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Did an artificial-intelligence (AI) system beat human doctors in warning the world of a severe coronavirus outbreak in China? Here’s a new science and technology news.
In a narrow sense, yes. But what the humans lacked in sheer speed, they more than made up in finesse.
Early warnings of disease outbreaks can help people and governments save lives. In the final days of 2019, an AI system in Boston sent out the first global alert about a new viral outbreak in China. But it took human intelligence to recognize the significance of the outbreak and then awaken response from the public health community.
What’s more, the mere mortals produced a similar alert only a half-hour behind the AI systems.
For now, AI-powered disease-alert systems can still resemble car alarms — easily triggered and sometimes ignored. A network of medical experts and sleuths must still do the hard work of sifting through rumors to piece together the fuller picture. It’s difficult to say what future AI systems, powered by ever larger datasets on outbreaks, may be able to accomplish.
The first public alert outside China about the novel coronavirus came on Dec. 30 from the automated HealthMap system at Boston Children’s Hospital. At 11:12 p.m. local time, HealthMap sent an alert about unidentified pneumonia cases in the Chinese city of Wuhan. The system, which scans online news and social media reports, ranked the alert’s seriousness as only 3 out of 5. It took days for HealthMap researchers to recognize its importance.
Four hours before the HealthMap notice, New York epidemiologist Marjorie Pollack had already started working on her own public alert, spurred by a growing sense of dread after reading a personal email she received that evening.
“This is being passed around the internet here,” wrote her contact, who linked to a post on the Chinese social media forum Pincong. The post discussed a Wuhan health agency notice and read in part: “Unexplained pneumonia???”
Pollack, deputy editor of the volunteer-led Program for Monitoring Emerging Diseases, known as ProMed, quickly mobilized a team to look into it. ProMed’s more detailed report went out about 30 minutes after the terse HealthMap alert.
Early warning systems that scan social media, online news articles and government reports for signs of infectious disease outbreaks help inform global agencies such as the World Health Organization — giving international experts a head start when local bureaucratic hurdles and language barriers might otherwise get in the way.
Some systems, including ProMed, rely on human expertise. Others are partly or completely automated.And rather than competing with one another, they are often complementary — HealthMap is intertwined with ProMed and helps run its online infrastructure.
“These tools can help hold feet to the fire for government agencies,” said John Brownstein, who runs the HealthMap system as chief innovation officer at Boston Children’s Hospital. “It forces people to be more open.”
The last 48 hours of 2019 were a critical time for understanding the new virus and its significance. Earlier on Dec. 30, Wuhan Central Hospital doctor Li Wenliang warned his former classmates about the virus in a social media group — a move that led local authorities to summon him for questioning several hours later.
Li, who died Feb. 7 after contracting the virus, told The New York Times that it would have been better if officials had disclosed information about the epidemic earlier. “There should be more openness and transparency,” he said.
ProMed reports are often incorporated into other outbreak warning systems. including those run by the World Health Organization, the Canadian government and the Toronto startup BlueDot. WHO also pools data from HealthMap and other sources.
Computer systems that scan online reports for information about disease outbreaks rely on natural language processing, the same branch of artificial intelligence that helps answer questions posed to a search engine or digital voice assistant.
But the algorithms can only be as effective as the data they are scouring, said Nita Madhav, CEO of San Francisco-based disease monitoring firm Metabiota, which first notified its clients about the outbreak in early January.
Madhav said that inconsistency in how different agencies report medical data can stymie algorithms. The text-scanning programs extract keywords from online text, but may fumble when organizations variously report new virus cases, cumulative virus cases, or new cases in a given time interval. The potential for confusion means there’s almost always still a person involved in reviewing the data.
“There’s still a bit of human in the loop,” Madhav said.
Andrew Beam, a Harvard University epidemiologist, said that scanning online reports for key words can help reveal trends, but the accuracy depends on the quality of the data. He also notes that these techniques aren’t so novel.
“There is an art to intelligently scraping web sites,” Beam said. “But it’s also Google’s core technology since the 1990s.”
Google itself started its own Flu Trends service to detect outbreaks in 2008 by looking for patterns in search queries about flu symptoms. Experts criticized it for overestimating flu prevalence. Google shut down the website in 2015 and handed its technology to nonprofit organizations such as HealthMap to use Google data to build their own models.
Google is now working with Brownstein’s team on a similar web-based approach for tracking the geographical spread of tick-borne Lyme disease.
Scientists are also using big data to model possible routes of early disease transmission.
In early January, Isaac Bogoch, an infectious disease physician and researcher at Toronto General Hospital, analyzed commercial flight data with BlueDot founder Kamran Khan to see which cities outside mainland China were most connected to Wuhan.
Wuhan stopped outbound commercial air travel in late January — but not before an estimated 5 million people had fled the city, as the Wuhan mayor later told reporters.
“We showed that the highest volume of flights from Wuhan were to Thailand, Japan, and Hong Kong,” Bogoch said. “Lo and behold, a few days later we started to see cases pop up in these places.”
In 2016, the researchers used a similar approach to predict the spread of the Zika virus from Brazil to southern Florida.
Now that many governments have launched aggressive measures to curb disease transmission, it’s harder to build algorithms to predict what’s next, Bogoch said.
