MAKE THE UNIVERSE WORK FOR YOU

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The current situation with the COVID-19 virus is an example of what happens when people do not understand how an epidemic progresses. I hope that this will help educate everyone.(It helped me!) If this spreadsheet is within 25% of what really happens I will be ecstactic! Consider this as an education tool to learn how some factors can effect the final outcome of the disease.

The spreadsheet can changed by the user so that conditions pertinent to your situation can be simulated.

The covid19V1.ods file is an Open Document spreadsheet and the covid19V1.xlsx is a Microsoft Excel spreadsheet. Each has three sheets within the file and they both do the same work. It is suggested that you download and save one of the files to your computer and then open it while you read the following paragraphs. (See below link)
• The Info sheet contains the instructions and some elements meant to be changed by the user like Virus spread-rate (S_RATE), population size (S_POP), and infected population at start((SS_POP). Those values that can be changed are in the A column just before the bold letters. The Virus spread-rate value has a range of near zero to about 1.82 as a maximum. Beyond this value, the spreadsheet will show error values in the Uninfected population column due to the fast rise and fall of the feedback loops in the spreadsheet. The Virus spread-rate is meant to be adjusted by the user to show how that variable can change the other results so dramatically. The 'Cured & Uninfected' graph is an example. This graph goes to a final 'steady state' value that is the result of the Virus spread-rate value and the 'Social Distance' values in the 'Social Distance' column.
• The CASES sheet has the actual calculations with the difference equations repeated for each day. The first & second columns have the detected infections from the CDC web site up to the date recorded. The 'Social Distance fraction' column is the column that sets the 'social distancing' factor, where 1 is average activity, less than 1 is social distancing, and more than 1 is crowds like Mardi Gras in New Orleans. A value of 0.7 is about as best as can be expected in a modern, mobile, interconnected society. For example, a value of zero, where EVERYONE is in solitary confinement, is of course impossible. You can set a new value into any row in the 'Social Distancing' column and it will be copied to the end of the column or until you go to a lower row and set another value to start at that time. Hence, you can see effects having and stopping 'social distancing' or crowds. The 'Social Distance fraction' column is meant to be changed by the user to see the results on the CASES sheet and GRAPHS sheet. The column Available Hospital Beds is also meant to be changed by the user and can be changed on any day both up and down.
• The GRAPHS sheet shows the graphs of the calculations done on the CASES page. Other graphs are possible, and encouraged, for spreadsheet wizards. An initial surprise was the 'Cured & Unifected' graph that showed only some of the population getting infected. The Cured graph is the 'herd immunity' you sometimes hear doctors talk about. Once the 'computed spread rate' column value goes to less than one, the epidemic is on the wane.

Click to download. COVID-19 Spreadsheet for Open Office users

Click to download. COVID-19 Spreadsheet for Microsoft Excel users

It is recommended that you download to your 'Download' folder on your computer so that your virus checker can scan the document before you open it.

What I have learned from this model.
• The first element I changed was the 'Virus spread-rate', which is on the Info page. I was surprised at the effects it had on the 'Cured & Infected' and the 'Total Deceased' graphs. I left the 'Social Distancing fraction' column numbers at 1. What I found was the Cured & Infected & Deceased numbers would level off to steady state values. Steady state values are what happens when a set of differential equations reach their final values if the equations are stable. Unstable equations can go to infinities. The inportant part is the ratio of Cured to Uninfected is directly a result of the Virus spread-rate value. The final value of the Total Deceased is also a result of the Virus spread-rate. I also noted that the 'Daily Computed Spread Rate' graph went naturally below one as fewer Uninfected were around to get infected and more Cured were around to resist further illness. Some results from South Korea show that Cured who have antibodies still show signs of COVID-19. This spreadsheet seems to indicate the Cured are still picking up the virus from other people. However, the antibodies have not yet completely removed the new COVID-19 viruses they have picked up from the environment.
• The second element I changed was in the 'Social Distance fraction' column on the CASES page. On the row at day 60, I changed the value from 1 to 0.85. This imediately changed the 'Daily Computed Spread Rate' and dramatically changed the 'Total Deceased' graphs toll. The Uninfected amount still stayed at a high level and the Cured rate stayed at a low level. Hence, holding the 'Social Distancing' to the full amount till forever will have great good effects on the total population. The economic effects are another spread-sheet possiblity, but from local effects I see, are tough on my neighbors.
• The third element I changed was also in the 'Social Distance fraction' column at day 120. There I tried several values and checked the GRAPHS sheet for the results. If I tried a value of 1, then the 'Hospital Sick','Total Deceased' , 'Uninfected', and 'Cured' graphs went back to nearly the same horrible values at the original test. When I tried a value of 0.93, the graphs clearly showed a 'second bounce' that was worse than the original values. I also noted how long it took to get that second bounce. When I tried a 0.89 value, I noticed the 'Daily Computed Spread Rate' remained below 1, and the 'Uninfected' and 'Cured' graphs were not noticeably changed. The 'Total Deceased' graph still went up slightly because the infection rate was so close to one.
• My take aways from these tests are:

  The 'Virus spread rate' will overcome significantly reduced 'Social Distancing' if allowed to until the 'Uninfected population' fraction gets low enough to drop the 'Daily computed spread rate' significantly below 1. See 'Social Distance fraction' of 0.93 above. In this example, the 60 days between start and then greatly reduced 'Social Distancing' was not enough to prevent increasing the mortality by over 10 times. I urge the user to change the 'Social Distance fraction' values in both amount at any one day and the days that the 'Social Distance' is implemented. The user may not understand the equations, but like ball players learn how the ball behaves in their sport, they can anticipate how it will behave in their circumstances.

  Any small reduction of 'Social Distancing' will result in slightly higher deaths as the 0.89 'Social Distance fraction' shows. However, reduced economic activity over the short term has little effect on death rates, but over the long term, has severe health conseqences that lead to early mortality. Therefore a balance must be made between the COVID-19 and economic harms that are the present reality. The fine line can best be found by increased testing of the general population so that the effective spread-rate of the virus is known directly and not through the hospital or mortaliy rates.

  The 'Social Distancing fraction' should be varied depending on a persons location. It should be above 1 for New York City and below 1 for a very rural county that has large farms or ranches over many square miles. This accounts for the rapid spread in large cities and slower spread in rural areas. However, large gatherings in rural areas can negate the rural advantage.

End of COVID-19 research. Thanks for reading this far.