February 2020 Jobs Report and Industry Update

 


Economics & Job Creation:

“THE EMPLOYMENT SITUATION — January 2020”

Life Sciences:
“Normal resting heart rate appears to vary widely from person to person”

Technology:
“Portable lab you plug into your phone can diagnose illnesses like coronavirus”

Healthcare:
“Cancer-causing culprits will be caught by their DNA fingerprints”

The Industrials:
“Unveiling a new map that reveals the hidden personalities of jobs”

Human Capital Solutions, Inc. (HCS) www.humancs.com is a Retained Executive Search firm focused in Healthcare, Life Sciences, the Industrials, and Technology. Visit our LinkedIn Company Page to learn more about HCS and receive weekly updates.

HCS has created the Prosperity at Work proposition which focuses on creating prosperous relationships between companies and their employees (associates). HCS assists companies in improving bottom line profitability by efficiently planning, organizing and implementing optimized, practical and value-added business solutions.

 

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Economics & Job Creation:

THE EMPLOYMENT SITUATION — JANUARY 2020

Total nonfarm payroll employment rose by 225,000 in January, and the unemployment rate
was little changed at 3.6 percent, the U.S. Bureau of Labor Statistics reported today.
Notable job gains occurred in construction, in health care, and in transportation and
warehousing.

This news release presents statistics from two monthly surveys. The household survey
measures labor force status, including unemployment, by demographic characteristics.
The establishment survey measures nonfarm employment, hours, and earnings by industry.
For more information about the concepts and statistical methodology used in these two
surveys, see the Technical Note.

Household Survey Data

Both the unemployment rate, at 3.6 percent, and the number of unemployed persons, at
5.9 million, changed little in January. (See table A-1. For information about annual
population adjustments to the household survey estimates, see the note at the end of
the news release and tables B and C.)

Among the major worker groups, the unemployment rates for adult men (3.3 percent),
adult women (3.2 percent), teenagers (12.2 percent), Whites (3.1 percent), Blacks
(6.0 percent), Asians (3.0 percent), and Hispanics (4.3 percent) showed little or
no change over the month. (See tables A-1, A-2, and A-3.)

Among the unemployed, the number of reentrants to the labor force increased by
183,000 in January to 1.8 million but was little changed over the year. (Reentrants
are persons who previously worked but were not in the labor force prior to beginning
their job search.) (See table A-11.)

The number of long-term unemployed (those jobless for 27 weeks or more), at 1.2 million,
was unchanged in January. These individuals accounted for 19.9 percent of the unemployed.
(See table A-12.)

After accounting for the annual adjustments to the population controls, the civilian
labor force rose by 574,000 in January, and the labor force participation rate edged
up by 0.2 percentage point to 63.4 percent. The employment-population ratio, at 61.2
percent, changed little over the month but was up by 0.5 percentage point over the year.
(See table A-1. For additional information about the effects of the population adjustments,
see table C.)

The number of persons employed part time for economic reasons, at 4.2 million, was
essentially unchanged in January. These individuals, who would have preferred full-time
employment, were working part time because their hours had been reduced or they were
unable to find full-time jobs. (See table A-8.)

The number of persons marginally attached to the labor force, at 1.3 million, changed
little in January. These individuals were not in the labor force, wanted and were available
for work, and had looked for a job sometime in the prior 12 months. They were not counted
as unemployed because they had not searched for work in the 4 weeks preceding the survey
for a variety of reasons, such as belief that no jobs are available for them (referred
to as discouraged workers), school attendance, or family responsibilities. Discouraged
workers numbered 337,000 in January, little changed over the month. (See Summary table A.)

Establishment Survey Data

Total nonfarm payroll employment increased by 225,000 in January, compared with an
average monthly gain of 175,000 in 2019. Notable job gains occurred in construction,
in health care, and in transportation and warehousing. (See table B-1. For information
about the annual benchmark process, see the note at the end of the news release and table A.)

In January, construction employment rose by 44,000. Most of the gain occurred in specialty
trade contractors, with increases in both the residential (+18,000) and nonresidential
(+17,000) components. Construction added an average of 12,000 jobs per month in 2019.

Health care added 36,000 jobs in January, with gains in ambulatory health care services
(+23,000) and hospitals (+10,000). Health care has added 361,000 jobs over the past 12 months.

