The current behavior is that if a country crosses the 100 mark on COVID- 19, the diffusion of cases to reach the 1,000 mark takes five to seven days as per behavioral studies done. This calculation can vary on the culture of the country and density of the population.
China took four days to cross the 1,000 mark after reaching 100, Italy six days, Iran five days, Spain seven days, South Korea six days, Germany and US eight days, which is why the medical fraternity was pressurizing the Government to go for a lockdown so that we keep the numbers below 100. Especially given the ‘family-oriented’ culture that exists in Sri Lanka and the ageing population, the ramifications can be heavy.
However, the President was strongly of the view that location specific curfews and ‘identify and isolate’ is the strategy that will work in Sri Lanka. He went on to state that with this strategy, if implemented with the support of the general public, the COVID-19 curve can be flattened The Financial Times
This repository contains the source code, models, and example usage of the COVID-19 Vulnerability Index (CV19 Index). The CV19 Index is a predictive model that identifies people who are likely to have a heightened vulnerability to severe complications from COVID-19 (commonly referred to as “The Coronavirus”). The CV19 Index is intended to help hospitals, federal / state / local public health agencies and other healthcare organizations in their work to identify, plan for, respond to, and reduce the impact of COVID-19 in their communities.
Versions of the CV19 Index
There are 3 different versions of the CV19 Index. Each is a different predictive model for the CV19 Index. The models represent different tradeoffs between ease of implementation and overall accuracy. A full description of the creation of these models is available in the accompanying paper, "Building a COVID-19 Vulnerability Index" (http://cv19index.com).
The 3 models are:
Simple Linear - A simple linear logistic regression model that uses only 14 variables. An implementation of this model is included in this package. This model had a 0.731 ROC AUC on our test set.
Open Source ML - An XGBoost model, packaged with this repository, that uses Age, Gender, and 500+ features defined from the CCSR categorization of diagnosis codes. This model had a 0.810 ROC AUC on our test set.
Free Full - An XGBoost model that fully utilizes all the data available in Medicare claims, along with geographically linked public and Social Determinants of Health data. This model provides the highest accuracy of the 3 CV19 Indexes but requires additional linked data and transformations that preclude a straightforward open-source implementation. ClosedLoop is making a free, hosted version of this model available to healthcare organizations. For more information, see http://cv19index.com.
Step 1 — Making a Labeled Data Set
Data on COVID-19 hospitalizations does not yet exist. While data begins to emerge, we can look at the affected populations and events that serve as proxies for the real event. Given that the disease’s worst outcomes are concentrated on the elderly, we can focus on medicare billing data. Instead of predicting COVID-19 hospitalizations, we can instead predict proxy medical events, specifically hospitalizations due to respiratory infections. Examples include Pneumonia, Influenza, and Acute bronchitis. We identify these labels by parsing medical billing data and searching for specific ICD-10 codes that describe these types of events. All predictions are made on a specific day. From a particular day, we look back in time 15 months for features. We exclude any events happening within three months of the prediction date, due to the lag in medical claims data reporting. Any diagnoses within the last year become the features we use in all of our models.
Step 2 — Models
There are hosts of model considerations that need to be made with these kinds of projects. Ultimately, we wanted these models to balance being as effective as possible, and still accessible to healthcare data scientists as quickly as possible. One of the reasons for choosing the data that we used is because medicare claims data is widely available to healthcare data scientists. If your organization has access to additional data sources, you may observe performance increases by incorporating such information. Balancing those considerations led us to create 3 models based on the ease of adoption and model effectiveness.
The first, is a logistic regression model using a small number of features. At ClosedLoop, we use the standard Python data science stack. The motivation for a very simple model is that it can be ported to environments like R or SAS without having to read or write a line of python. At low alert rates, the model performs close to parity with the more sophisticated versions of the model. The aforementioned white paper has all of the weights for the limited feature set, so it can be ported over by hand.
