Quick Model of the Predicted Spread of the Corona Virus

To satisfy my own curiosity, I created a simple model of the multigenerational spread of the CoronaVirus. I'm not an expert on public health so I'm not certain of the assumptions and process of a spreading virus but I know the mathematics is correct. 

Anyway, here's a snapshot of a table based on the following assumptions:

• Generational disease spread originating from one person over 11 generations. (I have no idea if 11 generations is reasonable, but I wanted to provide some sense of how widely the disease could spread.) 
• Each infected person spreads the disease to 3.8 other people. 
• Mortality rate is .02 (2% or crude rate of 2000 per 100,000)
• I guessed that it would take 36 hours for each person to spread the disease to the 3.8 other people. I don't take my timescale all that seriously but it provides some sense of how fast a disease could spread.

The table below shows the spread from single origination point and from 50 origination points. The number of days that it would take to generate these numbers based on my timescale assumption is about 17 days. (These tables have been updated. The death rate in my original tables was .03 not .02. These tables have a death rate of .02.)

Generation	0	1	2	3	4	5	6	7	8	9	10	11
Number infected in Generation	1	4	14	55	209	792	3,011	11,442	43,478	165,216	627,821	2,385,721
Running total infected	1	5	19	74	283	1,075	4,086	15,527	59,005	224,221	852,043	3,237,763
Total deaths	0	0	0	1	6	21	82	311	1,180	4,484	17,041	64,755
Multiple Origination Points Infected	50	190	722	2,744	10,426	39,618	150,547	572,078	2,173,896	8,260,805	31,391,059	119,286,025
Running total infected	50	240	962	3,706	14,131	53,749	204,296	776,374	2,950,270	11,211,075	42,602,134	161,888,159
Total deaths	1	5	19	74	283	1,075	4,086	15,527	59,005	224,221	852,043	3,237,763

I have to admit, I gasped when I saw these numbers and thought, I hope this isn't the case. But if the government takes action to stem the infection rate from 3.8 to 2, here's what you get:

Generation	0	1	2	3	4	5	6	7	8	9	10	11
Number infected in Generation	1	2	4	8	16	32	64	128	256	512	1,024	2,048
Running total infected	1	3	7	15	31	63	127	255	511	1,023	2,047	4,095
Total deaths	0	0	0	0	1	1	3	5	10	20	41	82
Multiple Origination Points Infected	50	100	200	400	800	1,600	3,200	6,400	12,800	25,600	51,200	102,400
Running total infected	50	150	350	750	1,550	3,150	6,350	12,750	25,550	51,150	102,350	204,750
Total deaths	1	3	7	15	31	63	127	255	511	1,023	2,047	4,095

The situation becomes far, far more manageable. In addition, the actions the government should take should reduce the number of generations the virus is allowed to spread to others. 

Having seen these numbers, it makes sense to me why South Korea is doing mass testing. The faster you can get infected people out of the environment where they can infect other people, the more manageable the epidemic becomes. In addition, this suggests that barriers and changes in people's behavior to slow the spread of the virus would significantly assist in stemming epidemic.

What Should You Do to Protect Yourself, Your Loved Ones and Your Fellow Citizens?

I prefer not to provide anyone with advice regarding what you should do. However, I'll happy to provide you with expert resources. So ...

Here's the CDC website for the CoronaVirus: https://www.cdc.gov/coronavirus/2019-ncov/index.html

Here's the website for the National Institute of Health: https://www.nih.gov/health-information/coronavirus 

My Comments Regarding the Trump Administration

Now, let's see if in the US, the Trump Administration is able to get it's act together. That news conference on 26 Feb 2020 was not all that reassuring. It was clear that Trump himself is completely clueless about the situation he and his administration are facing and what to do about it. Putting Pence at the head of the effort wasn't reassuring at all. As Governor of Indiana, Pence's policies lead to an outbreak of HIV in southern Indiana. And it took Pence far too long to respond and take actions that addressed the epidemic.(https://www.washingtonpost.com/politics/2020/02/27/mike-pence-hiv-indiana/) 

Let us all continue to monitor the situation going forward.