Employment in transportation and warehousing increased by 28,000 in January. Job gains
occurred in couriers and messengers (+14,000) and in warehousing and storage (+6,000).
Over the year, employment in transportation and warehousing has increased by 106,000.

Employment in leisure and hospitality continued to trend up in January (+36,000). Over
the past 6 months, the industry has added 288,000 jobs.

Employment continued on an upward trend in professional and business services in January
(+21,000), increasing by 390,000 over the past 12 months.

Manufacturing employment changed little in January (-12,000) and has shown little movement,
on net, over the past 12 months. Motor vehicles and parts lost 11,000 jobs over the month.

Employment in other major industries, including mining, wholesale trade, retail trade,
information, financial activities, and government, changed little over the month.

In January, average hourly earnings for all employees on private nonfarm payrolls rose by
7 cents to $28.44. Over the past 12 months, average hourly earnings have increased by
3.1 percent. Average hourly earnings of private-sector production and nonsupervisory employees
were $23.87 in January, little changed over the month (+3 cents). (See tables B-3 and B-8.)

The average workweek for all employees on private nonfarm payrolls was unchanged at 34.3
hours in January. In manufacturing, the average workweek remained at 40.4 hours, while
overtime edged down 0.1 hour to 3.1 hours. The average workweek of private-sector production
and nonsupervisory employees edged up by 0.1 hour to 33.6 hours. (See tables B-2 and B-7.)

The change in total nonfarm payroll employment for November was revised up by 5,000 from
+256,000 to +261,000, and the change for December was revised up by 2,000 from +145,000 to
+147,000. With these revisions, employment gains in November and December combined were
7,000 higher than previously reported. (Monthly revisions result from additional reports
received from businesses and government agencies since the last published estimates and from
the recalculation of seasonal factors. The annual benchmark process also contributed to the
November and December revisions.) After revisions, job gains have averaged 211,000 over the
last 3 months.

_____________
The Employment Situation for February is scheduled to be released on
Friday, March 6, 2020, at 8:30 a.m. (EST).

 

https://www.bls.gov/news.release/empsit.nr0.htm

 

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Life Sciences:

“Normal resting heart rate appears to vary widely from person to person”

A person’s normal resting heart rate is fairly consistent over time, but may vary from others’ by up to 70 beats per minute, according to analysis of the largest dataset of daily resting heart rate ever collected. Giorgio Quer of the Scripps Research Translational Institute in La Jolla, California, and colleagues present these findings in the open-access journal PLOS ONE on February 5, 2020 as part of an upcoming PLOS Collection on Digital Health Technology.

A routine visit to the doctor usually involves a measurement of resting heart rate, but such measurements are rarely actionable unless they deviate significantly from a “normal” range established by population-level studies. However, wearables that track heart rate now provide the opportunity to continuously monitor heart rate over time, and identify normal resting heart rates at the individual level.

In the largest study of its kind to date, Quer and colleagues retrospectively analyzed de-identified heart rate data from wearables worn for a median of 320 days by 92,457 people from across the U.S. Nearly 33 million days’ worth of heart rate data were collected in total. The researchers used the data to examine variations in resting heart rate for individuals over time, as well as between individuals with different characteristics.

The analysis showed that one person’s mean daily resting heart rate may differ by up to 70 beats per minute from another person’s normal rate. Taken together, age, sex, body mass index (BMI), and average daily sleep duration accounted for less than 10 percent of the observed variation between individuals.

The authors observed also a small seasonal trend in the resting heart rate, with slightly higher values observed in January and slightly lower values in July. The researchers also found that some individuals may occasionally experience brief periods when their resting heart rate differs by 10 or more beats per minute from their normal range.

These findings suggest the potential value of further research to investigate whether tracking a person’s daily resting heart rate could enable earlier detection of clinically important changes.

The authors add: “Day-to-day changes in resting heart rate could be the first true, individualized digital vital sign, which is only now possible to measure thanks to wearable sensor technologies. We analyzed the extent of inter- and intra-individual changes in resting heart rate over a prolonged period of time, showing distinct patterns of variation according to age and sex, time of the year, average sleep duration and body mass index. These variations in resting heart rate may allow for the identification of early unexpected changes in an individuals’ health.”

