Authors: Nathan Wolfe
The findings coming out are fascinating. Our guts are teeming with a complex assemblage of microbes, many of whom are long-term residents. They are not simply free riders. A great deal of the plant material we consume requires bacteria and their enzymes for digestion; human enzymes alone would not do the trick. And how the community of microbes is structured makes a big difference.
In a pivotal series of studies, Jeff Gordon and his students and postdocs (many of whom are now successful professors themselves) showed just how important the communities of bugs in our guts actually are. They have demonstrated that obesity is associated with a decreased relative abundance of one particular group of bacteria—the Bacteroidetes.
In another elegant study, Gordon and his team showed that the obese microbiota increases the amount of energy that can be obtained from food. In the final coup de grâce, they showed that altering the gut microbiota of normal mice with the obese microbiota results in significant weight gain. Very simply, bacteria in our guts play a role in obesity. Just as we saw with cervical cancer, a microbial cause of a chronic disease may point to an easier method to solve it. One day we may very well use a combination of probiotics and antibiotics to subtly alter our gut microbiota and to help us maintain a healthy weight.
Perhaps not surprisingly, the teeming masses of microbes in our guts also play a role in how we’re affected by deadly microbes. In the case of salmonella, a deadly bacteria and one of the leading causes of food-borne illness, it’s been known for some time that the biggest risk factors for the disease are eating eggs away from home and using antibiotics. Eating eggs is a risk factor since chickens infected with the bacteria can contaminate them. The antibiotic use, however, has long presented a mystery.
Recent research on gut microbiomes may shed some light. Justin Sonnenburg, a Stanford professor, is conducting important work to do just this. He uses an incredible system for maintaining germfree mice in a laboratory. The rodents live in completely sterile conditions—even to the point where their food is autoclaved before they eat it, eliminating any potential microbial contaminants. The germfree rodents provide a perfect model for picking through the exact determinants of different gut microbiota on the conditions of their hosts.
While it’s long been suspected that antibiotic use kills helpful microbes, thus damaging the natural shield that our gut microbes provide against new and invasive bugs like salmonella, it’s still not clear exactly how this happens. In the future, the work done in Sonnenburg’s lab should tell us.
There are gentle microbes out there—bugs that help us, defend us, and live quietly within us doing no harm at all. If we could accurately determine which of the microbes on our bodies and in the environment were beneficial to us and which were rogue, we’d find something pleasantly surprising: the harmful ones are certainly in the minority. The goal of public health should not be to have a completely sterile world but to find the rogue elements and control them. A key part of addressing the nasty microbes will be to cultivate the microbes that help us. One day soon, the way we protect ourselves may be by propping up the bugs that live within us rather than knocking them down.
12
THE LAST PLAGUE
The large, brightly lit, white-walled room appears at once chaotic and oddly organized. Young kids in their Silicon Valley uniforms of hoodies and sneakers sit hunched over laptops, talking on the phone and instant messaging while simultaneously mashing together and analyzing massive amounts of disparate data. Large monitors with maps and streaming news line the walls. There are no windows, so it’s hard to determine if it’s daytime or evening. Discarded coffee cups and junk food wrappers also fail to reveal the hour. Occasionally an older group wearing suits and formal business attire enters, chats, and then just as quickly disappears. As the discussion comes into focus, its purpose emerges: a 24-hour global situation room for emerging diseases.
At the top of the agenda of this California control room are Nigeria, Dubai, and Suriname. Clear signals from the masses of data collected have elevated their risk profile to “regular alert,” which means that roughly 20 percent of the team’s effort is focused on getting more data, interfacing with on-the-ground team members, and conversing with local and international health leaders. In the case of Suriname, the problem has already hit the news. Hospital admissions have been up over the past twenty hours, and a local newspaper article has hit with the potentially dubious report of cholera. In Nigeria and Dubai, the events so closely tracked in this room haven’t yet gone public. But they will.
