Feature Story

Why we don’t have more COVID-19 vaccines for animals

COVID-19 vaccines for humans number 30, while only three vaccines are available for animals, even though many species have been infected.

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Responding to COVID-19 outbreaks at more than 200 mink farms, the Danish government, in November 2020, culled its entire mink population. The Danish armed forces helped farmers slaughter each of their 17 million minks, which are normally farmed for their valuable fur.

The SARS-CoV-2 virus, said officials, spread from human handlers to the small, ferret-like animals, mutated, and then spread back to several hundred humans. Although the mass extermination faced much criticism, Denmark’s prime minister defended the decision last month, stating that the step was “necessary” and that the Danish government had “a responsibility for the health of the entire world.”

Over the past two and half years, COVID-19 infections have been reported in numerous animal species around the world. In addition to the Danish minks, there is other evidence that the virus can mutate as it’s transmitted back and forth between humans and animals, which increases the risk to public health. According to the World Health Organisation (WHO), COVID-19 vaccines for animals may protect the infected species and prevent the transmission of viral mutations. However, the development of such vaccines has been slow. Scientists attribute the deficiency to a lack of data.

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Puja Changoiwala
Puja Changoiwala is an award-winning journalist and author based in Mumbai. She writes about the intersections of gender, crime, technology, social justice and human rights in India. She tweets @cpuja.
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Scientists Want to Make Robots with Genomes that Help Grow their Minds

Giving robots self-awareness as they move through space - and maybe even providing them with gene-like methods for storing rules of behavior - could be important steps toward creating more intelligent machines.

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One day in recent past, scientists at Columbia University’s Creative Machines Lab set up a robotic arm inside a circle of five streaming video cameras and let the robot watch itself move, turn and twist. For about three hours the robot did exactly that—it looked at itself this way and that, like toddlers exploring themselves in a room full of mirrors. By the time the robot stopped, its internal neural network finished learning the relationship between the robot’s motor actions and the volume it occupied in its environment. In other words, the robot built a spatial self-awareness, just like humans do. “We trained its deep neural network to understand how it moved in space,” says Boyuan Chen, one of the scientists who worked on it.

For decades robots have been doing helpful tasks that are too hard, too dangerous, or physically impossible for humans to carry out themselves. Robots are ultimately superior to humans in complex calculations, following rules to a tee and repeating the same steps perfectly. But even the biggest successes for human-robot collaborations—those in manufacturing and automotive industries—still require separating the two for safety reasons. Hardwired for a limited set of tasks, industrial robots don't have the intelligence to know where their robo-parts are in space, how fast they’re moving and when they can endanger a human.

Over the past decade or so, humans have begun to expect more from robots. Engineers have been building smarter versions that can avoid obstacles, follow voice commands, respond to human speech and make simple decisions. Some of them proved invaluable in many natural and man-made disasters like earthquakes, forest fires, nuclear accidents and chemical spills. These disaster recovery robots helped clean up dangerous chemicals, looked for survivors in crumbled buildings, and ventured into radioactive areas to assess damage.

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Lina Zeldovich
Lina Zeldovich has written about science, medicine and technology for Scientific American, Reader’s Digest, Mosaic Science and other publications. She’s an alumna of Columbia University School of Journalism and the author of the upcoming book, The Other Dark Matter: The Science and Business of Turning Waste into Wealth, from Chicago University Press. You can find her on http://linazeldovich.com/ and @linazeldovich.
After Dobbs v. Jackson, the Battle Shifts to Digital Privacy v. Surveillance

The limits of digital privacy are becoming clearer in the post-Dobbs era, as a wide range of data sources can reveal online and offline activities, including whether a woman seeks an abortion.

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Since the recent reversal of Roe v. Wade — the landmark decision establishing a constitutional right to abortion — the vulnerabilities of reproductive health data and various other information stored on digital devices or shared through the Web have risen to the forefront.

Menstrual period tracking apps are an example of how technologies that collect information from users could be weaponized against abortions seekers. The apps, which help tens of millions of users in the U.S. predict when they’re ovulating, may provide evidence that leads to criminal prosecution in states with abortion bans, says Anton T. Dahbura, executive director of the Johns Hopkins University Information Security Institute. In states where abortion is outlawed, “it’s probably best to not use a period tracker,” he says.

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Susan Kreimer
Susan Kreimer is a New York-based freelance journalist who has followed the landscape of health care since the late 1990s, initially as a staff reporter for major daily newspapers. She writes about breakthrough studies, personal health, and the business of clinical practice. Raised in the Chicago area, she holds a B.A. in Journalism/Mass Communication and French from the University of Iowa and an M.S. from the Columbia University Graduate School of Journalism.