Artificial intelligence systems depend on vast amounts of prior data to train computers how to interpret new facts. But there are no close parallels to the way China is enforcing quarantine zones that impact hundreds of millions of people. (VOA)
A garage sale in the 21st century needs a tech-savvy platform. This is where Poshmark comes into the picture, the platform with a community of over 2.5 million Canadians has products listed with over half a billion dollars in value by their users.
It began expanding outside of the United States in Canada in May 2019 and has now launched in India. So its become simple and easy for anyone to sell items from their closet, enabled by a full suite of end-to-end seller tools and services, including seamless listing, merchandising, promotion, pricing, and shipping. Indian consumers will be able to join Social marketplace Poshmark, Inc. (Nasdaq: POSH), a booming community of more than 80 million users and a vibrant network of millions of shoppable closets to make money, save money, connect with others, and foster entrepreneurship.
The platforms scalable model and infrastructure enables continued expansion to new countries and categories in the future. | Photo by Duy Hoang on Unsplash
"As an Indian who grew up exploring the marketplaces of Old Delhi, I know firsthand how important it is to come together and connect as part of the shopping experience. I am confident that our social marketplace will resonate with Indian consumers and allow us to build a thriving and successful community here." The platform's scalable model and infrastructure enables continued expansion to new countries and categories in the future. (IANS/ MBI)
(Article originally written by: N. Lothungbeni Humtsoe)
Keywords: Clothes, garage, Poshmark, India, Old Delhi, social marketplace
Great historic events that have shaped the world and changed the outlines of countries are often not recorded in memory, or so we think. Wars made sure to destroy evidence and heritage, and the ones who survived told the tale of what really happened. Folklore, albeit through oral tradition kept alive many such stories, hidden in verse, limericks, and rhymes.
Ringa-ringa-roses, a common playtime rhyme among children across the world, is an example of folklore that has survived for many centuries. It tells the story of the The Great Plague of London which ravaged the city between 1665-1666.
The Plague broke out from improper disposal of garbage and poor sewage conditions. Fleas from the rats that lived in the sewers spread the disease that killed more than half of London's population. Many people fled from their homes as there was no medicine available for those who were infected.
Beak-shaped masks worn during the Great Plague of London Image source: wikimedia commons
It was around this time that masks began to be invented. The first masks were shaped like beaks, and were worn not to protect the wearer from the disease, but to the prevent them from being able to smell the decay and death around them, which they called 'miasma'. The beaks were filled with floral herbs that allowed doctors and nurses to tend to the sick without being reviled from the smell.
Children are often seen forming circles by holding hands and reciting loudly,
Pockets full of posies
We all fall down"
An illustration of the Great Plague of London, 1665 Image source: wikimedia commons
When the last line is sung, they break the circle and fall down. The roses and posies are believed to be the preferred fragrances inside the masks, and a single sneeze (a-tishoo) was enough to infect the one who was exposed to the disease. Consequently, they fell down, ill, and later died.
An alternative version of this rhyme is sung about the fall of Hiroshima and Nagasaki in the aftermath of World War II. The roses and posies are interchanged with geranium and uranium, to symbolise what was used in the atomic bomb. But this version is not as famous the original.
Keywords: Rhymes, Ringa-ringa-roses, Great Plague of London, WWII, Hiroshima, Nagasaki, Folklore
In modern times, many social movements aim to bring reform to the society we live in, on the basis of certain existing patterns. Patriarchy is something that many aim to cleanse our cultures of, to usher in the era of social and gender equality. Despite all these so-called movements, in southern India, certain societies that patronise matriarchy have existed since before India's independence. The Nairs and Ezhavas of Kerala, and Bunts and Billavas of Karnataka are matrilineal societies that continue to thrive in a patriarchal country.
Kerala remains separate from the rest of India in many ways. Be it literacy policy, form of government, or cultural practices, this state does not always conform to the ideal that India is known for. Even so with their social structure. Certain tribes have remained matrilineal, where the decision-making power rests with the eldest female of the family.
The Nairs and Ezhavas of Kerala, and Bunts and Billavas of Karnataka are matrilineal societies that continue to thrive in a patriarchal country. Image source: wikimedia commons
A male member, who is the close confidante of the matriarch is chosen. He plays a crucial role in representing the male members of his family, and his opinion is highly valued. He is called karavanan. The men reside in separate rooms or in separate houses, and do not interfere in the upbringing of children. Property is also passed down along the lineage of the eldest female. Among the Nairs, matriarchy is more prominently adhered to than the Ezhavas, who have some patrilocal connections.
In Karnataka, the Bunts and Billavas belong to the Tuluva ethnic group. They are also a predominantly matriarchal society, founded on the belief in a legend. Their matrilineal descent is known as Aliyasantana.
The story is told of a demon who threatened to destroy a kingdom if the king did not sacrifice his sons, but the king's sister comes forward to offer her children in sacrifice for the sake of the kingdom. The demon is touched and does not destroy the city. Since then, the kingdom, or the property is inherited through female lineage.
In Karnataka, the Bunts and Billavas belong to the Tuluva ethnic group. They are also a predominantly matriarchal society, founded on the belief in a legend. Image source: wikimedia commons
In the recent past, many of these matriarchal societies have been reduced to matrilineal societies by certain governmental laws. They fall under the patriarchal scheme of the rest of the state but have reserved the right to pass on property and heritage through the female line. In the North east of India, matriarchal dominance is far more resilient than the south.
Keywords: Bunts, Billava, Nair, Ezhava, Aliyasantana, Matrilineal, South India, Karnataka, Kerala