Scatter, Adapt, and Remember: How Humans Will Survive a Mass Extinction

by Newitz, Annalee

  We already have many of the medicines we need to kill pandemic diseases. But to stop the pandemic itself, we need math. We have to understand how a pandemic is likely to unfold across the globe, in many societies, before we can set up the best system for stopping it.

  The medical surveillance state

  Over 10 years ago, the U.S. government asked the CIA to work on pandemic prevention. Using the country’s most notorious spy agency to deal with a health-care issue sounds like a bizarre fit. But it is the perfect organization, because pandemics are prevented in part by using techniques borrowed from spying. Does that mean our survival is dependent on everybody enduring forced health checks every week during flu season? No. And it doesn’t mean the government will be snooping through your medical history either. Even if the CIA wanted to dig through everybody’s medical records, it would be impossible, because many people don’t have health insurance or receive regular checkups. The CIA helps medical organizations craft strategies for health surveillance, or the practice of gathering information about who is coming down with infectious diseases and where they are.

  The World Health Organization (WHO) and other health-monitoring groups rely on a combination of sources for their health-surveillance data, including news stories about flu outbreaks and virus samples from all over the world sent to the WHO’s Global Influenza Surveillance and Response System. WHO scientists working with Google have also created Google Flu Trends, a system that monitors flu outbreaks by tracking the search terms that people are using in various regions. Google researchers discovered that when there was a significant uptick in people searching for words related to flu symptoms, like “sniffles” or “fever,” it was almost always followed by the Centers for Disease Control and Prevention (CDC) identifying a flu outbreak. Now the CDC and other agencies use Google’s data to figure out where the flu is breaking out, days before people start going to the doctor to report the symptoms they researched online. Like all forms of health surveillance, Google’s flu data is made as anonymous as possible. All we really need to know is how many people have flu symptoms in a specific region—we don’t need to know their names or their street addresses.

  Though the CDC and the WHO are the organizations we think of first when it comes to containing a pandemic, the greatest asset in any surveillance network is always your local health department, where the signs of an outbreak are going to be registered first. David Blythe manages health surveillance for the Maryland public-health department, which coordinates with dozens of regional health departments in the state to track what are called flu-like symptoms. Blythe said that one of the main ways the CDC tracks potential outbreaks is with a volunteer network called ILINet (for Influenza-like Illness Surveillance Network), a volunteer effort by local doctors, nurses, and other health-care workers who report any infectious, flu-like symptoms they see cropping up in patients. It’s key that they report symptoms rather than trying to diagnose what they’re seeing, since one of the main things ILINet is designed to catch is a new, deadly flu strain. If one arises, its collection of symptoms may not match any known illness. Every week, analysts with ILINet pore over the data, looking for suspicious patterns. What’s crucial here is that this health surveillance is happening on a city-by-city basis. Pandemics always start in one place, as John Snow found with the cholera-infected well in London. In other words, when the next big pandemic starts brewing, city health-care workers are going to notice it long before national and international agencies do.

  To supplement the work of ILINet, Maryland also has a group of volunteer labs that send samples of flu strains they’ve collected to the state health department for testing on a regular basis. “This is a lab that’s just designed for surveillance,” Blythe said. “We can do the testing that tells us whether it’s AH3 or N1, and we can determine if it’s a pandemic strain.” And if they discover a new pandemic strain, they ship it to the CDC in Atlanta. Maryland is also working on a way for low-income and homeless people to report when they have the flu as well, since they tend to fall outside the health department’s surveillance network. “We know that many people with flu never seek out a health-care provider at all,” Blythe lamented. The Maryland Department of Health and Hygiene tries to remedy this by asking people to report in when they or somebody they know has the flu, even if they don’t go to the doctor. The agency also tracks illnesses in health-care workers, since they are often on the front lines when pandemic strikes. “If a new strain of SARS”—severe acute respiratory syndrome—“starts in Maryland and nobody recognizes it as SARS, the first place you’d see people getting sick would be hospitals, so we have surveillance to try to pick up that phenomenon,” Blythe explained.

  Patterns of infection

  Though a deadly pandemic could arise from the flu, it might also be a product of that ancient scourge the plague. A mutation in Y. pestis, the plague-causing bacteria, could leave us vulnerable to one of the deadliest diseases humanity has ever confronted. We might also find ourselves battling SARS, or (less likely) a virus like Ebola, which causes the extremely deadly and infectious viral hemorrhagic fever.

  Regardless of the microbe that threatens us, a pandemic proceeds through eight recognizable stages, from incubation in animals at stage 1 to full pandemic in multiple countries at stage 6 (the peak of the pandemic). The next two stages, post-peak and post-pandemic, occur when the disease ebbs away until no one is infected anymore.

  Nils Stenseth, a biologist with the University of Oslo’s Centre for Ecological and Evolutionary Synthesis, is an expert on plague. He and his colleagues lay out the typical scenario that most people expect for a pandemic, based on what they know of historic Black Death outbreaks:

  In this classic urban-plague scenario, infected rats (transported, for example, by ships) arrive in a new city and transmit the infection to local house rats and their fleas, which then serve as sources of human infection. Occasionally, humans develop a pneumonic form of plague that is then directly transmitted from human to human through respiratory droplets.