 

https://www.sciencedaily.com/releases/2020/02/200205171649.htm

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Technology:

“Portable lab you plug into your phone can diagnose illnesses like coronavirus”

Engineers with the University of Cincinnati have created a tiny portable lab that plugs into your phone, connecting it automatically to a doctor’s office through a custom app UC developed.

The lab the size of a credit card can diagnose infectious diseases such as coronavirus, malaria, HIV or Lyme disease or countless other health conditions like depression and anxiety.

The patient simply puts a single-use plastic lab chip into his or her mouth then plugs that into a slot in the box to test the saliva.

The device automatically transmits results to the patient’s doctor through a custom app UC created for nearly instant results.

UC professor Chong Ahn and his research team used the smartphone device to test for malaria. But the device could be used for smart point of care testing for countless chronic or infectious diseases or to measure hormones related to stress.

“Right now it takes several hours or even days to diagnose in a lab, even when people are showing symptoms. The disease can spread,” Ahn said.

The study was published in the Nature journal Microsystems & Nanoengineering.

His research team created a novel lab chip that uses natural capillary action, the tendency for a liquid to adhere to a surface, to draw a sample down two channels called a “microchannel capillary flow assay.” One channel mixes the sample with freeze-dried detection antibodies. The other contains a freeze-dried luminescent material to read the results when the split samples combine again on three sensors.

Ahn said the device is accurate, simple to use and inexpensive.

“The performance is comparable to laboratory tests. The cost is cheaper. And it’s user-friendly,” Ahn said. “We wanted to make it simple so anyone could use it without training or support.”

UC doctoral student Sthitodhi Ghosh, the study’s lead author, said the biggest advancement in the device is in the novel design of its tiny channels that naturally draw the sample through the sensor arrays using capillary flow. Ahn is Ghosh’s Ph.D. advisor.

“The entire test takes place on the chip automatically. You don’t have to do anything. This is the future of personal healthcare,” Ghosh said.

While the device has applications for diagnosing or monitoring viruses or other diseases, Ahn said he sees potential in the field of mental health, where doctors already utilize smartphones to help track the wellness of patients.

 

https://www.sciencedaily.com/releases/2020/02/200206134748.htm

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Healthcare:

“Cancer-causing culprits will be caught by their DNA fingerprints”

Causes of cancer are being catalogued by a huge international study revealing the genetic fingerprints of DNA-damaging processes that drive cancer development. Researchers from the Wellcome Sanger Institute, Duke-NUS Medical School Singapore, University of California San Diego School of Medicine, the Broad Institute of MIT and Harvard and their collaborators around the world have achieved the most detailed list of these genetic fingerprints to date, providing clues as to how each cancer developed.

These fingerprints will allow scientists to search for previously unknown chemicals, biological pathways and environmental agents responsible for causing cancer.

The research, published in Nature today (5th February) as part of a global Pan-Cancer Project, will help understand the causes of cancer, informing prevention strategies, and help signpost new directions for cancer diagnosis and treatments.

Also published today in Nature and related journals, are 22 further studies from the Pan-Cancer Project. The collaboration involving more than 1,300 scientists and clinicians from 37 countries, analysed more than 2,600 genomes of 38 different tumour types. The project represents an unprecedented international exploration of cancer genomes, which significantly improves our fundamental understanding of cancer and zeros-in on mechanisms of cancer development.

In the UK, someone is diagnosed with cancer every two minutes, with 363,000 new cancer cases every year. The disease causes around 165,000 deaths in the UK annually.

Cancer is caused by genetic changes — mutations — in the DNA of a cell, allowing the cell to divide uncontrollably. Many known causes of cancer, such as UV light and tobacco smoking, leave a specific fingerprint of damage in the DNA, known as a mutational signature. These fingerprints can help understand how cancers develop, and potentially, how they can be prevented. However, past studies have not been large enough to identify all potential mutational signatures.

The fingerprint study identified new mutational signatures that had not been seen before, from single letter ‘typo’ mutations, to slightly larger insertions and deletions of genetic code. The result is the largest database of reference mutational signatures ever. Only about half of all the mutational signatures have known causes, however this resource can now be used to help find more of these causes and better understand cancer development.

Professor Steven Rozen, a senior author from Duke-NUS Medical School, Singapore, said: “Some types of these DNA fingerprints, or mutational signatures, reflect how the cancer could respond to drugs. Further research into this could help to diagnose some cancers and what drugs they might respond to.”

