories of Puerto Rico and the District of Columbia, ranking each from worst to best as you read from left to right, top to bottom. All charts are presented covering the same period of time from 10 March 2020 through 31 March 2020 and use the same scale, with the width of the charts representing 0.5% of the state or territory's population, making is easy to quickly visualize in which states the coronavirus infections are concentrated and are spreading the fastest.

Progression of COVID-19 in the United States by State or Territory, 10 March 2020 - 31 March 2020

It appears from the available data that a number of states are not reporting their number of coronavirus-related hospitalizations, with New Jersey, Michigan, the District of Columbia, and Illinois standing out in that category among the top 10 states ranked by share of their population having been infected.

We're also well past the point where it is worthwhile to track the daily progression of COVID-19 in states whose governors have mandated business closures or stay-at-home orders for their residents. Also as of 31 March 2020, three out of four Americans are affected by these restrictions, which have spread far faster than the coronavirus.

Previously on Political Calculations


Update 31 March 2020: Thank you for scrolling all the way down to the bottom of this article! If you're viewing the original version of this article, here's where we will periodically post updates to the national tower chart presented above, or will link to newer posts in the series where you can find updates for all the charts.


Update 29 April 2020: Here's the latest update to the national tower chart showing the cumulative totals:

Daily Progression of COVID-19 in the United States, 10 March 2020 through 29 April 2020

The biggest changes in the daily numbers are coming from the Top 10 states. New York continues to have the largest number of confirmed cases, accounting for nearly a third of all confirmed cases in the U.S. and nearly two-fifths of reported deaths, with New York City and the surrounding counties that make up its greater metropolitan area having the largest share (counties in New Jersey adjacent to New York City have been similarly hard hit, with that state ranking second in the nation). Excluding the extremely high concentration of cases in this region, data from the rest of the U.S. is more similar to that being reported by Germany.

Also, an updated version of the skyline tower chart for individual states and territories is available here, with data through 28 April 2020.


Ranking the World for COVID-19 Coronavirus Cases

COVID-19 - Martin Sanchez via Unsplash: https://unsplash.com/photos/Tzoe6VCvQYg

Where is the worst country or region in the world to be in the world during the coronavirus pandemic?

Is the United States, which on 26 March 2020, surpassed the total number of cases reported in China? Is it Italy, which has seen over 9,000 deaths attributed to COVID-19 as of 27 March 2020? Or are both those stats the wrong way to measure the extent to which the health of individuals within given areas have been impacted by the viral infection?

The answer to that last question is yes, because populations of people are not evenly distributed among all the countries and regions of the world. Because of those differences in population sizes, when you compare the raw numbers of cases reported by two different countries that have very different size populations, you might be missing that the smaller number of cases reported by the country with the smaller population might really be indicating that its people's health is being more negatively impacted by the SARS-CoV-2 virus than the country with the larger population.

That's why epidemiologists use standardize metrics to express the degree to which a population within a given area is being impacted by a disease like COVID-19. A very common way to express those figures is by the number of deaths, recovered patients, or confirmed cases per 100,000 of the population. And that's the kind of information we've assembled about the incidence of COVID-19 among the world's major countries and regions in the following dynamic table.

Not only can you page through the table to see the data for 174 countries or regions of interest, you can search it for one in particular, and you can also rank all the data in the table from low-to-high by clicking a column heading for a particular category, or from high-to-low by clicking a column heading a second time.

In ranking the data in the table, you'll find the real answers to the first two questions we asked at the beginning of this article, but you'll also get a sense of how relatively serious the coronavirus pandemic is impacting the population within the countries we identified compared to others.

The data comes from the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE, which is limited by the quality of data it surveys from the nations reporting it. As a general rule of thumb, the more authoritarian a nation's leaders are, the less trustworthy are its officially reported coronavirus statistics.

Previously on Political Calculations

Image credit: unsplash-logoMartin Sanchez

COVID-19 In New York

New York has become the epicenter of COVID-19 infections in the United States. That description applies to both New York City, whose number of confirmed coronavirus cases total 17,896 with 192 deaths, and the state of New York, whose total positive cases reached 30,811 with 285 deaths as of 25 March 2020.

The following tower chart shows the progression of COVID-19 in the state of New York from 10 March 2020 through 25 March 2020.

