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The Disease Detective<\/em>, The New York Times Magazine, June 6, 2021<\/span><\/p>\n <\/p>\n While the rich nations seem to be moving forward on the Covid pandemic (seem to–ask the UK how that’s going), the billions of poor are being ravaged. Official death tolls, horrible as they are, clearly fall far short of reality, everywhere. Vaccines help those who get them, most of the world is desperate for them, and the nations seeming to move forward will turn into a variant illusion unless the pandemic is contained globally. Same old story.<\/p>\n Meanwhile, the next pandemics are waiting–or already here.<\/p>\n Who knew, that H.I.V. emerged nearly a dozen times over a century, starting in the 1920s, before it exploded worldwide, killed 35 million people so far, with 38 million currently infected.<\/p>\n And who knew that if we had a tool then, now in use, that it may well have been able to have been largely prevented?<\/p>\n Here’s an excerpt from The Disease Detective<\/em> in last Sunday’s New York Times Magazine:<\/p>\n Traditionally, the way that scientists have identified organisms in a sample is to culture them: Isolate a particular bacterium (or virus or parasite or fungus); grow it in a petri dish; and then examine the result under a microscope, or use genomic sequencing, to understand just what it is. But because less than 2 percent of bacteria \u2014 and even fewer viruses \u2014 can be grown in a lab, the process often reveals only a tiny fraction of what\u2019s actually there. It\u2019s a bit like planting 100 different kinds of seeds that you found in an old jar. One or two of those will germinate and produce a plant, but there\u2019s no way to know what the rest might have grown into.<\/em><\/p>\n And because different types of bacteria require specific conditions in order to grow, you also need some idea of what you\u2019re looking for in order to find it. The same is true of genomic sequencing, which relies on \u201cprimers\u201d designed to match different combinations of nucleotides (the building blocks of DNA and RNA). Even looking at a slide under a microscope requires staining, which makes organisms easier to see \u2014 but the stains used to identify bacteria and parasites, for instance, aren\u2019t the same.<\/em><\/p>\n Now, there’s a\u00a0practice known as metagenomic sequencing, that could change everything in the disease detection and prevention business.<\/p>\n As we say, from here on, the article speaks for itself. If you like surviving, it will interest you.<\/p>\n<\/div>\n “The Disease Detective”<\/a><\/p>\n By <\/span>Jennifer Kahn, The New York Times Magazine, June 6, 2021<\/span><\/p>\n Joe DeRisi invented a way to find pathogens that scientists didn\u2019t even know to look for. Can it help prevent the next pandemic?<\/em><\/p>\n Joe DeRisi remembers very clearly when his obsession with mystery diseases began. As a teenager in the 1980s, growing up outside Sacramento, he was riveted by news reports about the AIDS epidemic, which in its early years was spreading around the world and killing thousands of people while scientists struggled to establish the cause. \u201cI mean, what is it?\u201d DeRisi says. \u201cIs it a virus? Nobody knew! That whole concept, that we could have an epidemic or pandemic but couldn\u2019t figure out what was behind it \u2014 that stuck with me my whole life.\u201d<\/p>\n Today DeRisi is a professor of biochemistry who studies infectious diseases at the University of California, San Francisco, and co-president of the Chan Zuckerberg Biohub, a research institute in the city\u2019s Mission Bay neighborhood. Lean and white-haired at 51, he tends to talk in rapid bursts, sometimes inflected with a California-stoner vibe. When I met him at the Biohub in May, he, like many geneticists, had just come off a harried year of working on Covid-19, during which he transformed his lab into a facility that could process more than 2,600 rapid tests a day. \u201cThings have definitely calmed down,\u201d DeRisi said, as he led me inside the Biohub. \u201cIt was pretty intense for a while there.\u201d<\/p>\n As we made a lightning tour of the lab, DeRisi waved his hand at a series of expensive genetic sequencers, including one the size of a refrigerator. \u201cBoring gray boxes,\u201d he announced, before moving on. On a table near the back was a much smaller unit, plain white and roughly the size of a milk crate, with a simple touch-screen. Not long after becoming president of the Biohub in 2016, DeRisi started a project designed to spot unfamiliar diseases well before they would normally be detected. The white box, when connected to an elaborate analysis system DeRisi had designed, allowed researchers from around the world to piece together all the different DNA or RNA recovered from just about any sample \u2014 throat swabs, blood draws or other material \u2014 and scan it for unidentified pathogens.