I'll admit that I have an intense dislike of Trump and the growing group of servile sycophants that surround him. This Administration is corrupt and incompetent, and headed by someone who requires obsequiousness, but careless nothing about competence and truth. 

My opinion has only been reinforced by the Trump Administration's statement that all information, interviews and and statements regarding the CoronaVirus must be cleared through Pence and thus filtered through the administration. In other words, the Administration just muzzled Dr. Anthony Fauci and others. This should scare everyone. Public health should never be politicized, but it appears that it now has. 

I can admit to you that I didn't like the Bush Administration either for a whole host of reasons beginning with lying to get the US into a war with Iraq. But, I can say when it came to concerns about public health, both nationally and internationally, they were not all that bad. 

I feel that I give Administrations credit where credit is due and criticize them when their actions and policies do damage. And from what I have seen, Trump and his Administration has done little to make things better and done lots of damage. And things are only getting worse.


Here's an article from the Washington Post regarding a newly filed whistle blower complaint: https://www.washingtonpost.com/health/2020/02/27/us-workers-without-protective-gear-assisted-coronavirus-evacuees-hhs-whistleblower-says/

Deaths from Despair Part 3: Across US Metropolitan Areas

When I was analyzing suicide data, I subdivided the data by a variety of factors, both by single factors and multiple factors. One of those factors that proved itself as something of interest was the metropolitan area where the suicide victim resided. What I found was that the smaller the metropolitan area, the higher the suicide rate relative to the other metropolitan areas in each year. This was particularly true in more recent years. Since, death by suicide is one of measurements included in death from despair it makes sense to examine this data using as a factor in the analysis, metropolitan area. 

The figure below shows the death rate from despair for the six 2013 US metropolitan areas. The death rate for all metropolitan areas is shown as a dashed line.

Several things jump out from the figure above:

• The rate of death from despair from 1999 to 2018 has doubled and no metropolitan area has been spared.
• Death rates dropped from 2017 to 2018 except for large metropolitan and noncore areas.
• In 1999 large central metropolitan areas had the highest rate of death from despair. However, by 2018, they had the lowest rate. 
• In 1999 large fringe metropolitan areas had the lowest rate of deaths from despair while the other metropolitan areas were more tightly bunched.
• Over time, two clusters have developed: 1) large metropolitan areas and 2) medium-small metropolitan areas. Large metropolitan areas fall under the overall rate while the medium-small metropolitan areas are over the overall rate.

The figure below shows the year to year trends for large and medium-small metropolitan areas. And the figure that follows shows the year to year differences between the rates of death from despair for medium-small and the large metropolitan areas. 

These two figures show that while death rates from despair have increased dramatically in both clusters, the gap between large and medium-small metropolitan areas has grown over time with more deaths from despair occurring more frequently in medium-small metropolitan areas than in large metropolitan areas.

One of the reasons for the difference in rates of death may in part be due to the fact that economic opportunities have continued to shift to large metropolitan areas and economic opportunities continue to diminish in medium-small areas. That may help explain the difference we're seeing between large and medium-small areas. However, deaths from despair continue to increase in all metropolitan areas at an alarming rate. If economic opportunity were the explanation, then one would expect large metropolitan areas to be showing a dramatically lower rate of increase or no increase at all or maybe even a decrease in the rate of death from despair, but that's not what we're seeing. 

Deaths from despair have been increasing, but they have been increasing at a faster pace in medium-small than in large metropolitan areas in the US. 

Deaths from Despair Part 2: Gender as a Factor

Before I get into the data, I want to mention that the 2018 data has been loaded on the CDC's Wonder database (https://wonder.cdc.gov). I'll update some of recent findings using this new data. The new data has changed my projections for 2025. They're less dire than my earlier projections, nevertheless, they're still unacceptable. I'll discuss the updated projections at the end of this article.

