Here are some plots and data we are found interesting.

1. COVID-19 Data Analysis
Written on: 4/16/2020
Data Updated to: 4/15/2020

2. Disclaimer
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3. Introduction
▪ Country/Regional Data and Plots
▪ USA State Data and Plots
▪ USA Models
▪ USA Red vs Blue
▪ Questions
▪ Interesting Metrics from Data

4. REGIONAL ANALYSIS
Breakdown of data by Political/Geographic Regions

5. Cases by Country
>10,000 Cases

6. Cases by Country
Cases per 100k of Population
EU in Red & US in Blue

7. Deaths by Country
>100 Deaths

8. Deaths by Country
Deaths per 100k of Population
EU in Red & US in Blue

9. Cases by Region/Country
>10,000 Cases
What countries are in these groups is at the end of slide deck

10. Deaths by Region/Country
>100 Deaths

11. Case Trends by Region

12. Death Trends by Region

13. UNITED STATES
Analysis the State of affairs in the States of the

14. Cases by State
>2000 Cases

15. Deaths by State
>100 Deaths

16. Case Trends by State
Cases per 100k of Population

17. Death Trends by State
Deaths per 100k of Population

18. Mortality Rate (MR) and the Flu
▪ Mortality Rate is defined as:
▪ Number of Deaths per 100,000 people
▪ A Mortality Rate of 10 in the US population of 330MM people corresponds to
33,000 deaths
▪ Note the historical plot of the MR of influenza from 1930 to 2004.
▪ Link to article in the references; it’s a good read
▪ I found this conclusion relevant:
▪ The considerable similarity in mortality seen in pandemic and non-pandemic influenza
seasons challenges common beliefs about the severity of pandemic influenza. The
historical decline in influenza-classed mortality rates suggests that public health and
ecological factors may play a role in influenza mortality risk. Nevertheless, the actual
number of influenza-attributable deaths remains in doubt.
▪ I utilized the estimated 2019 population of various regions (i.e. New
York, USA, Michigan, etc) and deaths attributed to COVID-19 in those
regions to compare the variance in mortality rates across various
regions of the country
▪ By using Mortality Rate, it normalizes the data to aid in better regional
comparisons
▪ Why normalize it?
▪ Different regions or states have different public policy, population density, etc that are
impacting their states’ mortality rates for COVID19
See References #4

19. How to read Statistical Model
▪ The top plot is cumulative COVID-related deaths
over time
▪ Attempts to estimate the total deaths from COVID19
▪ This model is better for showing the efficacy of the
best fit model
▪ It also shows how the impact of changes in behavior
can impact total deaths.
▪ Note, New York early on had an MR tracking close
to 100, which subsequently made a step-change to
~70
▪ The bottom plot is daily death rate over time
▪ This plot better shows the peak death rate as well as
when to expect improvement
▪ The models utilize mortality rate as the variable
▪ Curve fit model, estimating mortality rate based on fit
to actual data and start times for the region
▪ Mortality Rates of 20, 40, and 100 are used to
bracket actual data, and for regional comparison
Reference #3 is the white paper for the numerical model used to generate all the models

20. USA Actual vs Models
Cumulative Plot
Note: The impact NY has on the
MR of the US. NY has a 10X
higher MR than the rest of the US

21. USA Actual vs Models
Daily Plot Remember the models are base on
population MR 40 for USA is higher
than for USA without NY, that is
why you see two model lines

22. New York Actual vs Models
Cumulative Plot

23. New York Actual vs Models
Daily Plot

24. New Jersey Actual vs Models
Cumulative Plot

25. New Jersey Actual vs Models
Daily Plot

26. Michigan Actual vs Models
Cumulative Plot

27. Michigan Actual vs Models
Daily Plot

28. Massachusetts Actual vs Models
Cumulative Plot

29. Massachusetts Actual vs Models
Daily Plot

30. Louisiana Actual vs Models
Cumulative Plot

31. Louisiana Actual vs Models
Daily Plot

32. Red vs Blue Deaths (2016 Presidential Election)
Red is Republican and Blue is Democrat

33. Red vs Blue… Why
▪ The Trump Administration (and likely the Constitution) left many
decisions to the States, including decisions to shut down commerce
▪ States like CA shut their whole state down at once; other states, like
Texas, left it up to the cities and counties
▪ This brings up an interesting political dynamic that could impact different
regions at different rates
▪ There has been some interesting information coming out around
Hydroxychloroquine treatments, but some state bureaucracies have
either held up the use of the medicine or limited its use
▪ Mortality Rate is affected by several variables including public policy

34. Questions I am trying to answer
▪ When will this end?
▪ What is the effect of different public policies?
▪ Can other states, regions, countries learn from the variability in public
policy in the US?
▪ How does this compare to the flu?
▪ How bad could it have been without stay-at-home policies?
▪ Is social distancing enough?
▪ Do we have to shut the economy down next time?