  Like the flu scenario in Contagion, this pandemic starts by infecting animals and quickly spreads to humans living in cities. Though Stenseth cautions that modern pandemics don’t always bloom first in cities, most pandemic modelers take cities as the fundamental points of contagion—the dots on a map that spawn red vectors of infection.

  John Snow’s famous map of London, in which he tracked a cholera epidemic to its source in a well. You can see where he drew lines for numbers of dead in each location. He zeroed in on the well by tracking where the greatest numbers of deaths had occurred. (illustration credit ill.13)

  But how do we predict where those red vectors will go once they’ve left the city behind? There’s one major difference between the Black Death hitting London in the 1340s and SARS hitting Hong Kong in 2003: air travel.

  Though the SARS outbreak began in mainland China, investigators with the WHO and the CDC tracked its global spread to one isolated incident at Hong Kong’s Metropole Hotel. A medical professor visiting from southern China, where SARS had been claiming lives for a few months, checked into a small room on the ninth floor. Within days, 16 guests and visitors to that floor had also come down with the illness—many of them becoming sick after they’d flown to other cities all over the world, from North America to Vietnam. Investigators later came to call this incident a superspreading event, and traced it back to a hot zone on the carpet in front of that infected medical professor’s hotel-room door.

  Even three months after the professor had checked out of the hotel, technicians were able to find SARS viruses in the carpet. In its report, the WHO speculated that the sick professor might have vomited outside the door to his room, leaving behind a massive number of live viruses that survived a cleanup from hotel staff. Somehow, those viruses wound up in the lungs of 16 other people who passed near the hotel hot zone, and carried it all over the world—starting what nearly became a pandemic.

  Incidents like the one in the Metropole
Hotel have led pandemic modelers to build air-travel routes into nearly all their outbreak scenarios. Tini Garske is a mathematician and researcher with the Imperial College London’s Centre for Outbreak Analysis and Modelling, and she’s spent most of her career modeling disease outbreaks. Her most recent work focuses on generating outbreak scenarios based on Chinese travel patterns. She and her colleagues surveyed a group of 10,000 Chinese people from two provinces, looking at typical travel patterns in both rural and urban regions. What they found was that pandemics emerging in rural areas are likely to spread “sufficiently slowly for containment to be feasible,” because most people surveyed rarely traveled outside their local areas. Economically developed urban areas make containment more difficult, owing to the numbers of people traveling great distances on a regular basis.

  It would seem that the answer is simply to prevent people from traveling during a pandemic. But by the time we know we’re in the midst of a pandemic, it’s too late. Many other models show that limiting air travel makes almost no difference when it comes to limiting the spread of disease—at most, this tactic could delay the spread by a week or two. There are, however, a few superior methods based on models that take Garske’s travel research into account, and that incorporate what we learned during the SARS near-pandemic and the H1N1 (swine flu) pandemic of 2009.

  Social distancing

  Usually the first strategy that comes to mind for stopping pandemics is quarantine. In a typical quarantine, the government separates people who have been exposed to the disease from the general population. Ideally, people who have the pandemic disease are isolated both from the general population and from the quarantined.

  During the SARS outbreak in Toronto, the Canadian government quarantined hundreds of people, and a number of large public events in the city were canceled, in an effort to contain the disease. After the dust settled, however, many medical experts, including representatives of the CDC, argued that the local government had overreacted, quarantining roughly 100 people for every SARS case. The chief of staff at York Central Hospital in Toronto, Richard Schabas, criticized the city sharply in a letter to a Canadian journal devoted to infectious disease: “SARS quarantine in Toronto was both inefficient and ineffective. It was massive in scale,” he wrote. “An analysis of the efficiency of quarantine in the Beijing outbreak conducted by the American Centers for Disease Control and Prevention concluded that quarantine could have been reduced by two-thirds (four people per SARS case), without compromising effectiveness.” In other words, the mass quarantines we see in virus horror movies like I Am Legend are not the way to stop a pandemic. They burn through health-care resources and are ineffective.

  If we’re facing a brewing pandemic, however, there are good reasons to avoid large-scale social events where the disease could spread. Canceling a large concert, or asking people to stay at home, are both part of a pandemic-containment technique called social distancing. Most experts believe that social distancing and quarantine on a limited basis can help: At UCLA’s David Geffen School of Medicine, biomedical model expert Brian Coburn and his colleagues claim that school closures and discouraging big public events can reduce the spread of flu by 13 percent to 17 percent. Voluntary quarantine in the home seems to work better than closing schools, though closing schools is often a sound policy because a microbe’s fastest route to pandemic status is to infect children.

  Vaccination must be global

  As we’ve seen already, quarantine works in only limited doses. What’s our next option? Let’s consider vaccination, which many of us are familiar with from the H1N1 (swine flu) pandemic of 2009. Vaccines program the immune system to recognize and neutralize disease-causing microbes that enter our bodies. When we get flu vaccinations, we receive a small dose of damaged and dead flu viruses that help our bodies build up antibodies tailor-made to stop the flu when it shows up. Vaccines are usually not cures, and don’t generally help people who are already sick; they are used as a preventative measure.

