Random Analytica

Charts, Infographics & Analytics. No Spinning the Data. No Juking the Stats

Tag: USA

Random Analytica: The United States of Violence

Two must read stories this week. CNN have listed the top mass shootings in the US since 1949 and The New York Times put together a thoughtful piece on how the shooters were able to obtain their weapons.

After the Port Arthur massacre in 1996 where 35 were killed by a deranged shooter Australia introduced sweeping gun control laws and removed access to military grade weapons. Since that time we have not had one mass shooting incident yet the United States of America continues to have mass shootings and the body counts are escalating.

It is my very strong view that civilians don’t need military grade weapons, bump stocks and silencers. Full-stop.

For my part I have put together an infographic on the nine worst mass shootings by an individual in the United States since 1949 which now includes the Marjory Stoneman Douglas High School shootings and highlights the array of military grade weapons utilised by the perpetrators.

Each weapon represents those killed.

This is done in solidarity with the kids of Marjory Stoneman Douglas High School who are peacefully protesting against the gun culture in America today. I hope for their sake that they rid American streets of military grade weapons and end the culture mass shootings.

MassShootingsUSA_180214

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Random Analytica: Most Cumulative Time In Space

I was in a discussion with the kids over the weekend over who had spent the most time in space. Astronaut Peggy Whitson broke a number of records for Team USA late last year but interestingly the board is stacked with Soviets, then Russians who comprise 90% of the top-10 and 80% of the top-50 given they have operated space stations since 1971 (starting with Salyut-1).

That discussion turned into a quick Top-10 chart.

MostCumulativeTimeInSpace

Note: M1-M6 represents separate mission flight times. The Soviet Union flag has been used for those cosmonauts who were accepted into the space program prior to 1991.

Random Analytica: Dow Jones Industrial Average closes up 567-points (+2.3%)

A lot of talk yesterday about the big losses experienced on Wall Street with the Dow Jones down 1,175-points, the first time that index has declined by more than 1,000-points in a single day.

Crash, tumble and wipe-out were utilised frequently across news channels and social media. The #TrumpSlump hashtag was overutilised by many who really don’t understand markets.

In relative terms yesterday’s Dow Jones numbers were not the worst day of historical trading although they did break the previous point’s loss record. In fact, it didn’t even rate in the top 100 of trading day points losses. My thoughts are here along with a couple of charts.

Today the conversation is all about volatility as the Dow Jones returned almost half of yesterday’s losses.

In fact, the Dow Jones Industrial Average had its 4th best day on record (in terms of points gained). Here is the updated top 20 chart.

180206_DJIA_PointsGained

To get within ‘coo-wee’ of needing to update the Biggest One-Day % Gains chart we would need a +7% increase which would equate to an approximate 1,750-point gain in a single day.

With volatility returning to the markets we might get more updates to this chart in coming weeks.

Random Analytica: Dow Jones Industrial Average closes down 1,175-points (-4.6%)

The Dow Jones Industrial Average closed down 1,175.21 points overnight losing 4.6% of its value in one-day of trading. That is the single worst day in terms of points but is it the worst day ever?

The simple answer is NO. In fact it doesn’t even rate in the top 20!

Here are a couple of charts to prove that point.

180205_DowJonesIndustrialAvg_Points

In terms of points the Dow Jones Industrial Average did have its worst day on record. The previous record was a loss of 777.68 points on the 29th September 2008 at the height of the Global Recession.

Here is a look at the top-20 worst losses as a percentage which is the more accurate reflection of yesterday’s trading day in the United States.

180205_DowJonesIndustrialAvg_Percentage

In terms of percentage the Dow Jones Industrial Average did not have its worst day ever. In fact, yesterday’s trading losses do not even rate in the top 20 worst days on record.

Black Monday was the worst day on record. Here is a reminder of what that headline looks like. Via the Australian Broadcasting Commission. No, this wasn’t the worst day on the Dow Jones — we’ve seen worse. Excerpt:

October 19, 1987

Known as Black Monday in America, this was the day that 22.61 per cent was lost from the Dow Jones. This was followed by Black Tuesday in Australia, when the ASX plunged a massive 25 per cent in response.

871021_SydneyMorningHerald

Photo: Front page of the Sydney Morning Herald, 21st October 1987, the day after the stock market crash via the Australian Broadcasting Commission.

Big technical stock exchange losses make for great headlines. The Dow Jones Industrial Average had a bad day and the Australian Stock Exchange is following that lead in response but it’s not the worst day ever.

Not even close.