We evaluate the model using a full train/test split. The models are tested on 369,865 individuals. We express model performance using the standard ROC curves, as well as the following metrics:
“What is new in the world? Nothing. What is old in the world? Nothing. Everything has always been and will always be.” – Shirdi Sai Baba
Sai Baba of Shirdi, also known as Shirdi Sai Baba, was an Indian spiritual master who was regarded by his devotees as a saint, fakir, and satguru, according to their individual proclivities and beliefs. He was revered by both his Hindu and Muslim devotees and during, as well as after, his life it remained uncertain if he was a Hindu or a Muslim. This, however, was of no consequence to Sai Baba. He stressed the importance of surrender to the true Satguru or Murshid, who, having trod the path to divine consciousness, will lead the disciple through the jungle of spiritual training.
Sai Baba is worshipped by people around the world. He had no love for perishable things and his sole concern was the realization of the self.
He taught a moral code of love, forgiveness, helping others, charity, contentment, inner peace, and devotion to God and guru.
He gave no distinction based on religion or caste. Sai Baba’s teaching combined elements of Hinduism and Islam: he gave the Hindu name Dwarakamayi to the mosque in which he lived, practised Muslim rituals, taught using words and figures that drew from both traditions, and was buried in Shirdi. One of his well-known epigrams, “Sabka Malik Ek” (“One God governs all”), is associated with Hinduism, Islam and Sufism. He also said, “Trust in me and your prayer shall be answered”. He always uttered, “Allah Malik” (“God is King”).
If you are wealthy, be humble. Plants bend when they bear fruit.
Spend money in charity; be generous and munificent but not extravagant.
Whatever creature comes to you, human or otherwise, treat it with consideration.
See the divine in the human being.
There is a wall of separation between oneself and others
and between you and me. Destroy this wall!
I get angry with none.
Will a mother get angry with her children?
Will the ocean send back the waters to several rivers?
What is our duty?
To behave properly. That is enough.
God is not so far away. He is not in the heavens above,
nor in hell below. He is always near you.
If you cannot endure abuse from another,
just say a simple word or two, or else leave.
I stay by the side of whoever repeats my name.
Do not be obsessed with egotism,
imagining that you are the cause of action:
everything is due to God.
Do not fight with anyone,
nor retaliate, nor slander anyone.
All gods are one. There is no difference
between a Hindu and a Muslim.
Mosque and temple are the same.
When you see with your inner eye. Then you realize
that you are God and not different from Him.
To God be the praise.
I am only the slave of God.
Choose friends who will stick to you till the end,
“The fool doth think he is wise, but the wise man knows himself to be a fool,”wrote Shakespeare in As You Like It. Little did he know, but this line perfectly encapsulates the spirit of the Dunning-Kruger effect.
The Dunning-Kruger effect is a type of cognitive bias in
which people believe that they are smarter and more capable than they really
are. Essentially, low ability people do not possess the skills needed to
recognize their own incompetence. The combination of poor self-awareness and
low cognitive ability leads them to overestimate their own capabilities.
The term lends a scientific name and explanation to a
problem that many people immediately recognize—that fools are blind to their
own foolishness. As Charles Darwin wrote in his book The Descent of Man,
"Ignorance more frequently begets confidence than does knowledge."
An Overview of the Dunning-Kruger Effect
This phenomenon is something you have likely experienced in
real life, perhaps around the dinner table at a holiday family gathering.
Throughout the course of the meal, a member of your extended family begins
spouting off on a topic at length, boldly proclaiming that he is correct and
that everyone else's opinion is stupid, uninformed, and just plain wrong. It
maybe plainly evident to everyone in the room that this person has no idea
what he is talking about, yet he prattles on, blithely oblivious to his own
ignorance.
The effect is named after researchers David Dunning and
Justin Kruger, the two social psychologists who first described it. In their
original study on this psychological phenomenon, they performed a series of
four investigations.
