BIRDSEYE VIEW POSTS

Since 2012 on the Weather Underground (www.wunderground.com) blogs, I have been posting annotated "birdseye view" charts of the Atlantic basin, with a detailed explanation and forecasting that references the chart. From there you may know me as "NCHurricane2009." While I now do these "birdseye view" posts here, I will continue to do comments via Disqus on Weather Underground at www.wunderground.com/cat6. You can see my Disqus feed at this link for my latest comments. Feel free to reply to me with your disqus account or e-mail at IOHurricanes@outlook.com 

 
 
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SPECIAL ARTICLE - HOW MUCH COVID-19 TESTING NEEDED IN THE UNITED STATES TO SAFELY REOPEN?

...SUNDAY APRIL 26 2020 8:30 PM EDT... Since my previous article on the current outbreak of the infamous coronavirus known as COVID-19, there has been a lot of discussion about reopening the United States due to the crushing economic and social tolls of being isolated under prolonged stay at home orders. South Korea offered a model of having no stay at home orders while simulataneously containing the disease by having sufficient testing to determine who has and who doesn't have the disesase, and quarinting those who were found to be infected. The World Health Organization (W.H.O.) has an answer to measuring whether or not enough testing is being done in a certain region. Their specification for a pandemic calls for running enough tests such that only 10% are positive (https://www.vice.com/en_us/article/v74wjd/the-us-doesnt-have-nearly-enough-coronavirus-tests-to-open-the-economy). Some studies suggest the positive test rate needs to be as low as 3% (https://www.cnn.com/2020/04/19/health/us-coronavirus-sunday/index.html). This seems to make sense, if you take the idea to an extreme, for example an area ran 1,000 tests in a single day and has 100% of those tests come back positive, then how do you know the true number of new cases that day? What if you ran 1,050 tests, would you still have 100% of the tests come back positive and do you actually have 1,050 new cases that day? But if the same area ran 300,000 tests in one day and only 3% came back positive, then chances are you have a pretty good grasp of how many new cases you had in a single day, and thus who actually has and does not have the disease. Since my previous update on COVID-19, I have begun collecting data on all 50 states, including the number of tests ran each day in each state. I have also done this for all nations I am tracking the progress of the virus in. For example in South Korea where sufficient testing (with no stay at home order) has continued to keep the disease contained, the daily positive test rate on April 25 was at an impressively low 0.32%, with similar figures for each day over the last several days. But it should also be noted that South Korea ramped up their testing early in their outbreak, thus at the peak of their outbreak the nation only had 0.002% of the uninfected population becoming infected per day (see Figure 3 below). As noted in my first article on COVID-19 (link here), it took 0.004% of Italy's uninfected population becoming infected each day to put hospitals at capacity, with some hospitals becoming overwhelmed when this metric reached 0.010%. Thus when taking a look at where each state stands as far as safety in loosening restrictions, I checked the state's daily postive test rate (to see if their is sufficient testing) and the daily rate at which the uninfected population is becoming infected (to see if the rate of new cases per day is low enough as to not overwhelm the state's medical system). Based on that analysis, it looks as though some state governments are following politics rather than the data within their own state. For example I found states where the daily rate of infections was too high and/or testing was not sufficient and yet are going ahead with lifting some restrictions. I also found states that are doing quiet well with testing and had low daily infection rates, and yet restrictions remain in place. However their was some good news in that there were plenty of states whose decisions on keeping or lifting restrictions seem to align with the latest data. I divided the state's into multiplie tiers depending on these findings, to see which tier your state falls into, see section below titled "updated data for the United States." Here is my advice based on which tier your state belongs: Tiers 2 and 5: 1) Even though your state or city may not be under strict stay at home orders, because of a lack of testing and/or a high enough number of new COVID-19 cases per day, 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) 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. Tier 4: 1) Continue following your state's stay at home order, your state either has a lack of testing and/or a high enough number of new COVID-19 cases per day. This means trying 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) 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. Tier 3: 1) Your state has a lower number of new cases per day and has sufficient testing, and the state government has already or is planning to lift some restrictions in the coming days. Even reduced restrictions does not mean a complete return to normal as some restrictions may still be in place. So please check your local news and local/state government websites for the latest rules. Tier 1: 1) Continue to follow your state's stay at home order. Perhaps there should be a discussion encouraged about reducing restrictions as your state has a lower concentration of new cases per day and sufficient testing activity. Tier 6: 1) There are currently a low number of new COVID-19 cases per day in your state and there is sufficient testing, and your state does not have a blanket stay at home order. However the lack of a blanket order may not mean there are no restrictions, check your local news and local/state government websites for the latest rules.