Random Analytica: Guantanamo Detainees 2009 – 2018

Ian Bremmer, the President of the Eurasia Group sent out an interesting tweet yesterday which highlighted the amount of detainees held by the US Military at Guantanamo Bay since 2009. Interestingly there were 214 detainees held at the prison in 2009 when then President Obama ordered the facility closed. Today there are still 41 detainees including Hambali who is accused of orchestrating the 2002 Bali Bombings and has still not faced trial.

GuantanamoDetainees2018

The New York Times has an excellent interactive project site with all the details and is well-worth a look. The Guantanamo Docket. Overview:

About the Project

The Guantánamo Docket is an interactive database of documents and analysis from The New York Times about the roughly 780 men who have been detained at Guantánamo as enemy combatants since January 2002.

The Times has reviewed thousands of pages of government documents released in recent years, as well as court records and news media reports from around the world. The Times will update the database with ongoing research.

There are three types of documents in the database:

Combatant Status Review Tribunals

The database includes Pentagon documents related to the Combatant Status Review Tribunals, military hearings created in response to a 2004 decision by the United States Supreme Court to judge whether prisoners at Guantánamo were properly designated as enemy combatants and subject to indefinite detention. The hearings took place from July 2004 to March 2005.

Administrative Review Boards

The database also includes documents from subsequent Administrative Review Boards, panels of military officers conducting annual hearings to determine whether the detainees remain a threat to the United States or its allies.

These documents, along with the documents related to the Combatant Status Review Tribunals, were selected for public disclosure by the U.S. Defense Department in 2006 in response to a lawsuit brought under the Freedom of Information Act by The Associated Press.

Joint Task Force Assessments

The database also includes a selection of classified documents from the Guantánamo Joint Task Force, part of a huge trove of secret documents leaked last year to the anti-secrecy organization WikiLeaks. They were made available to The Times by another source on the condition of anonymity. The files contain the government’s assessment of the dangers the individuals represent. The files are dated from February 2002 to January 2009, and some of the information may have been superseded by later, still undisclosed assessments made during the Obama administration or by more highly classified documents.

The documents contain the Defense Department’s assessments of the detainees, some of which have been challenged in federal court, and in some of the cases lower court judges have ruled against evidence presented by the government. Those cases have been appealed.

In June 2013, the Justice Department released a list showing who of the remaining Guantánamo detainees has been recommended for transfer, prosecution or continued detention without trial. The list, released under the Freedom of Information Act, represents the final recommendations of a task force of national-security agencies President Obama put together in 2009 as part of his unfulfilled pledge to close the prison within a year. The group issued a report in early 2010, but its individual recommendations were not included in that document.

Lastly, a copy of the tweet by Ian Bremmer which kicked off the idea for the infographic.

180201_Tweet_IanBremmer_Guantanamo

UPDATES

13 Feb 2018: Amended first paragraph to include Hambali story.

 

Random Analytics: West African Ebola Outbreak (to 5 Nov 2014)

The World Health Organisation (WHO) has updated it latest advice on the Ebola Outbreak. Ebola Response Roadmap Situation Report 7 November 2014. Summary:

A total of 13 268 confirmed, probable and suspected cases of Ebola virus disease (EVD) have been reported in six currently affected countries (Guinea, Liberia, Mali, Sierra Leone, Spain, the United States of America) and two previously affected countries (Nigeria, Senegal) up to the end of 4 November 2014. There have been 4960 reported deaths.

Following the WHO Ebola Response Roadmap structure, country reports fall into two categories: 1) those with widespread and intense transmission (Guinea, Liberia, and Sierra Leone); and 2) those with or that have had an initial case or cases, or with localized transmission (Mali, Nigeria, Senegal, Spain, and the United States of America).

Here are three charts/infographics of the West African Outbreak with data confirmed by WHO to 5 November 2014.

01 - Ebola_WAfricaOutbreakTableau_141108

The West African Ebola Outbreak (2013-2014) infographic details the cases, fatalities, provisional Case Fatality Rate (CFR) and health spend per capita in 2012 $USD.

The data point of interest for me in the past fortnight has been the revision in numbers that WHO has provided. In the most recent update case numbers in Sierra Leone have been significantly revised down, while in Liberia where cases are on the apparent wane the numbers were revised upwards. Data for Mali has been included in this update.

02 - Ebola_WAfricaOutbreakChart_141108

The West African Ebola Outbreak (by Nation) chart looks at the split between those recovered or still in treatment (highlighted by flag) and those deceased (in red).