<\/p>\n The medical word for such diseases is \u201cidiopathic\u201d: conditions whose symptoms can be described but that have no known cause. Before germs were understood, most illnesses were idiopathic by definition, including the Black Death, which we now know was caused by a bacterium (Yersinia pestis) but which doctors at the time hypothesized might be caused by staring at someone who was ill, the alignment of the planets, bad smells or wearing pointed shoes. What\u2019s startling is how many mystery infections still exist today. More than a third of acute respiratory illnesses are idiopathic; the same is true for up to 40 percent of gastrointestinal disorders and more than half the cases of encephalitis (swelling of the brain). Up to 20 percent of cancers and a substantial portion of autoimmune diseases, including multiple sclerosis and rheumatoid arthritis, are thought to have viral triggers, but a vast majority of those have yet to be identified.<\/p>\n Globally, the numbers can be even worse, and the stakes often higher. \u201cSay a person comes into the hospital in Sierra Leone with a fever and flulike symptoms,\u201d DeRisi says. \u201cAfter a few days, or a week, they die. What caused that illness? Most of the time, we never find out. Because if the cause isn\u2019t something that we can culture and test for\u201d \u2014 like hepatitis, or strep throat \u2014 \u201cit basically just stays a mystery.\u201d<\/p>\n While the cause of Covid-19 was quickly identified as a coronavirus, DeRisi notes, that won\u2019t necessarily be the case with whatever germ creates the next pandemic. And past strategies for detecting potentially dangerous viruses haven\u2019t always been very systematic. \u201cDifferent prevention projects in the past have just sort of picked up random roadkill on the side of the road and looked for viruses in it,\u201d DeRisi told me. \u201cOr they\u2019ll look for all the viruses in bats.\u201d While there\u2019s a place for that sort of sampling, DeRisi said, it\u2019s hard to know which of the many organisms discovered actually poses a risk. \u201cLike, we have a project that\u2019s examining the slurry in swine farms,\u201d he went on. \u201cAnd we\u2019ve identified at least 200 novel viruses so far. Which is great! But we have no idea which of those, if any, have the ability to jump into humans \u2014 or how bad it would be if they did.\u201d<\/p>\n It would be better, DeRisi says, to watch for rare cases of mystery illnesses in people, which often exist well before a pathogen gains traction and is able to spread. Based on a retrospective analysis of blood samples, scientists now know that H.I.V. emerged<\/a> nearly a dozen times over a century, starting in the 1920s, before it went global. Zika was a relatively harmless illness before a single mutation, in 2013, gave the virus the ability to enter and damage brain cells. Cristina Tato, an immunologist who runs the Biohub\u2019s Rapid Response Team, points out that months before Zika exploded in Brazil,<\/a> causing developmental issues and microcephaly in infants, researchers in the South Pacific noticed an increase in neurological symptoms, a missed clue that Zika was changing.<\/p>\n \u201cWith pathogens, we\u2019re much better at watching for things that we already know are out there,\u201d DeRisi said. \u201cEbola, we know. Zika, we know. The beauty of this approach\u201d \u2014 running blood samples from people hospitalized all over the world through his system, known as IDseq \u2014 \u201cis that it works even for things that we\u2019ve never seen before, or things that we might think we\u2019ve seen but which are actually something new.\u201d Traditionally, the way<\/strong> that scientists have identified organisms in a sample is to culture them: Isolate a particular bacterium (or virus or parasite or fungus); grow it in a petri dish; and then examine the result under a microscope, or use genomic sequencing, to understand just what it is. But because less than 2 percent of bacteria \u2014 and even fewer viruses \u2014 can be grown in a lab, the process often reveals only a tiny fraction of what\u2019s actually there. It\u2019s a bit like planting 100 different kinds of seeds that you found in an old jar. One or two of those will germinate and produce a plant, but there\u2019s no way to know what the rest might have grown into.<\/p>\n And because different types of bacteria require specific conditions in order to grow, you also need some idea of what you\u2019re looking for in order to find it. The same is true of genomic sequencing, which relies on \u201cprimers\u201d designed to match different combinations of nucleotides (the building blocks of DNA and RNA). Even looking at a slide under a microscope requires staining, which makes organisms easier to see \u2014 but the stains used to identify bacteria and parasites, for instance, aren\u2019t the same.