Progression of COVID-19 in New York State, 10 March 2020 through 25 March 2020

New York City accounts for 58% of the cases reported in the state, where the city's Department of Health has provided some limited demographic data about who has tested positive for COVID-19 in the city. The data is from 19 March 2020, but provided enough information for us to construct a cumulative distribution of the ages of the 3,954 who had tested positive for COVID-19 nearly a week ago, which allows us to generate a more detailed distribution of that sampled population. The following chart shows those estimated results.

Estimated Age Distribution of COVID-19 Infected Population in New York City, as of 19 March 2020

The median age of New York City's population of those testing positive for the coronavirus infection is 46, which means half of confirmed cases are in people above that age, and half are in people below that age. Of those confirmed to have coronavirus infections, 40 to 44 year old New Yorkers have the highest incidence, with 51% of the city's infected population would appear to fall between the ages of 30 and 54.

How good are these estimates? As of 25 March 2020, New York City's age demographic data for COVID-19 infections has been expanded to cover over five times as many cases, and the percentages of the smaller sample from our analysis fall within 1% of the larger sample's data for Ages 0 through 64, and within 3% up to Age 74.

Overall, the state of New York has recorded over three times the rate of incidence of residents testing positive for COVID-19, when measured as a percentage of its population, than second ranked New Jersey.

As for COVID-19 related deaths in New York City, 95% are reported to have occurred in individuals with underlying illnesses, including diabetes, lung disease, cancer immunodeficiency, heart disease, hypertension, asthma, kidney disease, and gastrointestinal/liver disease. The best statistical analysis we've seen for the mortality risk associated with COVID-19 is from David Spiegelhalter, who describes the effect of the disease as being "like packing a year's worth of risk into a week or two".

Why has New York City become the epicenter for coronavirus cases in the United States? While that's a question that will be studied by epidemiologists for years, significant parts of the answer might be found here.


Here's the latest update to the state of New York's full tower chart through 22 April 2020:

Progression of COVID-19 in New York State, 10 March 2020 through 21 April 2020

The daily growth of New York's confirmed cases is still growing, but with signs of deceleration. The state's confirmed cases accounting for a little under one-third of the total positive test results in the United States.

Here's a little more detail on the geographical distribution of confirmed cases in the state, where the following chart identifies the top 10 regions or counties, through 23 April 2020:

Confirmed COVID-19 Cases in New York State, Top 10 Regions or Counties, 23 April 2020

The region of New York City includes Bronx, Kings, New York, Richmond, and Queens counties. The most affected counties are adjacent to New York City.

Why is New York's situation with the coronavirus so bad? The New York Times points to the poor judgment of government officials, including Governor Andrew Cuomo and particularly New York City Mayor Bill De Blasio. Their grave mistakes greatly amplified the poor judgment and sluggishness of bureaucrats in the Centers for Disease Control and the Food and Drug Administration, who the New York Post reports failed to treat the rapidly developing crisis like a rapidly developing crisis.

But wait, there's more! A new study is pointing to the city's public transportation system, particularly its subways and buses, as major contributors in exposing New Yorkers to the coronavirus. The failure to regularly decontaminate the city's trains and buses while keeping them running on a reduced schedule that resulted in packing more New Yorkers into highly contaminated spaces ensured they would be at much higher risk of being exposed to the SARS-CoV-2 coronavirus (shades of what happened on the Diamond Princess cruise ship).

As for ending the business closures and stay-at-home orders they've imposed, on 16 April 2020, Governor Cuomo indicated he will extend his statewide order through 15 May 2020, while Mayor De Blasio will keep New York City locked down well into July or August 2020.

While the state's numbers of deaths and confirmed cases continues to rise, there is a positive trend developing with the state's 'test positivity' rate, which we've been tracking for several weeks. The rate, which reflects the percentage of positive results reported for each day's new test results, had peaked a little over 50% on 1 April 2020 and has since declined to below 30%. Most states and territories in the Top 24 for percentage of population with positive test results have test positivity rates greater than 20%, which is a threshold that indicates testing is being focused on 'most likely' cases rather than general sampling that would give a better indication of the overall spread of the infection within the state or territory.


COVID-19 Coronavirus Cases in the U.S.

Can you tell, quickly, how many coronavirus cases have been reported in the state of Washington in the following data visualization? Is that more or less than New York? How about California?

Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) Dashboard Map

This map is a screenshot we snapped on 17 March 2020 of the dashboard map at Johns Hopkins Coronavirus Resource Center, which is one of the leading sources of public information about the progression of the coronavirus pandemic. The odds are that unless you already knew the answers to the questions we asked at the beginning, you wouldn't be able to answer them just from looking at the map as presented.

