Catching the Next H5N1 Before it Hits

How understanding our interactions with animals could prevent the next global pandemic

Published on February 12, 2013 by Lauren Weisenfluh

When the bird flu, or H5N1, began sweeping across three continents in 2004, it caused a worldwide panic, killing more than 50 percent of its 600 human victims and 100 million birds. It also added to growing fears about the unpredictability of such epidemics, which were taking an increasingly more significant economic and human toll.

Although H5N1 seemed to come out of nowhere, the early 2000s was not the first time the world had encountered the virus. Five years earlier, H5N1 left plenty of so-called “viral chatter”—small outbreaks that precede large outbreaks—killing six of the 18 people who were infected in Hong Kong, China. If scientists had recognized these infections before they turned to outbreaks and then a global pandemic, the story of H5N1 would have been much different.

“No emerging infection has ever been predicted before it appeared in humans,” says Dr. Stephen Morse, a professor of epidemiology at the Mailman School of Public Health and an expert on emerging infectious disease.

Up to this point scientists have never been able to identify a highly contagious pathogen like H5N1 until it has broken out in humans and, in most cases, left some damage in its wake.

Dr. Morse and a small cohort of fellow infectious disease epidemiologists are trying to change this. They say the current approach is too reactive, that in a 21st century world where disease emerge and travels quickly across the world, surveillance needs to search out the infecting pathogen before it ever enters a human.

Considering that 60 percent of all emerging infectious disease, such as HIV, H5N1, and pandemic influenza, originated from animal sources, the evidence for targeting the link between animals and humans is persuasive.

“We see new things all the time,” says Dr. Nathan Wolfe of Metabiota, who studies pre-emergence interactions in African bush meat hunters. “We see new retroviruses out there—which is the category that HIV falls into—and we’re very, very concerned because this is the part of the world where HIV jumped from chimpanzees to humans. There’s no reason why other viruses in that same class won’t have the capacity to leap to humans.”

Once diseases are identified, health authorities have been able to prevent its spread by quarantining infected people and administering vaccines. However there can be significant lag time between when people are infected and when they show symptoms –sometimes weeks, or even months after becoming infected. By the time a pathogen is identified, much damage has already been done.

The approach of scientists like Dr. Morse is to pre-emptively identify potential outbreaks before they emerge by going directly to the source—the frontlines of where humans and animals co-exist.

These landscapes can include anything from animal markets in China—where dinner is butchered on the street—to pig farms in Malaysia, to illegal bush meat hunting in central Africa.

In a December 2012 Lancet article, Dr. Morse and his co-authors say that authorities need to monitor such locations where dense populations of humans and animals interact—“hotspots” for emerging infectious disease.

It is here that pathogens often jump from an animal to human, resulting in what is known as a novel zoonosis, a transmissible disease or infection between vertebrate animals and humans.

“There is no question of whether we will have more zoonotic pandemics – the question is merely when and where the next pandemic will emerge,” says Dr. Morse. “The challenge now is to establish whether and how researchers can intervene before a pathogen reaches the human population and develop appropriate triggers for action.”

At the forefront of disease prediction systems is Dr. Morse’s PREDICT project, part of USAID’s Emerging Pandemic Threats Program.

PREDICT focuses on the rapid detection of pathogens at an early stage by building laboratory capacity to meet these threats, and coordinating with a wide range of authorities to respond.

The organization is currently active in 20 viral “hotspot” countries, which have been identified by computer models as high risk for disease emergence.

Because of globalization, close interactions between animals and humans—like hunting and butchering—are increasing, making it more likely that novel pathogens will spillover into the human population.

By figuring out how and where humans alter the landscape, and identifying areas of high biodiversity, scientists can determine where novel zoonotic pathogens are likely to spill over into the human population.

The technology is undeniably in its infancy, challenging scientists to push beyond their current capabilities into new lines of inquiry to look at new routes of transmission, and the ability of a pathogen to evolve into the next pandemic.

“It’s essentially risk assessment, being able to understand what is out there and its potential before it really gets into the population,” says Dr. Morse.