<\/p>\n The practice that DeRisi helped pioneer to skirt this problem is known as metagenomic sequencing. Unlike ordinary genomic sequencing, which tries to spell out the purified DNA of a single, known organism, metagenomic sequencing can be applied to a messy sample of just about anything \u2014 blood, mud, seawater, snot \u2014 which will often contain dozens or hundreds of different organisms, all unknown, and each with its own DNA. In order to read all the fragmented genetic material, metagenomic sequencing uses sophisticated software to stitch the pieces together by matching overlapping segments.<\/p>\n The assembled genomes are then compared against a vast database of all known genomic sequences \u2014 maintained by the government-run National Center for Biotechnology Information \u2014 making it possible for researchers to identify everything in the mix. In this scenario, an undiscovered or completely new virus won\u2019t trigger a match but will instead be flagged. (Even in those cases, the mystery pathogen will usually belong to a known virus family: coronaviruses, for instance, or filoviruses that cause hemorrhagic fevers like Ebola and Marburg.)<\/p>\n Metagenomic sequencing is especially good at what scientists call \u201cenvironmental sampling\u201d: identifying, say, every type of bacteria present in the gut microbiome, or in a teaspoon of seawater. Such studies have revealed just how vast the microbial world is, and how little we know about it. One study found more than 1,000 different kinds of viruses in a tiny amount of human stool; another found a million in a couple of pounds of marine sediment. And most were organisms that nobody had seen before.<\/p>\n In 2002, as an assistant professor, DeRisi and his collaborator David Wang created the first medical version of this tool, a DNA microarray called the ViroChip that was designed to identify any known virus from a patient\u2019s blood or tissue, and also detect any new or unknown virus. In the years after developing the ViroChip, DeRisi used it mostly to hunt for unknown pathogens connected to respiratory diseases, including asthma. One of his early successes was helping to identify a mystery disease from Hong Kong that would turn out to be SARS. He also solved medical mysteries; in one case, he figured out that a construction worker\u2019s encephalitis was caused not by tuberculosis, as doctors thought for more than a year, but by a tapeworm from infected pork that had migrated to the patient\u2019s brain.<\/p>\n He dabbled in animal epidemics as well. Along with diagnosing a fatal neurological disease in snakes, he investigated an infection that was killing cockatiels and parrots, and solved a bizarre rash of deaths among sharks and bat rays in San Francisco Bay. At one point, he even investigated a case of encephalitis in a polar bear, although the cause turned out to be an autoimmune disorder. (DeRisi now studies the same illness in humans.)<\/p>\n After the Biohub opened in 2016, one of DeRisi\u2019s goals was to turn metagenomics from a rarefied technology used by a handful of elite universities into something that researchers around the world could benefit from. Unlike regular genomic sequencing, which is now cheap, metagenomics requires enormous amounts of computing power, putting it out of reach of all but the most well-funded research labs. The tool DeRisi created, IDseq, made it possible for researchers anywhere in the world to process samples through the use of a small, off-the-shelf sequencer, much like the one DeRisi had shown me in his lab, and then upload the results to the cloud for analysis.<\/p>\n DeRisi isn\u2019t alone in this cloud-based approach to metagenomics \u2014 a growing number of start-ups are doing the same. But he\u2019s the first to make the process so accessible, even in countries where lab supplies and training are scarce. DeRisi and his team tested the chemicals used to prepare DNA for sequencing and determined that using as little as half the recommended amount often worked fine. They also 3-D print some of the labs\u2019 tools and replacement parts, and offer ongoing training and tech support. The metagenomic analysis itself \u2014 normally the most expensive part of the process \u2014 is provided free.<\/p>\n But DeRisi\u2019s main innovation has been in streamlining and simplifying the extraordinarily complex computational side of metagenomics. \u201cMost metagenomics programs are really hard to use,\u201d a former collaborator noted. \u201cThey take a lot of practice and training.\u201d IDseq is also fast, capable of doing analyses in hours that would take other systems weeks.<\/p>\n \u201cWhat IDseq really did was to marry wet-lab work \u2014 accumulating samples, processing them, running them through a sequencer \u2014 with the bioinformatic analysis,\u201d says Jennifer Bohl, a researcher who worked at the Laboratory of Malaria and Vector Research in Phnom Penh. \u201cWithout that, what happens in a lot of places is that the researcher will be like, \u2018OK, I collected the samples!