  Most pandemic modelers agree on one thing: Vaccines stop pandemics only if they are administered very early in the outbreak, before the disease has had a chance to spread. Laura Matrajt, a mathematician at the University of Washington in Seattle, has modeled several strategies for containing pandemics with vaccines. The problem, she points out, is that pandemics spread differently depending on the population—a rural outbreak is very different from an urban one. They also spread differently in the developed world than they do in developing countries, largely because children make up nearly 50 percent of the population in many developing countries (in most developed nations children are less than 20 percent of the population).

  Vaccinating children is vital in stopping a pandemic, because they are what Matrajt calls a high-transmission group. In other words, children are humanity’s biggest spreaders of disease. If we can vaccinate kids against a pandemic disease, it will spread slowly enough that we can contain it and protect adults, too. Coburn reports that some of his colleagues found that “vaccinating 80% of children (less than 19 years old) would be almost as effective as vaccinating 80% of the entire population.”

  The problem is, most children are in developing countries that cannot afford to buy vaccines. This is where science butts heads with social reality. Pandemic modelers have to add dark economic truths into their equations, and figure out how best to administer vaccines in a situation where perhaps only 2 percent of the population will have access to it. Matrajt and her colleagues came up with several scenarios in the developing and developed worlds, where people had access to different amounts of vaccine, ranging from 2 percent coverage to 30 percent. “For a less developed country, where the high-transmission group accounts for the majority of the population, one needs large amounts of vaccine to indirectly protect the high-risk groups by vaccinating the high-transmission ones,” they wrote in a summary of their work. Tragically, the countries that need the most vaccine the soonest are the least likely to get it.

  Though vaccine manufacturers like GlaxoSmithKline and Sanofi-Aventis have promised to donate millions of vaccines to developing countries, and the WHO can pressure developed nations to donate 10 percent of their stockpiles, these gestures are still woefully inadequate. After contemplating the imbalances in H1N1 vaccine distribution, Dr. Tadataka Yamada of the Bill & Melinda Gates Foundation’s Global Health Program was so disturbed that he wrote, “I cannot imagine standing by and watching if, at the time of crisis, the rich live and the poor die.” With the Gates Foundation, he published guidelines for the global sharing of vaccines, arguing passionately that “rich countries have a responsibility to stand in line and receive their vaccine allotments alongside poor countries.”

  When H1N1 spread far enough that the WHO declared it a pandemic, scientists worked rapidly to synthesize a vaccine and manufacturers churned it out. Still, the vaccine wasn’t available until many months after the pandemic had subsided, and developing countries weren’t able to afford as many doses as developed ones. Luckily, this particular strain of the flu was very mild, but the world economic situation is one major reason vaccines may not be the best weapon against pandemics.

  Decentralized treatment and “hedging”

  What about the most obvious strategy? That would be treating the sick with medicines that kill the pandemic disease. In the case of flu, the treatments come from a few antiviral medications. In the case of a new outbreak of the bubonic plague, we’d look to antibiotics. But we have to ask ourselves the same questions we did when considering how to use vaccines to stop a pandemic: How will we get enough medicine to enough people fast enough?

  The answer isn’t just to send everybody to the hospital. First of all, people may be sick in areas where there are no hospitals, and second, during a pandemic, hospitals will be overwhelmed with sick people already. Plus, sick people may not actually be able to get out of bed and go to the hospital—especially if everybody in their family is sick, too. The University of Melbourne’s Robert Moss is an immunizat
ion researcher who points out that we’re going to need to come up with some novel ways of delivering antivirals in the event of another pandemic. After researching the ways antivirals were prescribed during the H1N1 pandemic, Moss and his colleagues discovered that medicine wasn’t handed out in a timely fashion because of one simple bottleneck: testing facilities. Most doctors conscientiously sent out blood samples from every person who visited them claiming to have the flu, and waited to hear back from often distant labs for diagnosis. As a result, people went untreated and more cases piled up as labs were overwhelmed. During a more deadly pandemic, the situation would have been disastrous.

  Moss believes there are a few simple ways that doctors can simplify the process of prescribing medication to avoid this bottleneck. He calls it decentralization. If a pandemic is under way and labs are overrun, the best way to diagnose patients is based on the symptoms that they present with. Do their ailments sound like the pandemic disease? Then give them the medicine. There’s no time to waste. In addition, Moss recommends setting up informal treatment centers in as many places as possible, including online, to make it easy for people to get diagnosed. Nurses who can’t normally prescribe medicines should be allowed to prescribe the antivirals if a patient has the symptoms of the pandemic disease. And couriers should deliver them to people’s houses.

  The developing world might be better prepared for this decentralized method than the developed, mainly because many medicines in these countries are already handed out via decentralized, informal treatment facilities. Health-care workers treating everything from yellow fever to cholera have set up treatment stations in remote regions, hoping to reach the largest number of people.