...SOURCES FOR DATA...

1) For global COVID-19 case count, as well as the total number of tests in each nation, https://www.worldometers.info/coronavirus/ 2) For a state by state breakdown in the United States, including the total number of tests each state has ran, https://www.worldometers.info/coronavirus/country/us/


...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. I calculate the mortality rate as: mortality rate % = (Total Deaths/Total Number of Cases)*100 And finally I calculate the daily positive test rate as: % of daily tests positive = (New Cases Today/Total Tests Ran Today)*100 Some states or nations do not update the total number of tests ran each day. So if this value is updated every four days for example, a four-day average is calculated by summing the total number of new cases over the last four days, and dividing by the number of tests ran over the last four days.


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

Figure 1 - Approximation of percent chance of becoming infected in all 50 states in the United States. 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.



Figure 2 - Current state of COVID-19 testing in the United States.


The 5-day trends in Figure 1 should not be taken as an interpretation of whether strict stay at home orders work or not. For example in my previous article (link here) I remarked that Michigan was seeing an overall decrease in new cases per day, and yet in Figure 1 Michigan is marked with a 5-day increase. But when looking longer term, beyond 5 days, in fact Michigan is seeing an overall slowdown in new cases per day since the implementation of the state's stay at home order. This phenomenon apperas to be due to short-term spikes on the way down from the peak of an outbreak, for example multiple short-term spikes are seen in Italy's data after Italy's peak in Figure 3 below. Therefore looking at trends longer than 5 days appears to be a better practice, but I have only recently begun looking at data in all 50 states such that I can only look at 5-day trends at the present time. Meanwhile, data and discussion showing the effectiveness of stay at home orders is in my first article on COVID-19 (link here). In some states, a recent 5-day increase in new number of cases per day seems to coincide with an increase in the number of tests ran per day, for example a look at Illinois, Massachusetts, New Hampshire, and Nebraska in Figures 1 and 2. Because many states as shown in Figure 2 are still at a current testing defecit, we can expect an increase in the new number of cases per day as testing ramps up to where it needs to be for safe state reopenings. I judged that if states were yellow or green in BOTH Figures 1 and 2, i.e. a state has sufficient testing AND has a low enough number of new cases per day, then that state would be safe to loosen restrictions. Unfortunately the loosening of restrictions seems to have some political motivations rather than simple objective motivations driven by data. Thus I divided states into the following six tiers as follows: Tier 1, States that I think are safe to reduce restrictions on by May 1 but are not going to have reduced restrictions: *Oregon, low concenration of new cases per day, sufficient testing, but no plans to lift restrictions *Vermont, low concentration of new cases per day, sufficent testing, current stay at home order ends May 15 *West Virginia, low concenration of new cases per day, sufficient testing, but no plans to lift restrictions Tier 2, States that I think are unsafe to reduce restrictions but have already or will have reduced restrictions by May 1: *Alabama, high concentration of new cases per day and insufficient testing, stay at home order expires April 30 *Arizona, even though concentration of new cases per day is on the low side, there is insufficient testing, stay at home order expires April 30 *Colorado, high concentration of new cases per day and insufficient testing, some non-essential businesses will be allowed to reopen on April 26 *Florida, even though there is sufficient testing, high concentration of new cases per day. Beaches were reopened on April 17 with other restrictions expiring April 30. *Georgia, high concentration of new cases per day and insufficient testing, some non-essential businesses were allowed to reopen on April 24. *Indiana, high concentration of new cases per day and insufficient testing, current stay at home order expires April 30. *Louisiana, high concentration of new cases per day and a signficant lack of testing, current stay at home order expires April 30. *Maine, even though there is a low concentration of new cases pewr day, there is a lack of testing. Current stay at home order expires April 30. *Minnesota, even though there is a low concentration of new cases pewr day, there is a lack of testing. Outdoor recreational activities were allowed on April 17, with additional restrictions expiring May 4. *Mississippi, high concentration of new cases per day and insufficient testing, some non-essential business will be allowed on April 27. *Nevada, high concentration of new cases per day and insufficient testing, current order set to expire on April 30. *Ohio, high concentration of new cases per day and insufficient testing, current order set to expire on May 1. *South Carolina, even though there is a lower concentration of new cases per day, there is insufficient testing, current order set to expire on April 27. *Tennessee, even though there is sufficient testing, there is a higher concentration of new cases per day, current order set to expire on April 30. Tier 3, States that I agree with