A data point of interest here is the case difference between Sierra Leone and Guinea yet a similar amount of deaths. Provisional CFR is Sierra Leone is 23.2% compared to Guinea which is a much higher 59.9%. Surely that can’t be correct?

03 - WestAfrica_Cases~FatalitiesMonth_141108

The West African EVD Outbreak – All Cases/Fatalities by month details the epidemiological curve of the outbreak from March 2014 when the first cases and deaths became apparent. Each column is visualised by the flag of the eight impacted countries. Note: Due to revisions in late October as provided by WHO I have finalised the October numbers as at 2 November.

The data point of interest in the last chart is the epidemic curve differences between cases (still rising) and deaths (decreasing). I would have expected that both should increase or decrease in tandem. I suspect missing data would account for the anomaly.

Summary

I’ll update and post my charts again when the data becomes available for the entirety of November. In the meantime if you want to keep across the West African outbreak detail via some alternate sources then I would recommend Crawford Kilian and for more regular epidemiological posts Maia Majumder, MPH and Ian Mackay, PhD.

 

Data Sources

[1] World Bank. Health expenditure per capita (current US$). Accessed 8 November 2014.
[2] World Health Organisation. WHO: Ebola Response Roadmap Situation Report 7 November 2014. Accessed 8 November 2014.

Random Analytics: West African Ebola Outbreak (to 18/19 Oct 2014)

The World Health Organisation (WHO) has updated it latest advice on the Ebola Outbreak. Ebola Response Roadmap Situation Report 22 October 2014. Summary:

Summary

A total of 9936 confirmed, probably, and suspected cases of Ebola virus disease (EVD) have been reported in five affected countries (Guinea, Liberia, Sierra Leone, Spain, and the United States of America) and two previously affected countries (Nigeria and Senegal) up to the end of 19 October. A total of 4877 deaths have been reported.

The outbreaks of EVD in Senegal and Nigeria were declared over on 17 October and 19 October 2014, respectively.

EVD transmission remains persistent and widespread in Guinea, Liberia, and Sierra Leone. All but one administrative district in Liberia and all administrative districts in Sierra Leone have now reported at least one confirmed or probably case of EVD since the outbreak began. Cases of EVD transmission remain lowest in Guinea, but case numbers are still very high in absolute terms. Transmission remains intense in the capital cities of the three most affected countries. Case numbers continue to be under-reported, especially from the Liberian capital Monrovia.

Of the countries with localized transmission, both Spain and the United States continue to monitor potential contacts. On 21 October the single patient with EVD in Spain tested negative for the disease for a second time. Spain will be declared free of EVD 42 days after the date of the second negative test unless a new case arises during that period.

On 22 October 2014, WHO convened the third Emergency Committee on Ebola under the International Health Regulations (2005).

Here are three charts or infographics of the West African Outbreak with data confirmed by WHO to 18/19 October 2014.

01 - Ebola_WAfricaOutbreakTableau_141023

 

The West African Ebola Outbreak (2013-2014) infographic details the cases, fatalities, the provisional Case Fatality Rate (CFR) and health spend per capita in 2012 $USD.

Midway through October the biggest data find for me has been the difference between the index cases in Senegal and the United States. Lots of similarities but IMO four very important differences:

  1. Both cases entered the country without disclosing the possibility that they may have been exposed to Ebola;
  2. Both cases presented to hospital shortly after arrival in the destination country;
  3. Difference One: In the case of Thomas Eric Duncan who travelled to the USA he presented at hospital but was released back into the community. He presented again three days later (interestingly a key and important fact left out of the official CDC Overview) with more extreme symptoms. In the Senegal case the patient sought treatment in Dakar giving no indication he may have Ebola but was not released and a day later Senegalese authorities linked him to other cases. He was subsequently quarantined;
  4. Difference Two: In the USA contract tracing was slow to be implemented while PPE protocols were inadequate which resulted in the spread of the disease amongst Health Care Workers (HCW). In Senegal no HCW were infected.
  5. Difference Three: The USA index case died of the disease; potentially due to those critical days where he was without care while in Senegal the patient recovered and has returned to Guinea.
  6. Difference Four (and this is the key one which you can see in the infographic): The average health spend per capita in the USA is $8,895 (in 2012 $USD money) while Senegal makes do with just $51 per person. That’s 174 times less than the USA.

02 - Ebola_WAfricaOutbreakChart_141023

The West African Ebola Outbreak (by Nation) chart looks at the split between those recovered or still in treatment and those deceased. As per the latest update from WHO there is an element of underreporting going on in the worst impacted countries (Liberia, Sierra Leone and Guinea).