A closer examination of one of the young analysts reveals what kind of data she’s crunching—disease data. With three active computer screens, she’s following the frequency of “chief medical complaints” filtered and forwarded from an early but robust cell-phone–based electronic medical record system located in Lagos. The frequency with which the users are reporting severe fever has increased steadily from baseline over the past thirty hours, and it matches independent over-the-counter drug purchase data for medications treating fever and malaise. The Twitter and Google trends on terms related to acute viral illness also seem to match. People are “telling” them they’re getting sick. The analyst’s teammates at the central African headquarters in Yaoundé have been on the phone with clinics for hours. The lab results are still pouring in, but the uptick is due to none of the usual suspects; it’s not malaria or typhoid, nor is it Marburg or Ebola.
On another screen, our analyst Skypes with someone on the hacker team. They’re opening the repository data feed with the lab in Lagos. Soon the local group will have the potential to upload reams of new genetic data from specimens that are just now being examined. Computer algorithms and bioinformatics engineers will search for the needle in the haystack—the new virus that appears to be killing people in west Africa.
Our analyst’s immediate boss is the Room Controller—a specialist who must weigh the data and evaluate the rankings that the computer systems are providing. Does Nigeria move up to “full alert” status as the algorithms recommend? How does this compare with the faint but potentially frightening bioterror chatter coming out of Dubai, where aggregated purchase data suggests that someone is buying equipment normally used to grow huge batches of bacteria? And how will it measure during the daily briefing against the longer-term trends examined in the chronic-infection group that seeks to identify unseen and creeping killers, rather than the more immediate but obvious flare-ups of the control room? What happens in this room is fast paced, globally interconnected, and potentially world saving.
This scenario is fiction. There is no such control room—yet. The reams of data from electronic medical records in Lagos do not yet exist, and the data from pharmacies are not yet well coordinated and compiled. But while we’re not there yet, the control room is exactly what we need—an innovative group devoted entirely to understanding and analyzing biological threats and catching them before they become disasters.
I’ve spent time in the closest equivalents our planet currently has to such a control room. During the beginnings of the H1N1 influenza pandemic, I visited with Scott Dowell—the head of the CDC’s Division of Global Disease Detection and Emergency Response—in the CDC’s control room, where the team rapidly responded to the mounting reports of illness in Mexico. I’ve also spent time in the WHO’s control room used during pandemic and other health emergencies. My organization, Global Viral Forecasting, is part of the WHO’s Global Outbreak Alert and Response Network. Sadly, bureaucracy, insufficient and ever-shifting funding, and constantly changing objectives from higher up the food chain hamper both the CDC and the WHO. These organizations need to grow stronger and better equipped, and they desperately need more funding. But even then, more will be needed.
* * *
In this final chapter, my hope is to review where we’ve come so far in the book. How do the history and advances stack up—in our favor or against us?
I’ll also try to answer some questions that I often get asked as a virologist. What steps do I personally take to mitigate my risk of infection? How should individuals evaluate a pandemic or biological threat while it’s occurring?
I’ll also do my best to answer the broader questions about what I believe is needed for the planet. What are the largest impediments to controlling future pandemics? What are we doing to get to the vision of the futuristic control room imagined above?
In the previous chapters, I’ve tried to provide a picture of where we currently stand in regard to pandemics and other microbial risks—to explain the central characters, the microbes, on their own terms and to examine how the major events in our history have affected our relationship with them.
What we’ve seen is that a range of early events created the conditions for a perfect viral storm. The advent of hunting in our biological lineage created a species that suddenly interfaced with animals, permitting a flood of new microbes into prehumans. And the near-extinction event we experienced likely left us ill prepared to deal with them.
We saw how an increasingly populous and interconnected world served to push us toward the center of the storm. Domestication of animal populations, the growth of urbanization, and our miraculous transport system tied together populations in ways unprecedented in the history of life on our planet. Particular human flourishes, including transplantation and injection, provided completely new routes for disease agents—whether natural or purposefully introduced—to spread and create havoc.