reduced restrictions by May 1: *Alaska, sufficient testing with a low concentration of new cases per day, some non-essential business was allowed on April 24 *Hawaii, low concentration of new cases per day and sufficient testing, stay at home order expires April 30 *Idaho, low concentration of new cases per day and sufficient testing, stay at home order expires April 30 *Montana, low concentration of new cases per day and sufficient testing, stay at home order expires April 26 *Texas, low concentration of new cases per day and sufficient testing, state parks were allowed to reopen on April 20 and some non-essential businesses were allowed to offer retail-to-go on April 24 Tier 4, States that I agree keeping restrictions through May 1 or later: *California, even though there is sufficient testing, the number of new cases per day remains elevated. No plans to lift restrictions as of now. *Connecticut, very high concentration of new cases per day and insufficient testing, current order expries May 20. *Illinois, high concentration of new cases per day and insufficient testing, stay at home order recently extended to May 30. *Delaware, high concentration of new cases per day and insufficient testing, stay at home order expires May 15. *Kansas, high concentration of new cases per day and insufficient testing, stay at home order expires May 3. *Kentucky, even though there is a low concentration of cases per day, there is insufficient testing to re-open, no end date to current stay at home order at this time. *Maryland, high concentration of new cases per day and insufficient testing, no end date to current stay at home order at this time. *Massachusetts, high concentration of new cases per day and insufficient testing, govenor indicates stay at home order may have to be extended beyond its current expiration of May 4. *Michigan, high concentration of new cases per day and insufficient testing, stay at home order recently extended to May 15 *Missouri, even though there is a lower concentration of new cases per day, there is insufficient testing, current stay at home order set to expire May 3. *New Hampshire, even though there is sufficient testing, a high concentration of new cases per day is currently present, stay at home order to expire May 4. *New Jersey, very high concentration of new cases per day and insufficient testing, no end date to stay at home order at this time *New Mexico, high concentration of new cases per day and insufficient testing, stay at home order to expire May 15. *New York, very high concentration of new cases per day and insufficient testing, stay at home order to expire May 15. *North Carolina, even though there is sufficient testing, there is a high concentration of new cases per day (just after Figure 1 was created, North Carolina's latest data now puts the state "red" instead of "yellow"). Stay at home order recently extended to May 8. *Pennsylvania, high concentration of new cases per day and insufficient testing, current stay at home order expires on May 8. *Rhode Island, very high concentration of new cases per day and insufficient testing, stay at home order to expire May 8. *Virginia, high concentration of new cases per day and insufficient testing, current stay at home order expires June 10. *Washington, despite sufficient levels of testing, Washington's latest data just after Figure 1 was created now puts the state back into the "red" from "yellow." Current stay at home order expires May 4. *Wisconsin, insufficient testing, and just after Figure 1 was created Wisconsin's data puts the state into the "red" zone. Stay at home order to expire May 26. Tier 5, States that never had blanket strict stay at home order that I think should be under one: *Arkansas, although there is sufficient testing, there remains a high concentration of new cases per day *Iowa, insufficient testing and elevated concentration of new cases per day *Nebraska, insufficient testing and elevated concentration of new cases per day *North Dakota, even though there is sufficient testing, there remains an elevated concentration of new cases per day *South Dakota, insufficient testing and elevated concentration of new cases per day *Utah, even though there is sufficient testing, there remains an elevated concentration of new cases per day. There has been a stay at home recommendation without force of law. Tier 6, States that never had blanket strict stay at home order that I think are okay: *Oklahoma, low concentration of new cases per day and sufficient testing *Wyoming, low concentration of new cases per day and sufficient testing

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

Figure 3 - 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 few days.


See Figure 3 for my updated forecast philosophy, next week to follow average of previous couple of days. Note the jump in new number of cases in the United States over the last couple of days, which coincides directly with an increase in the number of tests ran daily in the United States. This means the outbreak is not intensifying, but rather we are getting a better grasp of who actually has and who actually doesn't have COVID-19 as the testing increases nationally. 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 flattening to about 5.7% over the last several days. 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. April 25 has totaled at 960896 cumulative cases, and so far today (April 26) the cumulative case count has reached 987160 as of 8:24 PM EDT. Therefore this latest forecast is verifying fairly accurately thus far.


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