**...FRIDAY APRIL 17 2020 6:08 PM EDT...**

In my previous article on the deadly outbreak of COVID-19, I issued an outlook where I projected the United States to follow Italy's curve for the number of new cases per day normalized by the uninfected population. I had used Italy as a model since their were many parallels in both countries responses, and Italy was ahead of the United States as they experienced an explosion of COVID-19 cases sooner (__see United States Experimental Forecast section from the previous article at this link__).
While the United States has seen a flattening in the new number of cases per day, unfortuntately we are now above my previous forecast as the number of cases per day has become stuck at a pleateau instead of decreasing like Italy has seen. Perhaps this is due to some states still not having a stay at home order, which is unlike Italy where the entire nation has been a stay at home order. These states are now seeing a surge in new COVID-19 cases (__https://www.cnn.com/2020/04/17/politics/republican-governors-stay-at-home-coronavirus/index.html__). In addition their appears to be a swath of the national population in the United States not taking social distancing seriously as evidenced by a rise in protests against such government orders (__https://www.cnn.com/2020/04/16/politics/what-matters-april-16/index.html__).
In the previous article (__link here__) I presented a discussion and evidence in data that shows social distancing and staying at home as much as possible has been effective at reducing the number of cases, for example presenting information that states that had very few cases at the time of the stay at home order to this day have the lowest percentages of their population infected. If we remain stuck at this plateau, the projection I made below suggests by next week on Friday the United States will have nearly 900,000 cumulative COVID-19 cases with perhaps as many as 57,000 fatalities. So I hope everyone reading this has been or will take the following advice so we in the United States can hopefully see a reduction from the current plateau of new cases per day:
1) If you are not under any stay at home orders or have not been following to such orders, try to stay at home as much as possible and socially distance (maintain a physical distance) from others in public when going out for necessities.
2) If you are under stay at home orders, continue to practice those orders as these states have reached a plateau in the new number of cases per day. In the cases of Michigan and Washington, these orders coincide with what is now a general decrease in the new number of cases per day as Figure 1 below shows.
3) Don't forget about sanitation habits such as keeping your hands clean by frequent old fashioned washing with soap and water or using disinfectant gels or wipes. Have a holding area in your home to temporarily place items ordered online or picked up from any store where you can disinfect their packaging (bags, boxes, cans, etc.). You can also use this holding area to give time for any bacteria to dissipate on the packaging before storing bought items in your home.

**...WHAT AREAS IN THE UNITED STATES I HAVE COLLECTED DATA FOR...**

1) Michigan and North Carolina where I have family and friends 2) California, Washington, and New York which were the first states to have a rapid increase in the number of COVID-19 cases. 3) West Virginia, the last state to report its first COVID-19 case

**...SOURCES FOR DATA...**
1) For global COVID-19 case count, __https://www.worldometers.info/coronavirus/__
2) For a state by state breakdown in the United States, __https://www.worldometers.info/coronavirus/country/us/__
3) For a county-level breakdown in Michigan, __https://www.michigan.gov/coronavirus__
4) For a county-level breakdown in North Carolina, __https://www.newsobserver.com/news/local/article241168731.html__
5) New York state total and New York City total, __https://covid19tracker.health.ny.gov/views/NYS-COVID19-Tracker/NYSDOHCOVID-19Tracker-TableView?%3Aembed=yes&%3Atoolbar=no__