Professor Gad Getz, a senior author from the Broad Institute of MIT and Harvard, and Massachusetts General Hospital, said, “The availability of a large number of whole genomes enabled us to apply more advanced analytical methods to discover and refine mutational signatures and expand our study into additional types of mutations. Our new collection of signatures provides a more complete picture of biological and chemical processes that damage or repair DNA and will enable researchers to decipher the mutational processes that affect the genomes of newly sequenced cancers.”

Another study in the Pan-Cancer Project, published in Nature today, discovered that larger, more complex genetic changes that rearrange the DNA could also act as mutational signatures, and point towards causes of cancer. Researchers from the Wellcome Sanger Institute and the Broad Institute of MIT and Harvard and their collaborators found 16 of these signatures that spanned from rearrangements of single genes to entire chromosomes.

The global Pan-Cancer Project is the largest and most comprehensive study of whole cancer genomes yet. The collaboration has created a huge resource of primary cancer genomes, available to researchers worldwide to advance cancer research.

 

https://www.sciencedaily.com/releases/2020/02/200205132330.htm

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The Industrials:

“Unveiling a new map that reveals the hidden personalities of jobs”

Thousands of Australian students will get their Higher School Certificates this week — how many will choose the ‘right career’?

According to new research published today in the Proceedings of the National Academy of Sciences, understanding the hidden personality dimensions of different roles could be the key to matching a person and their ideal occupation.

The findings of “Social media-predicted personality traits and values can help match people to their ideal jobs” point to the benefit of not only identifying the skills and experience in a particular industry, but also being aware of personality traits and values that characterise jobs — and how they align with your own.

Lead researcher Associate Professor Peggy Kern of the University of Melbourne’s Centre for Positive Psychology notes that “it’s long been believed that different personalities align better with different jobs. For example, sales roles might better suit an extraverted individual, whereas a librarian role might better suit an introverted individual. But studies have been small-scale in nature. Never before has there been such large-scale evidence of the distinctive personality profiles that occur across occupations.”

The research team looked at over 128,000 Twitter users, representing over 3,500 occupations to establish that different occupations tended to have very different personality profiles. For instance, software programmers and scientists tended to be more open to experience, whereas elite tennis players tended to be more conscientious and agreeable.

Remarkably, many similar jobs were grouped together — based solely on the personality characteristics of users in those roles. For example, one cluster included many different technology jobs such as software programmers, web developers, and computer scientists.

The research used a variety of advanced artificial intelligence, machine learning and data analytics approaches to create a data-driven ‘vocation compass’ — a recommendation system that finds the career that is a good fit with our personality.

Co-author Dr Marian-Andrei Rizoui of the University of Technology Sydney said they were able to “successfully recommend an occupation aligned to people’s personality traits with over 70 per cent accuracy.”

“Even when the system was wrong it was not too far off, pointing to professions with very similar skill sets,” he said. “For instance, it might suggest a poet becomes a fictional writer, not a petrochemical engineer.”

With work taking up most of our waking hours, Professor Kern said many people want an occupation that “aligns with who they are as an individual.”

“We leave behind digital fingerprints online as we use different platforms,” said Professor Kern. “This creates the possibility for a modern approach to matching one’s personality and occupation with an excellent accuracy rate.”

Co-author, Professor Paul X McCarthy of the University of New South Wales in Sydney, said finding the perfect job was a lot like finding the perfect mate.

“At the moment we have an overly simplified view of careers, with a very small number of visible, high-status jobs as prizes for the hardest-working, best connected and smartest competitors.

“What if instead — as our new vocation map shows — the truth was closer to dating, where there are in fact a number of roles ideally suited for everyone?

“By better understanding the personality dimensions of different jobs we can find more perfect matches.”

The researchers noted that while the study used publicly available data from Twitter, the underlying vocation compass map could be used to match people using information about their personality traits from social media, online surveys or other platforms.

“Our analytic approach potentially provides an alternative for identifying occupations which might interest a person, as opposed to relying upon extensive self-report assessments,” said Dr Rizoui.

“We have created the first, detailed and evidence based multidimensional universe of the personality of careers — like the map makers of the 19th century we can always improve and evolve this over time.”

 

https://www.sciencedaily.com/releases/2019/12/191216151501.htm

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