Last February, when COVID-19 was just beginning to visibly emerge from China, I was asked to participate in a Laboratory panel discussion about the spread of this novel coronavirus and what it might mean for the United States. Having studied emerging zoonotic diseases for 25 years, I knew the outlook was troublesome, but I was still optimistic. I had a good idea of the extensive disruption that was coming our way, and yet, when the situation escalated dramatically a month later, I still found it hard to believe and harbored a strong sense of denial.
Anytime I’ve given a public lecture on emerging diseases and pandemics, I have shared a photo of a gravestone in Kansas that belongs to my great-aunt, Margret Ann Fair, who died of the 1918 influenza at the age of four. I often read her obituary to make the point that likely everyone in the room has an ancestor in their family tree who died during the 1918 pandemic. Like most researchers who study emerging infectious diseases, I always said that it was not a question of “if” a new disease could become a pandemic; it was instead a question of “when.”
And yet, there are days that I still can’t believe it is actually happening to us right now.
How did we know?
The reason I said it’s a question of “when” is because it is not uncommon for new diseases to emerge. Pathogens that can infect multiple species—such as rabies, influenza, and Ebola—are everywhere. Infectious diseases frequently spill over from animals to humans and vice versa, but we don’t always notice. Sometimes the pathogen is not particularly virulent, meaning it does not cause severe disease. Other times a pathogen may infect a “dead-end host”—one that does not transmit the pathogen further.
The key to a spillover becoming an international crisis is a combination of transmissibility and virulence. Avian flu (H5N1), for example, is extremely virulent and can make a person deathly ill in a short amount of time, killing about half of the humans it infects. This is scary, but with known pathogens of pandemic potential there has often been a tradeoff between virulence and transmissibility. The H5N1 avian influenza virus attacks us deep in the lungs and therefore is not as transmissible as seasonal influenza, which replicates more in the upper respiratory system. On the other hand, common colds—many of which are caused by coronaviruses—are extremely transmissible but not very virulent.
Infectious diseases frequently spill over from animals to humans and vice versa, but we don’t always notice.
Severe Acute Respiratory Syndrome (SARS), which emerged in 2002, is a deadly disease caused by SARS-associated coronavirus (SARS-CoV). This was the first severe and readily transmissible disease to emerge in many decades; it quickly spread to more than 20 countries, infected about 8000 people, and killed 774. In 2012, a related coronavirus emerged as a much more deadly disease. Middle East Respiratory Syndrome coronavirus (MERS-CoV) infected about 2500 people and caused 858 deaths. Fortunately, MERS was also not particularly transmissible and was quickly controlled.
Today’s pandemic is caused by SARS-CoV-2. It is closely related to SARS-CoV and MERS-CoV, but it had the correct mix of transmissibility and virulence to take the world by storm. With SARS-CoV-2 there are no tradeoffs: it is easily transmitted between people and it is very deadly in some. But it is that extreme variability in the disease characteristics and virulence in humans that adds to the perfect storm. SARS-CoV-2 can take from five short days to two entire weeks to incubate in a host before it causes coronavirus disease 2019, COVID-19 for short. But in some people, it never shows itself. Many who are infected with SARS-CoV-2 do not experience any symptoms (they are asymptomatic) or experience only mild symptoms—but they can still transmit the virus. The potentially long incubation period and pre-symptomatic or asymptomatic spread are some of the reasons this virus is so serious and also so complicated. All of this variation in the disease and transmission leads to variation in human behavior and in our response to the pandemic. This variation is something we are all witnessing every day.
It is not possible to predict exactly when a mutation will happen to make a pathogen pandemic-worthy or to anticipate when a spillover will occur. However, scientists know there are situations that can increase the likelihood of a spillover event, such as changes to the environment and climate or significant interactions between humans and wildlife (e.g., eating bushmeat or going to live meat markets). Scientists have combined these attributes to predict hotspot areas for emerging diseases. There is also a lot that we do know that can help with prediction. If we know which specific pathogens have pandemic potential, and which animals harbor those pathogens—we call them disease reservoirs—then we can monitor them as part of our global biosurveillance effort.