**...CALCULATIONS TO NORMALIZE DATA....**
Warning! Note that while the percentages described below have been of low numbers, it only has taken a very small percentage of the population getting infected to overwhelm the medical system, which forces hopsitals to make priorities as to who will or will not get COVID-19 treatments as well as other treatments for other serious diseases such as cancer. For example Italy on 3/11/2020 with only 0.021% of the national population infected with COVID-19 had hospitals reaching capacity (https://www.theatlantic.com/ideas/archive/2020/03/who-gets-hospital-bed/607807/).
Comparing nations or regions (state, county, city, province, etc.) simply by looking at the total number of cases may not provide a fair comparison as larger population areas naturally will have a higher number of cases. Therefore I converted the data by dividing by population to give a normalizing percentage, for instance:
% infected, nation = (total cases nationwide/total population of nation)*100
% infected, state = (total cases statewide/total population of state)*100
% infected, county = (total cases countywide/total population of county)*100
% infected, city = (total cases citywide/total population of city)*100
I also did the a similar normalization for the number of new cases per day, in a metric I called "percent chance of getting infected." For example in a population of 100, if you are getting 1 new case each day that the percent chance of the remaining uninfected 99 getting infected is (1/99)*100 = 1.01%. On the next day when another 1 case happens the chance of the uninfected 98 getting infected becomes (1/98)*100 = 1.02%. Then lets say on the third day the population is now getting 3 new cases per day, so now 95 are uninfected and the chances go up to (3/95)*100 = 3.15%. As such I calculated:
Number of Uninfected = Total Population - Total Number of Cases
% chance of becoming infected = (New Cases Today/Number of Uninfected)*100
Although I think this metric is proportional to the likelihood of getting infected, the small resulting values should not be interpreted as literal or to minimize the seriousness of the situation, because this is based on the number of new confirmed cases, so if testing supplies in a region are not adequate or a large number of people with flu-like symptoms decide not to get themselves tested, then the true number of COVID-19 cases in reality is larger and this percentage could actually be higher than what has been calculated thus far. And if you venture to certain hospitals, streets, buildings, etc. where the virus is present or in high concentration, the chances of becoming infected go up and is likely higher than reflected by the calculation. Rather, I use this calculation to understand if the number of new cases per day is increasing, staying the same, or decreasing, and this metric is normalized by population to be able to compare one region with less population to another region with more population more fairly.
The final metric is the mortality rate calculated as:
mortality rate % = (Total Deaths/Total Number of Cases)*100

**...UPDATED DATA FOR THE UNITED STATES...**

*Figure 1 - Approximation of percent chance of becoming infected in the states I am currently tracking. I made this approximation by taking the number of new cases per day and dividing by the uninfected population. See disclaimer within this figure about the limitations of this approximation, this metric should not be solely used in assessing your risk or decision making about COVID-19.*

**...MY LATEST FORECAST FOR THE UNITED STATES...**

*Figure 2 - Forecast paradigm used. The United States has not so far seen a decrease in the number of new COVID-19 cases per day as Italy has seen. It is hard to know when exactly this will occur, so my updated forecast is only a 1-week projection and assumes that the next week will follow the average of the last several days. *

See Figure 2 for my updated forecast philosophy, next week to follow average of previous days. This average was put into the column "% chance of getting infected" in Table 1. From there, the following metrics could be calculated in the forecast for each day: New Cases in One Day = (% Chance of Getting Infected/100)*(Total Uninfected Previous Day) Total Cases = Total Cases Previous Day + New Cases in One Day Total Uninfected = USA Population - Total Cases

% Population Infected = (Total Cases/USA Population)*100

The mortality rate forecast in Table 1 was based on the observation of the mortality rate increasing by 0.2% each day over the last several days. The surge seen in the last 24 hours I disregarded because this is due to New York state adding approximately 3700 deaths to their count that were previously not considered COVID-19 fatalities (__https://khn.org/morning-breakout/new-york-citys-death-toll-jumps-by-more-than-3700-after-officials-take-into-account-probable-cases/__). The forecast mortality rate was then used to forecast the total number of COVID-19 fatalities as follows:
Total Deaths = (Mortality Rate %/100)*Total Cases

*Table 1 - Tabular view of USA experimental forecast for COVID-19 cases*

*Figure 3 - Graphical view of USA experimental forecast for COVID-19 cases, total number of cases*

*Figure 4 - Graphical view of USA experimental forecast for COVID-19 cases, issued total fatalities*

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