\u2019 But because they can\u2019t analyze them, the samples end up in the freezer. The information just gets stuck there.\u201d<\/p>\n It wasn\u2019t long after <\/strong>DeRisi completed the prototype for IDseq that he performed his first test of it as a global health tool \u2014 a trial run that delivered some fascinating results. It all began in fall 2017, when he ran into Farhad Imam, a pediatrician and senior program officer at the Gates Foundation, at a global health conference in Washington. As they discussed the challenges of deploying the system in the developing world, Imam hit on the idea of enlisting Senjuti Saha, a microbiologist at the Child Health Research Foundation in Dhaka, Bangladesh, to see if IDseq might help shed some light on a mystery there.<\/p>\n Earlier that year, the C.H.R.F. noticed a sharp uptick in cases of meningitis in children. Some of these were fatal; many left patients disabled. \u201cIn Bangladesh, when a child is disabled, the entire family completely falls apart,\u201d Saha told me. \u201cThe mother doesn\u2019t go to work anymore. The siblings fall out of school. They get into this vicious cycle of debt.\u201d<\/p>\n Meningitis itself isn\u2019t a disease, just a description meaning that the tissues around the brain and spinal cord have become inflamed. In the United States, bacterial infections can cause meningitis, as can enteroviruses, mumps and herpes simplex. But a high proportion of cases have, as doctors say, no known etiology: No one knows why the patient\u2019s brain and spinal tissues are swelling.<\/p>\n This was the case with the Dhaka outbreak. C.H.R.F. is one of the premier microbiology labs in Southeast Asia and is in charge of tracking meningitis in the country for the World Health Organization. \u201cEvery meningitis case that comes in, we culture,\u201d Saha told me. \u201cWe do antigen tests for pneumococcus, Neisseria meningitidis, Hemophilus influenzae and G.B.S.,\u201d or Group B streptococcus \u2014 the four infections most likely to cause meningitis. \u201cThen we do a much more sensitive and specific test for Streptococcus pneumoniae bacteria, since that causes the highest proportion of cases. And then we also do real-time P.C.R. looking for fragments of DNA from any of these pathogens.\u201d<\/p>\n When the outbreak began, it was assumed that the cause would again be bacterial, but none of the tests could pinpoint a pathogen. Over the next year, Saha worked to solve the mystery, at times in collaboration with other labs. One partnership, with an organization in China, fell apart when the group wasn\u2019t willing to share its techniques. Another set of researchers, in Canada, ran their own tests on the meningitis samples, but couldn\u2019t figure out the cause either. Not long after, Saha attended a conference at the British Museum, where she gave a presentation titled \u201cThe Dark Side of Meningitis.\u201d \u201cIt was a negative talk,\u201d Saha recalls. \u201cLike: Why does everybody talk only about the successful cases? We need to talk about the thousands of cases every year where we have no idea what\u2019s causing the disease.\u201d<\/p>\n Before meeting DeRisi, Saha was skeptical about yet another collaboration. But the two instantly hit it off. Though DeRisi could be impatient, Saha liked that he was direct, and appreciated that his \u201cethics are very strong. In his head, he\u2019s like: This is right; this is wrong; this is what I\u2019m going to do.<\/em>\u201d Still, she proceeded carefully. \u201cBecause IDseq was new, and because I am very meticulous, I included a lot of controls,\u201d she told me. Of the 97 samples of cerebrospinal fluid, only 25 were from actual mystery-meningitis cases. The rest were either from cases for which Saha\u2019s lab had already identified the cause, or weren\u2019t meningitis at all. Several were simply water. \u201cThe idea was that all of these would be tested, and the process would be blinded,\u201d Saha says. \u201cBecause I had to see whether the platform worked or not.\u201d<\/p>\n When Saha and her team ran the mystery meningitis samples through IDseq, though, the result was surprising. Rather than revealing a bacterial cause, as expected, a third of the samples showed signs of the chikungunya virus \u2014 specifically, a neuroinvasive strain that was thought to be extremely rare. \u201cAt first we thought, It cannot be true!<\/em>\u201d Saha recalls. \u201cBut the moment Joe and I realized it was chikungunya, I went back and looked at the other 200 samples that we had collected around the same time. And we found the virus in some of those samples as well.\u201d<\/p>\n Until recently, chikungunya was a comparatively rare disease, present mostly in parts of Central and East Africa. \u201cThen it just exploded through the Caribbean and Africa and across Southeast Asia into India and Bangladesh,\u201d DeRisi told me. In 2011, there were zero cases of chikungunya reported in Latin America. By 2014, there were a million.