My approach in this series of articles is to first consider single factor comparisons before I drill down into multi-factor comparisons and trend analysis. In this article I focus on gender. In later articles I'll focus on age, race, Hispanic, size of the community, etc. I'll also divide the data into two groups: 1) drug and alcohol deaths and 2) suicides, and analyze the data by the same list of single factors used to analyze deaths from despair. After the single factor analysis, I'll focus on multi-factor comparisons. 

Deaths from Despair: Gender Comparisons

From my analysis of suicide and drug-overdose deaths data, I found that there were clear differences between men and women. You'll note that there are clear gender differences when it comes to deaths from despair as you'll note in the figures below.

In terms of the number of deaths per 100,00 (crude rate), men die in much greater numbers than women. The difference is stark. Furthermore, the trend lines are decidedly different. In both cases, the trend is upwards, but with women the curve is linear, meaning the rate remains the same from year to year. However, the trend line for men is curvilinear, meaning that the rate of increase is accelerating.

One positive things to note is that in 2018 for both men and women, the number of deaths dropped from 2017. However, as I noted before, the number of drug overdose deaths for 2017 jumped dramatically from 2016, well beyond my worst case expectations. The hope is that the 2018 results suggest a downward trend, but it may be that the 2018 suggest only a slowing of the rate of increase, not a change in direction. A signal of a change in direction would be that the number of deaths in 2018 was less than 2016 and that's not the case.

Updates to Trend Lines

I want to mention that I have updated the trend line for Total (men and women combined) as a result of the addition of the 2018 data point. Although a 3rd order curve is a slightly better fit, the 2nd order curve better accounts for the addition of the 2018 data. And as you'll note has a lower acceleration rate.

Number of Deaths

The figure below shows the actual number of deaths for women, men and total number. 

The figure above puts the problem the US faces in stark terms. Yes, there was a drop in the total number of deaths from despair from 2017 to 2018, but any way you look at it nearly 157,000 (total) deaths from despair each year is unacceptable as well as all of the unnecessary deaths from despair during this 20 year period from 1999 to 2018. 

What's Going on in America? Why is this happening?

I've started reading the book by Kristof and WuDunn, Tightrope (2020). There are a couple of quotes from their book that I believe are applicable here:

• "Gallup found that Americans are among the most stressed populations in the world, tied with Iranians and even more stressed than Venezuelans." 
• "America now lags behind its peer countries in health care and high-school graduation rates while suffering greater violence, poverty and addiction."

The numbers and the trends provide further support to these quotes. And I believe help explain why these numbers are so high. 

I'll discuss more of the possible reasons why Americans die with such frequency from despair in later articles. 

Gender Differences

Women may be dying less from despair than men -- about 1/3 as many per year. But approximately 45,000 deaths per year in 2017 and 2018 is a number that should be of great concern. And then one examines the number of men dying from despair. Yes, women do seem to be more resilient, but there are levels of stress can overcome even the most resilient.

The nearly 112,000 men dying in the last two years should be significant concern. In contrast approximately 115,000 Americans died each year as a result of conflict in World War II, the bloodiest war in world history. For America the time for that war was just over three and a half years. And here we're seeing over 20 years each year deaths in the range of what you would expect in a full scale war. And these are avoidable deaths. 

Projections to 2025

The following two figures show my current projections from 2019 to 2025. 

These projections are based on my current trend lines as shown in the first figure. 

I have the greatest confidence in the projected trend line for women. Based on everything that we have seen, deaths from despair for women will continue to increase the steady pace shown in the figures. I have less confidence in the trend for men. Accelerated growth is difficult to project into the future.

The trend line to 2025 combining men and women (total) that includes the 2018 data shows about 100,000 fewer deaths projected for 2025 than my earlier projection. That earlier figure is shown below.

217,000 deaths instead of 331,000 is over one third fewer, but 217,000 deaths is still a staggering number of deaths from despair. But even if the number of per year deaths remained the same from year to year from 2018, 157,000 total deaths each year is a staggering number of avoidable deaths, in this case, from despair.