To be fair, the map is designed to visualize the progression of cases around the world, not just in the U.S. The map's designer did provide the means to get the information however. Since the map is an interactive one at the Johns Hopkins site, you could click on the circles that appear above each of these states to get the data, zooming in to get to your state of interest where the circles overlap each other at the scale we showed above, but doing so will take multiple steps to access the data. There must be a simpler way to visualize the daily snapshot of this data to allow the data for one state to be quickly compared with others.

That's why we've developed the following simply bar chart comparing each state's reported number of confirmed cases, deaths, and recovered patients, which we'll update periodically until the total number of cases has stabilized.


It's basic, but it works. And for what it's worth, if you're looking for coronavirus maps the U.S., there are many very bad examples. Check out this map from the U.S. Centers for Disease Control, which was flagged on the Crappy Design subreddit:

The good news is the CDC has since fixed the color scale problem of their map. It's still not terribly useful, but that's the government for you.


Adding a second chart to present the numeric data from the first chart as a percent of each state or territory's 2019 estimated population:


Data Sources

2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE. CSSE COVID-19 Time Series Data: Confirmed. [CSV File].

2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE. CSSE COVID-19 Time Series Data: Recovered. [CSV File].

2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE. CSSE COVID-19 Time Series Data: Deaths. [CSV File].

U.S. Census Bureau. Annual Estimates of the Resident Pouplation for the United States, Regions, States, and Puerto Rico: April 1, 2010 to July 1, 2019 (NST-EST2019-02). [Excel Spreadsheet]. Last updated 30 December 2019. Accessed 14 March 2020.

The COVID Tracking Project. Most Recent Data. [CSV File].

Cashing Out of the S&P 500

Retired Couple - Source: Unsplash - Max Harlynking: https://unsplash.com/photos/DGP-759-Ukk

Have you been saving for retirement and are now ready to retire? What would happen if you withdrew a fixed percentage of the value of your retirement investment once a year for the rest of your life, if that investment was in the S&P 500? Would that provide enough money to pay for the things you might want to buy with it after you no longer have an income from a job? Or might market volatility force you to reconsider your options?

These are difficult questions to answer, because the future is very much an undiscovered country, where chaos controls both the timing and magnitude for when and how much market volatility might erupt.

But if we assume the unfixed future might be like the past, we can test how well a strategy to only withdraw a fixed rate of money from such an investment would have fared using the S&P 500's rich history of data during its most turbulent episodes.

And that's what we've done with our latest tool, where you can see how well you could count on your investment in the S&P 500 would have fared for up to 40 year long periods if you had chosen to retire in any month between January 1871 and 40 years before the present* while fully reinvesting your dividends along the way. If you're accessing this article on a site that republishes our RSS news feed, please click through to working version of the tool at our site.

S&P 500 Investment Data
Description Value
Initial Investment Value (Before Any Withdrawals)
Annual Withdrawal Percentage
Start Month for Withdrawals
Number of Years of Withdrawals

S&P 500 Withdrawal Estimates
Calculated Results Values
Month of Final Withdrawal
   Investment Value Before Withdrawal
   Withdrawal Amount
   Amount Remaining In Investment
Withdrawal Highlights
Average Annual Withdrawal Amount
Total Amount Withdrawn Over All Years
Largest Annual Withdrawal
Smallest Annual Withdrawal




























































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































































For our tool's default settings, we've chosen September 1929 as the time of the first withdrawal, because this month immediately precedes what happened with the U.S. stock market at the onset of the Great Depression. If your S&P 500 cash out strategy can survive the sustained series of disruptive events that followed this month and provide sufficient funds to support your needs, you can reasonably expect to weather any lesser event.

For good measure, you might also want to consider how your retirement might fare if a market crash occurred well after you've retired. You might choose a date that includes the years of the Great Depression or you could choose the more recent disruptive event of the Great Recession of 2008-2009 by selecting a starting year in the range of the late 1960s through the late 1970s. The maximum length of time the tool will consider for your S&P 500 withdrawal strategy is 40 years.

The tool's results indicate the value of your investment in the S&P 500 before and after your annual withdrawal, along with our estimates of the total amount you would have withdrawn over the number of years you've selected, the average amount of your annual withdrawals, and also the highest and lowest values of your annual withdrawals along with the years in which they would have occurred. Meanwhile, the tool does not consider things like taxes, commissions, or fees, which would most likely be taken out of any money you withdraw if they apply.

