Mobility data helps policymakers, local government and executives make informed decisions on COVID-19 restrictions and reopening.
COVID-19 in the United States
Confirmed Cases
in the USA
Deaths
in the USA
Cases per Capita
per 100,000
Deaths per Capita
per 100,000
Based on publicly available data, how is COVID-19 (also known as Coronavirus) spreading in the United States? How fast is it growing in each state? And how prepared may different states be to cope with the spread of this global pandemic?
At Data USA, our mission is to visualize and distribute open source data of U.S. public interest. To track the evolution and trajectory of COVID-19, we have created a series of interactive graphics. These visualizations are designed to put the spread of COVID-19 in context.
Confirmed Cases by State
| State | 14-day Trend of New Cases | 14-Day New Cases | 14-Day New Cases per 100,000 | Confirmed Cases | Cases per 100,000 | Confirmed Deaths | Total vs New Cases | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Daily New Cases
Use the map to select individual states.
Because of the exponential nature of early epidemic spreading, it is important to track not only the total number of COVID-19 cases, but their growth.
This chart presents the number of new cases reported daily by each U.S. state.
For more information about the difference between linear and logarithmic scale, click here.
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Economic Impact
Unemployment Insurance Claims
Initial unemployment insurance claim numbers are not seasonally adjusted.
Initial unemployment insurance claims in the United States
Initial Unemployment insurance claims in
Since new claims for unemployment insurance began to spike the week ending on Saturday, March 21st, there have been over 0 initial claims filed.
This chart shows weekly initial unemployment insurance claims in the United States (not-seasonally adjusted). The most recent data point uses Advance State Claims data, which can be revised in subsequent weeks.
For more information about the difference between linear and logarithmic scale, click here.
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Monthly State Employment
Change in employment in the United States
between 0 0 and 0 0
There was a N/A% decrease in employment between 0 0 and 0 0 in the United States (0 employees).
This chart shows monthly employment numbers in the United States (not-seasonally adjusted) across all industry sectors.
For more information about the difference between linear and logarithmic scale, click here.
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Mobility
Community Mobility
This chart shows how visits and length of stay to workplaces have changed over time compared to a baseline.
Baselines are calculated using aggregated and anonymized data to show popular times for places in Google Maps. Changes for each day are compared to a baseline value for that day of the week.
Data from the Google LLC "Google COVID-19 Community Mobility Reports" https://www.google.com/covid19/mobility/.
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Risks and Readiness
Below you will find some statistics of the preparedness of U.S. states and of the vulnerability of the population in each state. For more information on critical care in the United States, visit this report from the Society of Critical Care Medicine.
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Data from the Kaiser Family Foundation State Health Facts.
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Data from the Census Bureau ACS PUMS 1-Year Estimate.
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Data from the Census Bureau ACS PUMS 1-Year Estimate.
FAQs
Exponential Growth & Logarithmic Scales
What is exponential growth? And how does it relate to the use of logarithmic scales?
At the beginning of an epidemic, epidemic growth exponentially. Exponential growth is growth that happens by multiplying rather than adding.
Compare linear growth that adds 10 at each time step with exponential growth that multiplies by 2.
A linear growth sequence that adds 10 at each time step looks like:
0, 10, 20, 30, 40, 50, 60, 70, 80, 100…Whereas exponential sequence that multiplies by 2 at each time step looks like:
1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024....At the beginning, linear growth seems faster (20 is much larger than 4), but linear growth does not accelerate. It adds the same amount every time. Exponential growth accelerates, adding more at each time step, so it can grow suddenly.
After 10 steps, linear (+10) growth brings us to 100. Exponential (x2) growth brings us to (1,024). After 20 steps, linear growth only brings us to 200. Exponential growth to more than 1 million!
Exponential growth is so fast that to appreciate it better we need to use logarithmic scales. These are scales that also grow by multiples. For example, a logarithmic scale between 1 and 1,000,000 goes from 1 to 10, from 10 to 100, from 100 to 1,000, from 1,000 to 10,000, from 10,000 to 100,000, and from 100,000 to 1,000,000. This is a logarithmic scale in base 10, because we are multiplying by ten each time. What this scale shows is that, in exponential growth, 1,000 is halfway to 1,000,000. That’s why it is important to stop exponential growth even if the numbers look small. The same number of steps that bring you from 1 to 1,000 bring you from 1,000 to 1,000,000.
Strictly speaking, epidemic processes are only exponential early on, when the number of cases is small compared to the size of the population or other limiting factors. Eventually, growth peters out, either because spreading became widespread, or because other factors, such as physical distancing, or immunization, reduces the speed of the spreading. To learn more about the basic functional forms of epidemic spreading, watch this video prepared by the CDC.
Disclaimer
Information on this site is provided on an “as is” and “as available” basis. Data USA makes every effort to ensure, but does not guarantee, the accuracy or completeness of the information on the Data USA website. This site is for informational purposes and is not intended provide advice or aid in decision making. Our goal is to keep this information timely. If errors are brought to our attention, we will try to correct them.
COVID-19 in Numbers