People who scored in the lowest percentiles on tests of
grammar, humour, and logic also tended to dramatically overestimate how well
they had performed (their actual test scores placed them in the 12th
percentile, but they estimated that their performance placed them in the 62nd
percentile).
The Research
In one experiment, for example, Dunning and Kruger asked
their 65 participants to rate how funny different jokes were. Some of the
participants were exceptionally poor at determining what other people would
find funny—yet these same subjects described themselves as excellent judges of
humour.
Incompetent people, the researchers found, are not only poor
performers, but they are also unable to accurately assess and recognize the quality
of their own work. This is the reason why students who earn failing scores on
exams sometimes feel that they deserved a much higher score. They overestimate
their own knowledge and ability and are incapable of seeing the poorness of
their performance.
Low performers are unable to recognize the skill and
competence levels of other people, which is part of the reason why they
consistently view themselves as better, more capable, and more knowledgeable
than others.
"In many cases, incompetence does not leave people
disoriented, perplexed, or cautious," wrote David Dunning in an article
for Pacific Standard. "Instead, the incompetent are often blessed with an
inappropriate confidence, buoyed by something that feels to them like
knowledge."
This effect can have a profound impact on what people
believe, the decisions they make, and the actions they take. In one study,
Dunning and Ehrlinger found that women performed equally to men on a science
quiz, and yet women underestimated their performance because they believed they
had less scientific reasoning ability than men. The researchers also found that
as a result of this belief, these women were more likely to refuse to enter a
science competition.
Dunning and his colleagues have also performed experiments
in which they ask respondents if they are familiar with a variety of terms
related to subjects including politics, biology, physics, and geography. Along
with genuine subject-relevant concepts, they interjected completely made-up
terms.
In one such study, approximately 90 per cent of respondents
claimed that they had at least some knowledge of the made-up terms. Consistent
with other findings related to the Dunning-Kruger effect, the more familiar
participants claimed that they were with a topic, the more likely they were to
also claim they were familiar with the meaningless terms. As Dunning has
suggested, the very trouble with ignorance is that it can feel just like
expertise.
Causes of the Dunning-Kruger Effect
So what explains this psychological effect? Are some people
simply too dense, to be blunt, to know how dim-witted they are? Dunning and
Kruger suggests that this phenomenon stems from what they refer to as a
"dual burden." People are not only incompetent; their incompetence
robs them of the mental ability to realize just how inept they are.
Incompetent people tend to:
Overestimate their own skill levels
Fail to recognize the genuine skill and expertise of other
people
Fail to recognize their own mistakes and lack of skill
Dunning has pointed out that the very knowledge and skills
necessary to be good at a task are the exact same qualities that a person needs
to recognize that they are not good at that task. So if a person lacks those
abilities, they remain not only bad at that task but ignorant to their own
inability.
An Inability to Recognize Lack of Skill and Mistakes
Dunning suggests that deficits in skill and expertise create
a two-pronged problem. First, these deficits cause people to perform poorly in
the domain in which they are incompetent. Secondly, their erroneous and
deficient knowledge makes them unable to recognize their mistakes.
The Dunning-Kruger effect is as follows: "People with low skill levels draw wrong conclusions and make wrong decisions, but are unable to make mistakes because of their low skill levels".
This means: a lack of understanding of mistakes made leads to a belief in one's own correctness and, consequently, to increased confidence in one's own decisions and in oneself, as well as to an awareness of one's own superiority.
Thus, the Dunning-Kruger effect is a psychological paradox that we all often face in life: less competent people see themselves as professionals, while more competent people tend to doubt themselves and their abilities. The lower the skill level, the higher the self-confidence. At beginning of their research, Dunning and Kruger called Charles Darwin's famous statement: "Ignorance breeds confidence more often than knowledge" and Bertrand Russell: "It is one of the unfortunate things of our time that those who are confident are stupid, and those who have imagination or understanding are full of doubt and indecision
A Lack of Metacognition
The Dunning-Kruger effect is also related to difficulties
with metacognition, or the ability to step back and look at one's own behaviour
and abilities from outside of oneself. People can often only evaluate
themselves from their own limited and highly subjective point of view. From
this limited perspective, they seem highly skilled, knowledgeable, and superior
to others. Because of this, people sometimes struggle to have a more realistic
view of their abilities.