SARS-CoV-2 most likely originated in bats. Bats and humans—and other animals like cats—have angiotensin-converting enzyme 2 (ACE2) attached to the outsides of their nasal, lung, and kidney cells. These ACE2 enzymes normally serve as docking stations for a protein called angiotensin that helps regulate blood pressure, wound healing, and inflammation. SARS-CoV-2 binds to ACE2 as a way to gain entry into cells. This is how diseases can jump between species: if humans share certain receptor molecules with animals, then pathogens that use those receptors can spread to humans.
Humans in some cultures eat wildlife, and often keep them in live meat markets where refrigeration is not possible. Wild animals in cages in these “wet markets” are under stress, which makes them more vulnerable to disease than they might be in the wild. And this is how spillover happens: a person is exposed to an infected animal and if the pathogen has new mutations or is novel to that person’s immune system—and if it has the ability to dock and enter the person’s cells—the emergent pathogen could infect the person. If this happens, the pathogen could thus take hold in a new species.
The “One Health” paradigm is the concept that the environment, wild animals, agriculture animals, humans, and pathogens are interconnected. It is important to understand each of these compartments and their connections to ensure the health of all populations on the planet.
The ecology of infectious diseases is something I have been studying for the last 25 years. I have been fortunate to have met the top scientists around the world who study infectious diseases and spillover events. These researchers are some of the most dedicated and hardworking scientists anywhere, and their efforts are now focused on helping the global community understand why this pandemic happened and what to do before the next one.
Canaries aren’t the only harbingers
I first came to Los Alamos to do my graduate work on western bluebirds. I became interested in zoology as an undergraduate—giving up my previous plans to study bass violin—when I realized I just couldn’t stop thinking about the natural world. During my time as a graduate student at Colorado State University I worked on a United States Department of Agriculture project on the impact of insecticides on birds. I became interested in toxicology and understanding the effect chemicals have on the immune system and other physiological processes that make an animal more susceptible to infectious disease.
SARS-CoV-2 had the correct mix of transmissibility and virulence to take the world by storm.
My graduate work with the Environmental Restoration project at the Lab was an opportunity to set up a network of nestboxes across the Pajarito Plateau (upon which Los Alamos sits) with which to study wild bird individuals and populations. We wanted to determine if stresses such as legacy environmental pollution, food limitation, habitat changes, or climate shifts were impacting the birds in the region. With the nestboxes, we could take physiological measurements of the birds that were surviving and breeding, but to thoroughly answer our questions we needed a way to measure the birds’ immune systems. The year 2020 was the 24th field season for the Los Alamos Nestbox Network (now operated by the Lab’s Environmental Stewardship Group), and I am grateful to the teams of students and staff who have dedicated their time and passion into keeping this project going. As it turns out, long-term studies are how we can answer these difficult questions.
One of the things that attracted me to Los Alamos—and kept me here—is the innovation in biotechnology and modeling. For example, the invention of flow cytometry (a tool for evaluating and sorting cells) and the seminal work in genomic sequencing both happened here. I saw an opportunity to apply these tools to novel systems, such as wildlife and infectious-disease surveillance. My colleagues Kirsten McCabe, Babetta Marrone, and I worked to develop flow cytometry-based immunological assays to detect antibodies in different species of birds because most tests had been developed for chickens and wouldn’t work on other species. In 2003, when New Mexico was hit the hardest by West Nile Virus, we lost 98 percent of the black-billed magpies in the Pojoaque valley below Los Alamos. This project led us to explore a central question to understanding infectious diseases: Why are some species susceptible while others are dead-end hosts?
Species susceptibility is one aspect of studying emerging diseases, as it helps focus surveillance efforts on the appropriate animal populations. Furthermore, it is critical to appreciate all the factors that can make an animal stressed, which also adds to its susceptibility. Stress is a physiological response in the body, and some stress hormones, like cortisol, are known to suppress parts of the immune system, such as the inflammatory response. Being in a cage at a wet market is one source of stress for an animal, but there are many others. Deforestation and other human activities lead to habitat loss, forcing animals to move to new areas where they may face food insecurity or new predators. Biodiversity in areas around the world is a good index of a healthy system; it is often inversely related to the occurences of emerging zoonotic diseases and outbreaks. Environmental changes, especially to the climate, can also lead to forced migration of animals. Finally, environmental pollution, as we have long been studying in Los Alamos, can be a source of stress if it causes damage to animals’ immune systems or reproductive systems.