* Like our S&P 500 At Your Fingertips and Investing Through Time tools, we plan to periodically update this tool, with the first update in the first quarter of 2020 after the S&P 500's data for 2019 is finalized, and then once a year afterward, which will allow us to roll in new 40-year long periods.

References

The tool above really doesn't say anthing about what a "safe withdrawal rate" for you may be. For that kind of insight, do check out the following resources on the topic, which you might find useful.

Hubbard, Carl; Cooley, Philip L.; and Walz, Daniel T. Retirement Savings: Choosing a Withdrawal Rate That Is Sustainable. Journal of the American Association of Individual Investors. [Online Article]. February 1998.

Pfau, Wade. The Trinity Study and Portfolio Success Rates (Updated to 2018). Forbes. [Online Article]. 16 January 2018.

RBC Wealth Management. Sustainable withdrawal rates in retirement. [PDF Document]. 25 March 2019.

Where our tool is concerned, so long as you select an annual withdrawal percentage rate of less than 25.0%, your investment will effectively last forever because there will always be some fraction remaining in your investment from which you can withdraw some percentage of it in future years, even though the withdrawal amounts may become vanishingly small, which can be considered the investment math version of one of Zeno's paradoxes.

In practice, you may find it extraordinarily difficult to resist raising the percentage of your investment that you cash out in years where market volatility might crash the amount you would withdraw if you otherwise maintained a fixed percentage rate of withdrawal, where you would intervene to reset that withdrawal rate because you've come to value having cash today more than whatever potential investment value you might have tomorrow. If you need cash to cover your living expenses in retirement or in times of severe economic distress, where your ability to earn income is very limited, it's very understandable.

Our tool can accommodate that kind of decision making. Just update it with the value of your investment at the starting month where you would need to adjust your withdrawal rate, and see what happens next. Then adjust it again at later dates as you might need.

Image credit: unsplash-logoMax Harlynking

Celebrating Political Calculations' Anniversary

Our anniversary posts typically represent the biggest ideas and celebration of the original work we develop here each year. Here are our landmark posts from previous years:

  • A Year's Worth of Tools (2005) - we celebrated our first anniversary by listing all the tools we created in our first year. There were just 48 back then. Today, there are nearly 300....
  • The S&P 500 At Your Fingertips (2006) - the most popular tool we've ever created, allowing users to calculate the rate of return for investments in the S&P 500, both with and without the effects of inflation, and with and without the reinvestment of dividends, between any two months since January 1871.
  • The Sun, In the Center (2007) - we identify the primary driver of stock prices and describe a whole new way to visualize where they're going (especially in periods of order!)
  • Acceleration, Amplification and Shifting Time (2008) - we apply elements of chaos theory to describe and predict how stock prices will change, even in periods of disorder.
  • The Trigger Point for Taxes (2009) - we work out both when, and by how much, U.S. politicians are likely to change the top U.S. income tax rate. Sadly, events in recent years have proven us right.
  • The Zero Deficit Line (2010) - a whole new way to find out how much federal government spending Americans can really afford and how much Americans cannot really afford!
  • Can Increasing the Minimum Wage Boost GDP? (2011) - using data for teens and young adults spanning 1994 and 2010, not only do we demonstrate that increasing the minimum wage fails to increase GDP, we demonstrate that it reduces employment and increases income inequality as well!
  • The Discovery of the Unseen (2012) - we go where so-called experts on income inequality fear to tread and reveal that U.S. household income inequality has increased over time mostly because more Americans live alone!

We marked our 2013 anniversary in three parts, since we were telling a story too big to be told in a single blog post! Here they are:

  • The Major Trends in U.S. Income Inequality Since 1947 (2013, Part 1) - we revisit the U.S. Census Bureau's income inequality data for American individuals, families and households to see what it really tells us.
  • The Widows Peak (2013, Part 2) - we identify when the dramatic increase in the number of Americans living alone really occurred and identify which Americans found themselves in that situation.
  • The Men Who Weren't There (2013, Part 3) - our final anniversary post installment explores the lasting impact of the men who died in the service of their country in World War 2 and the hole in society that they left behind, which was felt decades later as the dramatic increase in income inequality for U.S. families and households.

Resuming our list of anniversary posts....