Chapters 9 and 10 gave a sense of the contemporary tools we have that might allow us to countervail against the rising threat of pandemics—new techniques for diagnosing microbes and new methods for monitoring people and communities. Contrasting with most of the book’s presentation of harmful bugs, chapter 11 explored the emerging uses and benefits of many harmless microbes.
* * *
As a professional microbiologist, one common question I get is how do I personally mitigate my risk of infection? For starters, I always keep my vaccines fastidiously up-to-date. When I am in malarious regions, I take malaria prophylaxis religiously. I didn’t always do that, but I learned the hard way how important it is.
During winter months, I’m aware of transmission routes for respiratory illnesses, and I do my best to decrease my risk of acquiring them. Public transport is a notorious risk due to the mass movements of humans through it, so I try to wash my hands or use a simple alcohol-based hand sanitizer when leaving subways or planes. Likewise, I’m aware of times when I’m shaking large numbers of hands and try to wash them soon after or avoid touching my nose or mouth unless necessary. Certainly doing your best to ensure consumption of clean food and water is important, and so is working to limit risk associated with unsafe sex. Of course, these answers really depend on who you are and where you live. Sadly, access to clean water, vaccines, good malaria drugs, and condoms are by no means universal—but they need to be for
everyone’s
sake.
Perhaps of equal interest is how to evaluate the news reports and assess risk when an outbreak occurs. This can be done by focusing on a few particular features of the epidemic. How is the microbe spreading? How effectively is it being transmitted? What percentage of people that it infects is it killing? A very deadly epidemic that
doesn’t
seem to be spreading is less worrying than a nominally deadly pandemic that’s moving at a fast and efficient clip. Things that seem terrifying, like the Ebola virus, aren’t always global risks. And things that seem benign, like HPV, sometimes can be devastating. Fortunately, basic facts about transmissibility and deadliness can help anyone evaluate the risk.
Assuming that living in one location or courting a certain quality of life makes you immune from the risk of a pandemic is wrong. While HIV didn’t spread around the world randomly affecting people, it affected very poor people and very wealthy people alike. It affected people with almost no access to health care and, in the case of hemophiliacs, some of the people with the best health care in the world. We’re all on one interconnected planet.
* * *
Among the most pressing questions I get when I speak to audiences globally about these issues is “Ok, I get it and now I’m scared. How do we deal with this?” One of the greatest impediments to predicting and preventing future pandemics is the notion that pandemics occur randomly and are inherently neither predictable nor preventable. If I have done nothing else in this book, I hope I have repudiated these ideas. Prediction and prevention of pandemics will not be easy, but there is much we can do right now, and the advances that are steadily occurring will allow us to do even more in the future.
Not having an active public health mind-set of pandemic prevention has led to hugely inefficient systems in the past. Among the best terms I’ve heard to describe these inefficiencies and overreactions is
disease du jour
. When we have an influenza threat, we drop everything and focus on mitigating risk from future influenza pandemics. When we have SARS, we focus on unknown respiratory diseases. The list goes on.
One day we may be able to rank the greatest future risks for pandemics, but for now we cannot. We know that they’ll almost certainly be microbes that come from animals and that some spots around the world pose greater risks for their entry. We need resilient systems that don’t assume the next threat will be influenza or SARS or whatever the au courant infectious disease happens to be. The systems should be generic and forward focused. They should target the unknowns and the general patterns that gave us our past pandemics, rather than any of the specific pandemics we’ve had. This doesn’t mean we should disregard the excellent global influenza surveillance systems or the wonderful work done by my colleagues, like Derek Smith, who uses data on global samples of seasonal influenza to predict the next year’s strain and develop vaccines against it. But we should also recognize that those systems will help us mitigate future influenza risks—
not
the risks associated with the next unknown agent.