35. Interesting thoughts on the Data
▪ NY has a ten times higher mortality rate than the rest of the US
▪ For 8 days, NY was trending close to a mortality rate of 100
▪ What caused it to be so high?
▪ What caused the improvement?
▪ Is public policy to blame for both failure and success?
▪ Trump Admin estimated 100k to 250k deaths in the US, this model is currently
estimating 30k to 40k deaths in the US
▪ Where did they get 100k to 250k? Overestimating early trends in NY and applying it to
the entire US?
▪ Why are we seeing the trends change upwards after what appeared to be a peak?
▪ Red States have 23.1% of active COVID19 Cases, but 17.3% of deaths

36. Next Steps
▪ We are updating the slides daily
▪ I plan on adding some models for Europe and S. America
▪ Working on some better Country / Regional Trend Plots (time zero)
▪ If you want to see something, send us an email

37. Comments, Questions & Opinions are Welcome
contact@radiusenergysolutions.com

38. Country Region (group) Country Region Country Region (group) Country Region Country Region (group) Country Region Country Region (group)Country Region
Zimbabwe Andorra Andorra United Kingdom Moldova Moldova
Zambia Australia Australia Switzerland Monaco Monaco
Western Sahara Canada Canada Sweden Mongolia Mongolia
West Bank and Gaza Trinidad and Tobago Spain Montenegro Montenegro
Uganda Saint Vincent and the Grenadines Slovakia New Zealand New Zealand
Togo Saint Lucia Romania Norway Norway
Tanzania Saint Kitts and Nevis Portugal Papua New Guinea Papua New Guinea
South Sudan Jamaica Poland Russia Russia
South Africa Haiti Netherlands San Marino San Marino
Sierra Leone Grenada Malta Vietnam
Seychelles Dominican Republic Luxembourg Thailand
Senegal Dominica Lithuania Singapore
Sao Tome and Principe Cuba Latvia Philippines
Rwanda Barbados Italy Malaysia
Nigeria Bahamas Ireland Laos
Niger Antigua and Barbuda Hungary Indonesia
Namibia Panama Greece Cambodia
Mozambique Nicaragua Germany Burma
Mauritius Honduras France Brunei
Mali Guatemala Finland Venezuela
Malawi El Salvador Estonia Uruguay
Madagascar Costa Rica Denmark Suriname
Liberia Belize Cyprus Peru
Kenya Uzbekistan Croatia Paraguay
Guinea-Bissau Kyrgyzstan Bulgaria Guyana
Guinea Kazakhstan Belgium Ecuador
Ghana China China Austria Colombia
Gambia Cruise Ship Cruise Ship Fiji Fiji Chile
Gabon Ukraine Holy See Holy See Brazil
Ethiopia Slovenia Iceland Iceland Bolivia
Eswatini Serbia Japan Japan Argentina
Eritrea North Macedonia Korea, South Korea, South Sri Lanka
Equatorial Guinea Kosovo Liechtenstein Liechtenstein Pakistan
Cote d'Ivoire Czechia Mexico Mexico Nepal
Congo (Kinshasa) Bosnia and Herzegovina United Arab Emirates Maldives
Congo (Brazzaville) Belarus Tunisia India
Chad Albania Syria Bhutan
Central African Republic Sudan Bangladesh
Cameroon Somalia Afghanistan
Cabo Verde Saudi Arabia Taiwan* Taiwan*
Burundi Qatar Timor-Leste Timor-Leste
Burkina Faso Oman US US
Botswana Morocco Turkey
Benin Mauritania Israel
Angola Libya Georgia
Lebanon Azerbaijan
Kuwait Armenia
Jordan
Iraq
Iran
Egypt
Djibouti
Bahrain
Algeria
SE Asia
South America
South Asia
W Asia no ME
EU+CH+UK
Middle East
Africa
Carribean
Central America
Central Asia
Eastern Europe No EU
Countries by Region

39. Reference
1. Data stream is from Tableau via a data.world connection
2. They are indicating that the raw data is from John Hopkins University
3. https://www.hindawi.com/journals/mpe/2012/124029/ Cumulative
Distribution Model
4. Trends in Recorded Influenza Mortality: United States, 1900–2004
1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2374803/
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