<\/p>\n Ordinary chikungunya can cause lasting neurological damage and lifelong joint pain. DeRisi called the disease \u201chugely devastating\u201d and noted that chikungunya, in the Kimakonde language, spoken in Tanzania, means \u201cto become contorted.\u201d But a neuroinvasive version that caused brain damage and primarily affected children and infants was especially alarming.<\/p>\n Chikungunya is a mosquito-borne virus, but when DeRisi and Saha looked at the results from IDseq, they also saw something else: a primate tetraparvovirus. Primate tetraparvoviruses are almost unknown in humans, and have been found only in certain regions. Even now, DeRisi is careful to note, it\u2019s not clear what effect the virus has on people. \u201cMaybe it\u2019s dangerous, maybe it isn\u2019t,\u201d DeRisi says. \u201cBut I\u2019ll tell you what: It\u2019s now on my radar. So this thing that would have been totally invisible, that nobody even knew to look for \u2014 now we\u2019re watching for it.\u201d<\/p>\n That sort of discovery matters, Farhad Imam observes, partly because it can head off a new epidemic, but also because it reveals a landscape of potentially dangerous viruses that we would otherwise never find out about. \u201cWhat we\u2019ve been missing is that there\u2019s an entire universe of pathogens out there that are causing disease in humans,\u201d Imam notes, \u201cones that we often don\u2019t even know exist.\u201d<\/p>\n After finishing the<\/strong> meningitis pilot study, DeRisi and Imam started to roll out IDseq more widely. \u201cThe plan was, Let\u2019s let researchers around the world propose studies, and we\u2019ll choose 10 of them to start,\u201d DeRisi recalls. \u201cWe thought we\u2019d get, like, a couple dozen proposals, and instead we got 350.\u201d<\/p>\n A group in Madagascar wanted to compare the organisms found in bats against those found in patient blood samples, as a way to see what viruses might be spilling over. A research institute in Brazil, which often sees patients with mysterious fevers, wanted to know the cause. \u201cThe selling point for researchers is: \u2018Look, this technology lets you investigate what\u2019s happening in your clinic, whether it\u2019s kids with meningitis or something else,\u2019\u201d DeRisi said. \u201cWe\u2019re not telling you what to do with it. But it\u2019s also true that if we have enough people using this, spread out all around the world, then it does become a global network for detecting emerging pandemics. Because maybe you\u2019re focused on childhood meningitis in Dhaka, but suddenly you have all these adults showing up with a weird respiratory illness. You\u2019re going to turn your attention to that.\u201d<\/p>\n At the lab, DeRisi pulled up the IDseq results for some of Saha\u2019s meningitis samples, drawn from patients\u2019 cerebrospinal fluid. \u201cThis is a heat map,\u201d DeRisi said, pointing at what looked like an erratically filled-in grid, with some white squares and others in gradations of yellow or red. At the top, a stretch of dark red-purple blocks showed the presence of chikungunya, but there were also dozens of lighter squares, reflecting everything from secondary infections to garden-variety bacteria that live on the skin. Each row, DeRisi explained, represented a different microbe that the system had detected with the color representing the amount of virus that had been found. Some of these were familiar: Alphapapillomavirus causes warts; Saccharomyces cerevisiae is a fungus found in bread and beer.<\/p>\n Making it possible for countries to do their own metagenomic testing, regularly and in real time, could increase pathogen detection in places where new pandemics are most likely to emerge. But the heat map also showed how hard it can be to determine which organism, out of many, is the one making a person ill. One hazard of metagenomics is that it amplifies all the genetic material in a sample indiscriminately, making it challenging to know which of the various bacteria or viruses the process detects are actually significant. Nasal swabs, for example, routinely pick up signs of influenza and respiratory viruses \u2014 as well as dozens, or even hundreds, of types of bacteria. That\u2019s especially true in the parts of the world where DeRisi would like to offer IDseq. As David Relman, a microbiologist at Stanford University, notes, \u201cWhen you draw blood from someone who has a fever in Ghana, you really don\u2019t know very much about what would normally be in their blood without fever \u2014 let alone about other kinds of contaminants in the environment. So how do you interpret the relevance of all the things you\u2019re seeing?