A Little Knowledge Can Lead to Overconfidence
Another contributing factor is that sometimes a tiny bit of
knowledge on a subject can lead people to mistakenly believe that they know everything about it. As the old saying goes, a little bit of knowledge
can be a dangerous thing. A person might have the slimmest bit of awareness
about a subject, yet thanks to the Dunning-Kruger effect, believe that he or
she is an expert.
Other factors that can contribute to the effect include our
use of heuristics, mental shortcuts that allow us to make decisions quickly,
and our tendency to seek out patterns even where none exist. Our minds are primed
to try to make sense of the disparate array of information we deal with on a
daily basis. As we try to cut through the confusion and interpret our own
abilities and performance within our individual worlds, it is perhaps not
surprising that we sometimes fail so completely to accurately judge how well we
do.
Who Is Affected by the Dunning-Kruger Effect?
So who is affected by the Dunning-Kruger effect?
Unfortunately, we all are. This is because no matter how informed or
experienced we are, everyone has areas in which they are uninformed and
incompetent. You might be smart and skilled in many areas, but no one is an
expert at everything.
The reality is that everyone is susceptible to this
phenomenon, and most of us experience it with surprising
regularity. People who are genuine experts in one area may mistakenly believe
that their intelligence and knowledge carry over into other areas in which they
are less familiar. A brilliant scientist, for example, might be a very poor
writer. For scientists to recognise their lack of skill, they
need to possess a good working knowledge of things such as grammar and
composition. Because those are lacking, the scientist in this example cannot also recognize their own poor performance.
The Dunning-Kruger effect is not synonymous with low IQ. As
awareness of the term has increased, its misapplication as a synonym for
"stupid" has also grown. It is, after all, easy to judge others and
believe that such things simply do not apply to you.
So if the incompetent tend to think they are experts, what
do genuine experts think of their own abilities? Dunning and Kruger found that
those at the high end of the competence spectrum held more realistic views of their knowledge and capabilities. However, these experts tended to underestimate their abilities relative to how others did.
Essentially, these top-scoring individuals know that they
are better than the average, but they are not convinced of how superior their
performance is compared to others. The problem, in this case, is not that
experts don't know how well-informed they are; they tend to believe that everyone else is also knowledgeable.
Is There Any Way to Overcome the Dunning-Kruger Effect?
So is there anything that can minimize this phenomenon? Is
there a point at which the incompetent actually recognize their own ineptitude?
"We are all engines of misbelief," Dunning has suggested. While we
are all prone to experiencing the Dunning-Kruger effect, learning more about
how the mind works and the mistakes we are all susceptible to might be one step
toward correcting such patterns.
Dunning and Kruger suggest that as experience with a subject increases, confidence typically declines to more realistic levels. As people
learn more about the topic of interest, they recognise their lack
of knowledge and ability. Then as people gain more information and become experts on a topic, their confidence levels begin to improve again.
So what can you do to gain a more realistic assessment of
your abilities in a particular area if you are not sure you can trust your self-assessment?
Keep learning and practising. Instead of assuming you know
all there is to know about a subject, keep digging deeper. Once you gain
greater knowledge of a topic, you will more likely recognize how much
there is still to learn. This can combat the tendency to assume you’re an
expert, even if you're not.
Ask other people how you're doing. Another effective
strategy involves asking others for constructive criticism. While it can
sometimes be difficult to hear, such feedback can provide valuable insights
into how others perceive your abilities.
Question what you know. Even as you learn more and get
feedback, it can be easy to only pay attention to things that confirm what you
think you already know. This is another type of psychological
bias known as confirmation bias. To minimize this tendency, keep
challenging your beliefs and expectations. Seek out information that challenges
your ideas.