These changing dynamics provide the ideal environment for the emergence of novel pathogens, a stage referred to Dr. Morse and his colleagues as “pre-emergence”—when a pathogen is still in its natural reservoir, usually wildlife, yet is changing its interactions with potential hosts, such as livestock and humans. Examples include the encroachment of livestock into wildlife, and ecological changes due to climate change.

PREDICT partners with other organizations, such as Metabiota, to understand pathogens at this stage of “pre-emergence” in viral hotspots.

Embracing a principle that a coalition of clinicians and veterinarians call One Health, that human and animal health should not be studied in isolation, researchers at Metabiota travel to the heart of Africa to hunt for viruses that are on the brink of emergence from wildlife into human populations.

In central Africa, people rely on illegal bush meat hunting—the butchering of wild animals—to feed their families and provide income. These hunters are in close contact with the blood and guts of their game, acting like a driver who has stopped on the side of the road to allow a pathogen to hitchhike into human populations.

Dr. Wolfe is currently working with bush meat hunters to catch these pathogens before they emerge in humans.

To do so, he teaches the hunters to collect bush meat blood on cards after butchering. These cards help preserve the blood’s microscopic contents as they are transferred to a facility for identification.

The microscopic life of these blood cards are subsequently analyzed and catalogued by microbiologists, such as Dr. Ian Lipkin, an internationally renowned expert on pathogen discovery and director of Columbia University’s Center for Infection and Immunity—known as the “man from which viruses cannot hide,” and a co-author with Dr. Morse of the 2012 December Lancet article.

“We’ve discovered at least 400 new viruses since I came to Columbia in 2002, and the process is accelerating,” said Dr. Lipkin in an interview with the New York Times.

Tremendous strides in molecular diagnostics have made pathogen discovery closer to reality than science fiction. Integrative polymerase chain reaction (PCR) sample preparation has simplified pathogen identification. Scientists can cheaply identify pathogens at the family level using broad-based PCR, avoiding costly technology that identifies pathogens at more specific levels—such as species.

One difficulty is in identifying which pathogens will actually jump from an animal to a human, since many pathogens never leave their host species.

Scientists are still trying to figure out what makes one pathogen more likely than another to make the fatal jump.

“There’s no established methodology for this,” Dr. Morse says. “That’s what makes it interesting. How do you separate [pathogens at high risk of emergence] from all of the noise? That’s the challenge with prediction.”

Regardless, information like that being gathered by Dr. Wolfe would have been invaluable during the early stages of the 2002 H5N1 outbreak.

“By capturing this moment [of intimate interaction between bush meat hunters and their prey], we might be able to move to a situation where we can catch [pathogens] early,” notes Dr. Wolfe.

Advances in communication technology have played a key role in disease forecasting systems. Cell phones and social media have provided a much faster and easier way for users to report real-time outbreaks.

While the technology is fragmented throughout the world, the ability of Twitter and Google Flu Trends to accurately predict infectious disease outbreaks suggest they will play a key role in the future of disease forecasting. With the help of this technology, professionals can identify and contain localized outbreaks at an earlier stage than historical surveillance systems.

Yet, without political recognition and investment in these disease prediction systems, they are unlikely to succeed. The budgetary coordination and ability to build and maintain these systems on both local and national government levels “might be the greatest challenge of all,” concede Drs. Morse, Lipkin, and co-authors.

As with any new technology in its infancy, there are also skeptics.

“It’s outside people’s comfort zones” Dr. Morse says. “We tend to divide the world up into disciplines…we need a cultural change. That’s going to take time. My hope is that the younger generations will be more amendable to it.”

With worldwide health at stake, the incentive for the embrace of disease prediction systems by both policy makers and scientists is urgent.

Says Dr. Morse: “With new technologies, for the first time in history, we are now poised to predict and prevent emerging infections at the source, before they reach us.”

Edited by Elaine Meyer. Additional research by Arti Virkud.

Lauren Weisenfluh
Lauren is a 2nd year Mailman student pursuing her Master's in Public Health with a concentration in Epidemiology. She's particularly interested in the intersection between ecology and public health—specifically, emerging infectious disease. Follow her @LaurenWeisenflu.

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