Using the Los Alamos Nestbox Network, our results showed that legacy environmental contamination had little impact on the birds. However, we observed large impact to the birds from habitat changes. The increased temperatures in Northern New Mexico and resulting tree die-off at lower elevations forced the birds to move to higher elevations. Furthermore, in the drought year of 2002, nestling bluebirds had half the immune system capacity compared to a normal year.
Recently, we observed an example of multiple stresses combining to cause a mass wild-bird mortality event. In September 2020, an estimated one million birds died in New Mexico and southern Colorado, where they had been experiencing a combination of drought, wildfire smoke, and weather extremes (temperatures close to 100 degrees Fahrenheit one day and snow two days later). Because of this event, we are creating a Southwest Avian Health Network to connect ornithologists in New Mexico to those in neighboring states.
As my work progressed over the years, I began to focus my attention on measuring other signatures in birds to help with assessing disease susceptibility. Some of my studies focused on a sugar molecule called sialic acid, which is the receptor for influenzas. Knowing that avian influenza is highly pathogenic in chickens but causes minimal disease in other bird species, we sought to determine if different birds have varied amounts of sialic acid, which could make some more susceptible, or even superspreaders, of disease. In a recent publication, we demonstrated that sialic acid does indeed differ among bird species and that some blood cells in birds had more human-type sialic acid than expected. This is an important finding for birds, since sialic acid is also a receptor for the parasite Plasmodium, which causes malaria in birds and humans.
So many systems
To this day, I continue my work studying bird species’ susceptibility to disease and biosurveillance in animals. However, in 2004 I also began broadening my scope and looking at pandemic modeling as part of a Department of Homeland Security project on H5N1 avian influenza. Our project focused on modeling the impact of a pandemic on critical infrastructures. We looked at hospital capacities, the impacts of closing schools and limiting contacts, and the effectiveness of targeting treatments if available. (With influenza, we knew that Tamiflu could help but that we would have limited doses.) In 2009, we were part of a multi-team effort at the Laboratory using several of our epidemiological models to predict the impacts of different scenarios for pharmaceutical and vaccine interventions for the spreading H1N1 influenza (“swine flu”) pandemic. It was exciting to work with the amazing scientists and epidemiologists at Los Alamos, and it was a true collaborative effort.
This pandemic is transformative, pushing science and collaborations to their highest potential.
It was during my eight years with this critical infrastructure modeling team at Los Alamos, and with two Laboratory-directed exploratory research projects for understanding both West Nile Virus and avian influenza host heterogeneity, that I fell in love with scientific collaboration. While the science was engaging and interesting, it was collaboration with my colleagues that most excited me. I began to seek out information to learn how to make collaborations better and how to foster collaborations between my fellow researchers. I became enthralled with the emerging field of the “science of team science” and what makes transformative science teams. I sought everything I could read on leadership, communication, and teamwork. This interest would pay off later when I did an assignment in Virginia as a Biological Threat Reduction Program (BTRP) Science Manager with the Defense Threat Reduction Agency.
Although genomic sequencing technology was advancing at a rapid pace in the early 2000s, enabling scientists to evaluate the blueprints of organisms and thoroughly understand how they are related and how they differ, its full potential could only be realized via strong international partnerships. When it comes to pathogens, the genetic blueprint is vital, and current sequencing technology makes it possible to study a genome relatively quickly. As we see today with COVID-19, most testing is based on reverse transcriptase polymerase chain reaction (RT-PCR), which matches pieces of the viral RNA from a patient to known SARS-CoV-2 sequences.