அவமானங்கள்தான் வாழ்க்கையின் ஆசான். அவமானம் கத்துக்கொடுப்பது மாதிரியான பாடத்தை எந்த மகத்தான புத்தகமும் கத்துக்கொடுக்காது.அவமானங்களைத் தன்மானத்தோடு எதிர்கொள்வதே வெகுமானம்தான் .
அவமானங்களே ஒரு மனிதனை வெற்றியின் அரியாசனத்தில் அமர்த்தும். அவமானம் என்பது ஒரு மனிதனுக்கு தூண்டுகோள்தான்.
மனிதனின் மனம் அவமானங்களை கண்டால் முதலில் துவண்டாலும், வைராக்கியம் மனதில் உருவாகும்.
அதுவே முயற்சியில் வேகத்தை கொடுத்து வெற்றிக்கு வழி வகுக்கும்.
ஒருவனது அவமானங்கள்தான் அவனை கடினமாக உழைக்க வைக்கிறது.
ஒருவனது அவமானங்கள்தான் கடுமையாய் முன்னேற வேண்டும் என்கின்ற வெறியை தூண்டுகிறது.
ஒருவனது அவமானம்தான் வாழ்கையில் மிகப்பெரிய வெற்றியாக உருமாற்றுகிறது. ஒரு சின்ன அவமானம் கூட இல்லாமல் யாரும் உயர்ந்துவிட முடியாது.
அவமானப் படுத்துகிறவர்களை நாம் அவமானப்படுத்தினாலோ அல்லது அவர்கள்மீது ஆத்திரமடைந்தாலோ அவமானப்பட்டதாகக் காட்டிக் கொண்டாலோ அவமானப்படுத்தியவனைப் பொருட்படுத்தியதாகிவிடும். அதற்காகத்தானே அவர்கள் ஆசைப்படுகிறார்கள். அவர்களை நாம் உதாசீனப்படுத்துவது தான் நல்லது. நாம் ஆத்திரமடையும்போது உள்ளத்தளவு மட்டுமல்ல உடலளவும் பாதிக்கப்படுகிறோம்.
அமெரிக்க ஜனாதிபதியாக ஆப்ரகாம் லிங்கன் தேர்ந்தெடுக்கப்பட்டு முதல்முறையாக நாடாளுமன்றத்தில் பேச எழுகிறார். அப்போது உறுப்பினர் ஒருவர் அவரை அவமானப்படுத்த வேண்டும் என்பதற்காக எழுந்து “நான் அணிந்திருக்கும் செருப்பை உங்களுடைய தந்தையார் தான் தைத்துத் தந்தார்; நன்றாக இருக்கிறது. அதற்கு நன்றி” என்றதும் தன்னை ஒரு செருப்பு தைக்கும் தொழிலாளியின் மகன் என்று இழிவுபடுத்தியதாகக் கருதி ஆத்திரப்படாமல் “மகிழ்ச்சி. அந்த செருப்பில் ஏதாவது பழுது ஏற்பட்டால் கொண்டு வாருங்கள்… நான் திருத்தித் தைத்துத் தருகிறேன். எனக்கும் செருப்புத் தைக்கும் தொழில் தெரியும்” என்று கூறினாராம். சராசரி மனிதர்கள் சினந்து சிவப்பார்கள். சரித்திரம் படைப்போர் எதற்கும் சலனப்பட மாட்டார்கள்.அவமானப் படுகிறவர்கள்தான் அதிகமாக வெற்றியாளர்கள் ஆகிறார்கள். அவமானங்களை உடைத்தெறிய வேண்டுமொனால் அவமானப்படுத்தியவனிடம் மோதிக் கொண்டிருப்பதைவிடத் தாம் பெறுகிற வெற்றிகளால் அவர்களை வெட்கித் தலைகுனியச் செய்யவேண்டும். சார்லி சாப்ளின் படாத அவமானங்களா? அவரது தோற்றம் கேலிக்குரியதாக இருந்திருக்கிறது அவரது வறுமை அவரை அவமானப் படுத்தியிருக்கிறது. அவற்றை உடைத்தெறிந்து உயர்ந்தார்.சிவாஜிகணேசன் வானொலி குரல் தேர்வுக்குச் சென்றபோது தேர்ந்தெடுக்கப்படவில்லை. ஆனால் பின்னாளில் அவர் 'சிம்மக்குரலோன்'. அதுபோல அமிதாப்பச்சன் நடிக்கவந்த நேரம் நிராகரிக்கப்பட்டவர். பின்னாளில் அவர் சூப்பர் ஸ்டார்.