03 - WestAfrica_Cases~FatalitiesMonth_141023

The West African EVD Outbreak – All Cases/Fatalities by month details the epidemiological curve of the outbreak from March 2014 when the first cases and deaths became apparent. Each column is visualised by the flags of the seven impacted countries.

The mid-month data-find from this chart is that the epidemic curve in relation to deaths continues to increase month on month yet the case load seems to be pulling back. All the anecdotal evidence coming out of West Africa points to an increasing, rather than a decreasing case load as individuals, families and population centres avoid health care facilities. In past months, the case load mid-month would be approximately equal to the previous month. Best case scenario would be that West Africa is getting on top of the disease but the facts-on-the-ground don’t support this. I’d expect to see some revisions to the data in coming weeks and months.

Summary

I’ll update and post my charts again when the data becomes available for the entirety of October. In the meantime if you want to keep across the West African outbreak detail via some alternate sources then I would recommend Crawford Kilian and for more regular epidemiological posts Maia Majumder, MPH and Ian Mackay, PhD.

 

Data Sources

[1] World Bank. Health expenditure per capita (current US$). Accessed 23 October 2014.
[2] World Health Organisation. WHO: Ebola Response Roadmap Situation Report 22 October 2014. Accessed 23 October 2014.

Random Analytics: Ebola in the USA? Time for some context

Back at the end of September when the Thomas Eric Duncan Ebola case was first diagnosed in Texas and hit the headlines Ebola went from being an African issue to become an American problem. Social media exploded on the subject, Twitter mentions on Ebola tripled overnight and news agencies across the Western world struggled to keep up with the renewed interest.

Most of the analysis has been very good but some of the commentary has been downright crazy.

CNN did a story on how some US Republicans are calling for stronger border controls by linking Ebola with ISIS. As crazy as the idea of mixing the Ebola and ISIS narrative is CNN itself asked the same question prompting The Independent to write ‘The Isis of biological agents?’: CNN is asking the stupid Ebola questions.

1 - CNN_Ebola~ISIS

Stupid is as stupid does is not just reserved for the United States. In my own country of Australia a recently returned nurse was hospitalised on fears she may have contracted the disease after registering a mild fever. This incident had Bob Katter, the federal member for Capricornia suggesting a ban on people travelling to Australia from West Africa and calling for all returning Health Care Workers to be put into government isolation upon their return (the nurse in question was actually in self-imposed home isolation).

Anyway, I thought the debate on the one case in the United States against the 8,398 in Western Africa (as per the most recent WHO update) was worth putting in context. An infographic:

2 - EbolaCasesbyFlagSize_8Oct2014

The West African Ebola Outbreak – Cases by Country is a look at the six countries impacted by the disease with data to 7/8 October 2014. Each individual country is represented by their flag and the size of their flag is a percentile proportion of total cases.

As you can see Liberia has 48.5% of all cases, followed by Sierra Leone (35.1%), Guinea (16.1%) and Nigeria (0.2%). Both the USA and Spain have one case each which equates to 0.000119% of all cases and too small to be represented by a flag.

The story of Thomas Eric Duncan is tragic and the entry of a disease like Ebola into the West is scary but we need to get some context on how bad the situation is.

 

To the Lost

 

Data Sources

[1] Hooten, C. ‘The Isis of biological agents?’: CNN is asking the stupid Ebola questions. The Independent. 7 October 2014. Accessed 12 October 2014.
[2] World Health Organisation. WHO: Ebola Response Roadmap Situation Report 10 October 2014. Accessed 12 October 2014.

Random Analytics: Romney’s Promise

Just two weeks out from the US election it may be worth noting a promise made by Mitt Romney during the first debate held in Denver on the 3rd October 2012.

He stated that “If I’m president, I will create, help create 12 million new jobs in this country with rising incomes”.

This is a big promise. Let’s put aside the promise about rising incomes (as the Economist recently noted US median incomes have reversed over the last 15-years after peaking in 1999) and unpack some of the data in relation to US employment.

If he were to win the US Presidency Mr Romney’s administration would need to create 250,000 new jobs per month which would equal 750,000 per quarter or 3-million per year.

Figure 1: US Employment gains & losses by quarter (please note that Q1 is Jan – Mar). Data sourced from the US Bureau of Labour Statistics.

