Get smarter, faster. Subscribe to our daily newsletter.
Who's profiting most from the coronavirus outbreak?
Stock markets may be plummeting, but that doesn't mean the spread of COVID-19 is hurting everyone's bottom line.
- The novel coronavirus has so far infected more than 110,000 people and killed nearly 4,000.
- "Stay-at-home" companies — like Netflix and Amazon — seem to be uniquely poised to weather the outbreak.
- Media companies also appear to be profiting from surges in coronavirus-related traffic.
The novel coronavirus, which causes the disease COVID-19, has infected 110,000 people and killed 4,000 across six continents. But the virus is also wreaking economic havoc. Stock markets have plummeted in the wake of the outbreak, with oil stocks leading the decline this week, and some analysts are saying that the virus' spread could push the economy into a recession.
Some companies have proven resistant to the outbreak. This includes sellers of products like N95 respirators, medical face-masks (which don't fully protect people from the virus, according to the Centers for Disease Control and Prevention), and sanitization products, like Clorox. Companies that offer "stay-at-home" products and services are also benefiting from the outbreak, or at least not taking as big of a hit. These include companies like Netflix, Amazon, Zynga, Facebook and Peloton, to name a few.
The investment firm MKM Partners listed those companies and others on its "Stay at Home Index" of stocks it predicts will fare well as the outbreak plays out.
"We tried to identify what products/services/companies would potentially benefit in a world of quarantined individuals. What would people do if stuck inside all day?" said JC O'Hara, chief market technician at MKM Partners, in a recent report. "Rather than attempting to forecast how much lower these stocks may go, we decided to explore which stocks may hold up better."
Samuel Corum / Stringer
Amazon, in particular, is a complicated case. It's reasonable to assume that more people will be staying home and ordering products online, but it's unclear whether the e-commerce giant will be able to control the integrity of its supply chain. As the outbreak has prompted some factories in China to slow or close, Amazon has been stocking up on popular Chinese exported goods, in some cases ordering twice as much as usual, according to a New York Times report.
Besides entertainment and consumer goods companies, digital media companies also seem to be profiting in the wake of the coronavirus outbreak. Data compiled by the GDELT Project compared the amount of online searches for coronavirus with the amount of mentions the outbreak received on the websites of CNN, MSNBC, and Fox News. The results showed that both measures increased sharply in late January, when the first case of coronavirus hit the U.S., and again in late February as the outbreak intensified.
There's currently a debate over how the wall-to-wall media coverage of coronavirus might be fueling irrational panic, but it might be social media that's most fueling the panic — while also revealing some especially malicious and opportunistic attempts to profit from the chaos.
The Washington Post recently reported that the State Department identified more than 2 million tweets containing misinformation and conspiracy theories about the outbreak, and that many of those tweets appeared to be "inauthentic and coordinated activity." The goals of these campaigns aren't exactly clear.
Billy H.C. Kwok / Stringer
The cybersecurity firm Check Point Software recently issued a report detailing how scammers set up the website vaccinecovid-19.com, which purported to sell "the best and fastest test for Coronavirus detection at the fantastic price of 19,000 Russian rubles (about US$300)."
"...cyber-criminals are exploiting interest in the global epidemic to spread malicious activity, with several spam campaigns relating to the outbreak of the virus," the firm wrote.
Check Point Software also noted how people in Japan had received emails that appeared to contain official information on the spread of coronavirus, sent from a Japanese disability welfare service provider. But when they opened the email attachment, they unwittingly downloaded a trojan virus.
Photo by Anthony Kwan/Getty Images
Still, this isn't to suggest that online platforms are having a mostly negative effect during the outbreak.
"Social media presents a mixed bag," Samuel Scarpino, a business professor of network science at Northeastern University College of Science, told Axios. "We know social media is promoting panic, and people are taking advantage of that by spreading misinformation, but it's also helping to spread good, reliable information that empowers people to make the right decisions."Ultimately, the people who stand to profit most from the coronavirus outbreak will likely be investors who follow Warren Buffett's famous bit of investing advice: "be greedy only when others are fearful." Just beware that grifters may also heed this advice.