மறக்கக்கூடாது
அவமதித்தவர்களை மறந்துவிட வேண்டும். ஆனால் அவமானங்களை மறக்கக்கூடாது. அதை அடுத்தடுத்த தளங்களுக்கான வெற்றிப் பயணத்தின் பாதையாக்கிக் கொள்ளவேண்டும்.வந்தனா சைனி என்ற சிந்தனையாளர் “அவமானங்களை மறவாதீர் உங்கள் வெற்றிக்கான விதைகள் அவற்றில் உள்ளன” என்பார்.அவமானங்களில் வெற்றிக்கான விதைகள் இருக்கின்றன என்பது உண்மைதான். அதற்காக வெற்றிபெற வேண்டுமானால் அவமானப்பட வேண்டும் என்றும் அர்த்தப்படுத்திக் கொள்ளக்கூடாது. “நான் வெற்றியாளனாக வேண்டும். தயவு செய்து யாராவது வந்து கொஞ்சம் அவமானப்படுத்துங்கள்” என்று கேட்டுக் கொண்டிருக்க முடியாது. அவமானங்களைத் தாங்கிக் கொள்ளுங்கள் என்பதுதான் நம் அறிவுரையே தவிர அவமானங்களைக் கேட்டு வாங்கிக் கொள்ளுங்கள் என்பது அல்ல.
தாங்கி கொள்ளுங்கள்
அவமானத்தைத் தாங்கிக் கொள்வதோடு நின்றுவிட வேண்டும். அதற்காகப் பழிவாங்கும் எண்ணம் வளர்த்துக் கொள்வது நல்லதல்ல. நேரம் வரும் வரைக் காத்திருந்து அவமானப்படுத்தியவரை அவமானப்படுத்த நினைப்பது கேவலமானது. அதுவரை அந்தக் குப்பையை மனத்தில் வைத்துக்கொள்வதும் தீதானது.நாம் அவமானப் படுத்தப்பட்டபோது எப்படி உணர்ந்தோமோ அப்படித்தானே நம்மால் அவமானப் படுத்தப்பட்டவர்களும் உணர்வார்கள் என எண்ணவேண்டும்.ஆறுதல் பெறுவற்காகவோ ஆத்திரத்தை தீர்த்துக் கொள்வதற்காகவோ நமக்கு நேர்ந்த அவமானத்தை மற்றவர்களிடம் பகிர்ந்து கொள்வது கூடாது. அப்படிச் செய்வதின் மூலம் நமது அவமானத்திற்குப் பிரமாதமான விளம்பரத்தை நாமே தேடிக் கொண்டிருக்கிறோம் என்பதோடு, மீண்டும் நம்மை நாமே அவமானம் செய்து கொள்கிறோம். அவமானங்களை மறந்துவிடுவதோடு, அவமதிப்பவர்களை மன்னித்து விடுங்கள்.அவமானங்களைத் தவிர்த்துக் கொண்டும் தாங்கிக் கொண்டும் அடுத்தடுத்த வெற்றிப் பயணங்களுக்கு ஆயத்தமாகுங்கள். அவமானம் உங்களுக்கு ஒரு வெகுமானமாகும்.- ஏர்வாடி எஸ். இராதாகிருஷ்ணன்எழுத்தாளர், சென்னை94441 07879