Over the past 10-years and nine-months (129-months of data) there have been just 11-months where employment gains exceeded 250,000. To be fair April 2004 had a gain of 249,000 so let’s allow that one as a conceded pass thus increasing the total to 12. There have only been two periods where the employment increased at more than 250K in consecutive months, that is the first quarter of 2006 (during the height of the pre-GFC period) and the first two months of 2012. On the negative ledger the months where employment losses exceeded 250,000 also tally 12. Between August 2008 and July 2009 the US economy officially shed 6.874-million jobs over 12-months. Over the past 10-years no other month saw a loss of more than 250,000 except for that period.

In terms of quarterly data there have only been two quarters where employment increase by more than 750,000 (Q2-2005 and Q1-2006). On the negative side the period Q3-2008 through to Q3-2009 were five consecutive quarters where job losses exceeded 750,000. In the first quarter of 2009 the US economy lost more than 2.3-million jobs, more than three times the Romney target but moving in the wrong direction.

Figure 2: US Working Population 2002 – 2012 (updated with October 2012 data). Data sourced from the US Bureau of Labour Statistics.

To add to both Mr Romney and Mr Obama’s concerns are not just creating new jobs but also keeping pace with new entrants to the workforce which I would estimate could be between 300,000 – 900,000 per annum depending on how you might calculate the increase. For all the talk of the impending crunch time due to baby boomer exits there has been a sustained increase in the US working aged population over the past decade as shown in Figure 2. The red line reflects BLS actuals, an increase of 10-million workers in the past decade. The black polynomial trend-line I’ve added to highlight the incline-decline-incline impacts of the GFC. However way you cut it, even a minimum increase in new entrants adds another 10% to the annual job creation burden.

In economics we have a saying. Unemployment goes down the elevator but re-employment has to climb the stairs. Just looking at these two graphs highlights some of my concerns with Mitt Romney’s aspiration of creating more than 250,000 jobs over a sustained 48-month period.

Looking at the data, even in the best of times the task would have been incredibly hard. I still think the global employment situation has a lot of downside risk. Even with recent improved employment data I don’t believe the US is out of the woods yet, in fact I suspect we might see further soft, even negative employment data next year in the US.

For Mitt, if he were to get over the line I would suggest he might have promised in haste and will regret in leisure.

Update (6/11/2012): Given the recent discussion around the US unemployment figures for October, which showed a provisional increase of 171,000 non-farm jobs but an overall rise in the unemployment figure from 7.8% to 7.9% I thought an update of the US Working Population graphic would be useful. Between September and October 2012 the US Working Population (those in the civilian labour force) actually increased from 155,075,000 to 155,779,000 or an increase of 704,000. Interestingly, the available Working Population figure was at its highest in Jul 2008 at 156,300,000 so although this months figures may seem high to some there is still a reasonable amount of elasticity in this number (thus it doesn’t represent a truly high figure at this stage).

Random Analytics: Australian Unemployment: A Global Perspective (Oct 2007 – Sep 2012)

I had an interesting discussion today about Australia’s recent increase in its official unemployment rate which rose to 5.4% (seasonally adjusted). That percentile equates to 662,700 unemployed persons. It has been my consistent view that the current unemployment and participation rate data is softened by factors such as seasonal adjustment and under-reporting. My point here is that the real unreported figure could be higher due to severance economy issues and as Australia transitions from an overall boom economy to, at best, a more globally normalised economy.

Rather than focus on that rather negative sentiment I thought it might be useful to have a look at some global data to get a sense of perspective. Here is a look at the official (seasonally adjusted) unemployment figures for Australia, the USA, UK, Spain & Greece.

Figure 1: Unemployment (seasonally adjusted) for Australia, USA, UK, Spain & Greece. Data sourced from the ABS, BLS, ONS & EuroStat.

That gold line which has trended under or around 5% for the entirety of the Global Financial Crisis is Australia.

For the other countries represented in the graph the last five years have been dark days indeed. The US (dark blue), still the world’s largest economy has an official unemployment figure of 7.8% (or 12.1-million persons). The UK (in green) sits at 7.9% (2.57-million) trending at 8% or thereabouts since mid-2009. Then there are the current horror stories of Greece & Spain, both of which now have official Euro high unemployment figures of 25.1%. For Spain there are 5.77-million and Greece 1.26-million unemployed, a total of 7.03 million unemployed for both countries. Put in context this equals more than 60% of the total current Australian Labour force.

So things might not be great in Australia at the moment as we see layoffs across some sectors of the economy and our official unemployment figures nudge up.

I’m happy to bet that you would still rather be in Australia with this economy than in Greece or Spain with their economies?