- Why public health officials sound more worried about the ... ›
- Are you psychologically prepared for a coronavirus outbreak? - Big ... ›
- How likely are you to die from coronavirus? - Big Think ›
- 27 million Americans may have lost employer insurance amid pandemic - Big Think ›
- Can medical detection dogs sniff out COVID-19? - Big Think ›
Northwell Health is using insights from website traffic to forecast COVID-19 hospitalizations two weeks in the future.
- The machine-learning algorithm works by analyzing the online behavior of visitors to the Northwell Health website and comparing that data to future COVID-19 hospitalizations.
- The tool, which uses anonymized data, has so far predicted hospitalizations with an accuracy rate of 80 percent.
- Machine-learning tools are helping health-care professionals worldwide better constrain and treat COVID-19.
The value of forecasting<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTA0Njk2OC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMzM2NDQzOH0.rid9regiDaKczCCKBsu7wrHkNQ64Vz_XcOEZIzAhzgM/img.jpg?width=980" id="2bb93" class="rm-shortcode" data-rm-shortcode-id="31345afbdf2bd408fd3e9f31520c445a" data-rm-shortcode-name="rebelmouse-image" data-width="1546" data-height="1056" />
Northwell emergency departments use the dashboard to monitor in real time.
Credit: Northwell Health<p>One unique benefit of forecasting COVID-19 hospitalizations is that it allows health systems to better prepare, manage and allocate resources. For example, if the tool forecasted a surge in COVID-19 hospitalizations in two weeks, Northwell Health could begin:</p><ul><li>Making space for an influx of patients</li><li>Moving personal protective equipment to where it's most needed</li><li>Strategically allocating staff during the predicted surge</li><li>Increasing the number of tests offered to asymptomatic patients</li></ul><p>The health-care field is increasingly using machine learning. It's already helping doctors develop <a href="https://care.diabetesjournals.org/content/early/2020/06/09/dc19-1870" target="_blank">personalized care plans for diabetes patients</a>, improving cancer screening techniques, and enabling mental health professionals to better predict which patients are at <a href="https://healthitanalytics.com/news/ehr-data-fuels-accurate-predictive-analytics-for-suicide-risk" target="_blank" rel="noopener noreferrer">elevated risk of suicide</a>, to name a few applications.</p><p>Health systems around the world have already begun exploring how <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315944/" target="_blank" rel="noopener noreferrer">machine learning can help battle the pandemic</a>, including better COVID-19 screening, diagnosis, contact tracing, and drug and vaccine development.</p><p>Cruzen said these kinds of tools represent a shift in how health systems can tackle a wide variety of problems.</p><p>"Health care has always used the past to predict the future, but not in this mathematical way," Cruzen said. "I think [Northwell Health's new predictive tool] really is a great first example of how we should be attacking a lot of things as we go forward."</p>
Making machine-learning tools openly accessible<p>Northwell Health has made its predictive tool <a href="https://github.com/northwell-health/covid-web-data-predictor" target="_blank">available for free</a> to any health system that wishes to utilize it.</p><p>"COVID is everybody's problem, and I think developing tools that can be used to help others is sort of why people go into health care," Dr. Cruzen said. "It was really consistent with our mission."</p><p>Open collaboration is something the world's governments and health systems should be striving for during the pandemic, said Michael Dowling, Northwell Health's president and CEO.</p><p>"Whenever you develop anything and somebody else gets it, they improve it and they continue to make it better," Dowling said. "As a country, we lack data. I believe very, very strongly that we should have been and should be now working with other countries, including China, including the European Union, including England and others to figure out how to develop a health surveillance system so you can anticipate way in advance when these things are going to occur."</p><p>In all, Northwell Health has treated more than 112,000 COVID patients. During the pandemic, Dowling said he's seen an outpouring of goodwill, collaboration, and sacrifice from the community and the tens of thousands of staff who work across Northwell.</p><p>"COVID has changed our perspective on everything—and not just those of us in health care, because it has disrupted everybody's life," Dowling said. "It has demonstrated the value of community, how we help one another."</p>
A leading British space scientist thinks there is life under the ice sheets of Europa.
- A British scientist named Professor Monica Grady recently came out in support of extraterrestrial life on Europa.