\u201d<\/p>\n Such criticisms have led some to say that metagenomics simply isn\u2019t suited to the infrastructure of developing countries. Along with the problem of contamination, many labs struggle to get the chemical reagents needed for sequencing, either because of the cost or because of shipping and customs holdups. Even uploading data can be fraught. \u201cIn Cambodia, we have problems with the internet, and we have big problems with power outages,\u201d Bohl says. \u201cSo the constant fear is that I\u2019ll wake up after a 48-hour run and there\u2019ll be no information, because the power went out in the middle of the night.\u201d<\/p>\n When I mentioned this to Saha, she said that such conditions were not an argument for limiting access. Imam agrees. \u201cBefore now, a researcher would literally have to send their samples to a lab in the global north \u2014 to what I call \u2018one of the two Cambridges,\u2019 Boston or England \u2014 just to answer a question about a disease in their own country,\u201d he says. \u201cSo this really represents a change in terms of who has access to metagenomic technology, and what can be done with it.\u201d<\/p>\n Soon after the<\/strong> first Covid lockdowns began in the United States in March 2020, DeRisi and his group set up Slack channels to talk with IDseq teams around the world, nearly all of which had started using the technology to track coronavirus variants as they emerged. In Cambodia, Bohl\u2019s team sequenced the virus\u2019s genome from a patient who had recently returned from Wuhan \u2014 one of the earliest sequences to be posted on Gisaid, an open-access database for disease variants. In Bangladesh, Saha and her group did the same, and discovered a strain with two unfamiliar mutations. \u201cThat\u2019s one of the beauties of the system,\u201d DeRisi observes. \u201cIt allows you to pivot on a dime.\u201d By that point, the SARS-CoV-2 virus, which causes Covid-19, had been identified using electron microscopy; there was no need to use metagenomic sequencing to find a mystery agent. But as one infectious-disease specialist, David Patrick at the University of British Columbia, told me: \u201cWhat if that hadn\u2019t worked? It would have been nice to have an extra tool in the kit.\u201d<\/p>\n As the coronavirus spread around the world, the Africa Centers for Disease Control and Prevention, which oversees a continentwide Pathogen Genomics Initiative (P.G.I.), also reached out, hoping to expand the IDseq program to additional labs around the continent. Tato, the researcher who oversaw that process in Senegal, Ethiopia, Egypt and Nigeria, says that while tracking Covid was part of what motivated the Africa C.D.C.\u2019s interest, the expansion was also aimed at ongoing epidemics like yellow fever, Ebola and Lassa fever. (Nigeria\u2019s yellow-fever infections, in particular, were growing more severe, leading researchers to wonder whether the virus had evolved in ways that made it more virulent.) But the P.G.I. also urged countries to begin using metagenomics more broadly \u2014 for instance, to investigate the vast repository of samples collected over the years by Dakar\u2019s Institut Pasteur, from patients as well as wildlife and birds.<\/p>\n Even just as a public-health tool, IDseq has the potential to be illuminating. In Nepal, Tato told me, projects are underway to determine the causes of both idiopathic pediatric encephalitis and a mysterious infection that causes blindness in infants and children, which is thought to be transmitted by moths. (The infectious agent carried by the moths \u2014 bacteria, fungus or some other toxin \u2014 is still unknown.) \u201cThey\u2019ve got this new technology, and they\u2019re just running with it,\u201d Tato adds. \u201cThey keep finding new things they want to investigate.\u201d<\/p>\n Using IDseq to tackle regional health problems is part of the point, DeRisi says. \u201cLook, most of the stuff that people find with IDseq will never turn into a pandemic,\u201d he went on. \u201cBut that doesn\u2019t mean it\u2019s useless. We\u2019ll still be learning what pathogens are out there, how they\u2019re changing, when they\u2019re becoming more dangerous. All of which makes it more likely that we\u2019ll be able to spot an emerging pandemic before it takes off.\u201d<\/p>\n Discovering a contagious disease early makes it easier to contain, but widespread sampling also means that we\u2019re less likely to be caught off-guard. \u201cWith Ebola, there\u2019s always an issue: Where\u2019s the virus hiding before it breaks out?\u201d DeRisi explains. \u201cBut also, once we start sampling people who are hospitalized more widely \u2014 meaning not just people in Northern California or Boston, but in Uganda, and Sierra Leone, and Indonesia \u2014 the chance of disastrous surprises will go down. We\u2019ll start seeing what\u2019s hidden.\u201d<\/p>\n\n\n\n\n\n![\"Biological](\"https:\/\/static01.nyt.com\/images\/2021\/06\/06\/magazine\/06mag-derisi-02\/06mag-derisi-02-mobileMasterAt3x.jpg?quality=75&auto=webp&disable=upscale&width=600\")
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