- Europa, the sixth largest moon in the solar system, may have favorable conditions for life under its miles of ice.
- The moon is one of Jupiter's 79.
Neil deGrasse Tyson wants to go ice fishing on Europa<div class="rm-shortcode" data-media_id="GLGsRX7e" data-player_id="FvQKszTI" data-rm-shortcode-id="f4790eb8f0515e036b24c4195299df28"> <div id="botr_GLGsRX7e_FvQKszTI_div" class="jwplayer-media" data-jwplayer-video-src="https://content.jwplatform.com/players/GLGsRX7e-FvQKszTI.js"> <img src="https://cdn.jwplayer.com/thumbs/GLGsRX7e-1920.jpg" class="jwplayer-media-preview" /> </div> <script src="https://content.jwplatform.com/players/GLGsRX7e-FvQKszTI.js"></script> </div>
Water Vapor Above Europa’s Surface Deteced for First Time<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="9c4abc8473e1b89170cc8941beeb1f2d"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/WQ-E1lnSOzc?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span>
The scent of sickness: 5 questions answered about using dogs – and mice and ferrets – to detect disease
Could medical detection animals smell coronavirus?
Study confirms the existence of a special kind of groupthink in large groups.
- Large groups of people everywhere tend to come to the same conclusions.
- In small groups, there's a much wider diversity of ideas.
- The mechanics of a large group make some ideas practically inevitable.
The grouping game<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTQ1NDE2Ni9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYxMjI2MzA4OX0.RLrswIWbuEzHNqsw0F7EUrp9jPn7OulLPqCxcZT11ik/img.jpg?width=980" id="159b8" class="rm-shortcode" data-rm-shortcode-id="0feb15d2d7dde144c710c2f4f1e5350c" data-rm-shortcode-name="rebelmouse-image" data-width="2767" data-height="382" />
Some of the shapes used in the experiment
Credit: Guilbeault, et al./University of Pennsylvania<p>The researchers tested their theory with 1,480 people playing an online "Grouping Game" via Amazon's Mechanical Turk platform. The individuals were paired with another participant or made a member of a group of 6, 8, 24, or 50 people. Each pair and group were tasked with categorizing the symbols shown above, and they could see each other's answers.</p><p>The small groups came up with wildly divergent categories—the entire experiment produced nearly 5,000 category suggestions—while the larger groups came up with categorization systems that were virtually identical to each other.</p><p><a href="https://www.asc.upenn.edu/news-events/news/why-independent-cultures-think-alike-its-not-in-the-brain" target="_blank">Says Centol</a>a, "Even though we predicted it, I was nevertheless stunned to see it really happen. This result challenges many long-held ideas about culture and how it forms."</p><p>Nor was this unanimity a matter of having teamed-up like-minded individuals. "If I assign an individual to a small group," says lead author Douglas Guilbeault, "they are much more likely to arrive at a category system that is very idiosyncratic and specific to them. But if I assign that same individual to a large group, I can predict the category system that they will end up creating, regardless of whatever unique viewpoint that person happens to bring to the table."</p>
Why this happens<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTQ1NDE4NC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMjkzMDg0Nn0.u2hdEIgNw4drFZ2frzx0AJ_MAxIizuM98rdovQrIblk/img.jpg?width=980" id="d3444" class="rm-shortcode" data-rm-shortcode-id="5da57d66e388fad0f1c17afb09af90a7" data-rm-shortcode-name="rebelmouse-image" data-width="1440" data-height="822" />
The many categories suggested by small groups on the left, the few from large groups on the right
Credit: Guilbeault, et al./Nature Communications<p>The striking results of the experiment correspond to a <a href="https://www.nature.com/articles/s41562-019-0607-5" target="_blank">previous study</a> done by NDG that investigated tipping points for people's behavior in networks.</p><p>That study concluded that after an idea enters a discussion among a large network of people, it can gain irresistible traction by popping up again and again in enough individuals' conversations. In networks of 50 people or more, such ideas eventually reach critical mass and become a prevailing opinion.</p><p>The same phenomenon does not happen often enough within a smaller network, where fewer interactions offer an idea less of an opportunity to take hold.</p>