Accessing sequence data from around the world is critical to our ability to understand biological threats such as SARS-CoV-2 and others. This data availability, however, depends on two things: that other countries have the technology to provide such data and that we have cultivated relationships with them so that we can easily collaborate. In 2011, Los Alamos began participating in two programs to promote international scientific engagement: the BTRP and the Department of State’s Cooperative Threat Reduction (CTR) program. Through these programs, Los Alamos scientists have helped establish sequencing centers in multiple countries (including the Republic of Georgia, Jordan, Kenya, and Uganda), and my amazing colleagues continue to support more than 29 countries worldwide with ongoing sequencing and bioinformatics training.
I believe these cooperative-engagement programs comprise some of the most important international efforts by the United States. In my role as a BTRP Science Manager (2013–2016), my job was to help the United States develop collaborations with partner countries to build their capabilities in detection, diagnostics, and reporting. As a result, biosurveillance and infectious disease technologies were strengthened in these partner countries, and we created strong, lasting relationships through scientific diplomacy and building trust between countries. Through this partnership, diagnostic laboratories around the world were better prepared to respond to the COVID-19 pandemic and provide ample and accurate diagnostic testing for their citizens.
When “if” becomes “now”
It is strange to spend decades studying something you hope won’t happen, but here I am. This pandemic was accurately predicted—we knew the hotspots where a spillover would most likely occur, and we knew that coronaviruses could spill over. We also knew what to do: stamp it out when it starts, test, contact trace, and quarantine. Yet here we are.
Since February, I have spent my time focusing on two main areas. First, my colleagues and I are supporting our BTRP partner countries by sharing best practices both to improve COVID-19 sequencing and genomics in their local laboratories and to help feed the international databases with valuable sequences. Second, we reconvened our critical infrastructure modeling team, gave it a new name, and have been ferociously working on developing a modeling experiment to understand the uncertainty of the pandemic. Now called MEDIAN (Modeling Epidemics for Decision support with Infrastructure ANalysis), this systems-dynamics model includes a range of distributions for all aspects of what is going on, from disease characteristics (incubation, pre-symptomatic transmission, mortality rate) to the uncertainty of human behavior (quarantining, wearing masks, rates of contact tracing).
Using MEDIAN, we are looking to identify the most important factors contributing to the severity of the pandemic. Our model is not about predicting how many people will be infected tomorrow or will die next week—other Los Alamos models examine this important aspect. Instead our goal is to take into account the uncertainty and variability in the pandemic to help understand which things are driving its spread and where to focus our response.
This understanding is derived from specifically designed experiments where we evaluate various distributions and look for key correlations. For instance, we might design an experimental run that has a disease incubation period of 5–14 days, with a percentage range of pre-symptomatic transmission, an age distribution of mortality rates, and a few other variables, each with a lot of uncertainty. Then we can run 10,000 simulations overnight covering all the uncertainties and we get a spaghetti figure of epidemic curves that is not that helpful. However, once we have this spaghetti figure, we can use statistics to pull out the most important disease and mitigation variables driving the epidemic. For the COVID-19 effort, we are focusing on the role of diagnostic testing. This will help us investigate the different patterns associated with testing strategies. For instance, we are seeking to correlate the impact of mass testing with contact tracing and quarantine on the number of cases and deaths.
One day at a time
This is hard. There is still so much uncertainty with this pandemic, and it can be overwhelming. However, there is much we do know that can help us today and that will help us prepare for tomorrow and the next emerging disease. Our work on COVID-19 is immediate and critical, but the rest is still important.
Our small lab group in Bioscience Division is looking at the big picture of emerging disease by taking into account all aspects, such as climate change, environmental change, biodiversity impacts, and plant pathogens, as part of our Ecological Health Security Lab. For example, understanding how long-term environmental change impacts future mosquito distributions and the infectious diseases they carry is one important aspect. To address this, we are part of a new Laboratory-directed project to couple Earth systems and epidemiological models; this infectious disease-climate team is a true collaboration across many directorates and divisions at Los Alamos.
Ecological health security is the epitome of a complex system. Our ecology is changing: our proximity to and relationships with animals are evolving, our climate is adjusting, and the plants and wildlife are adapting (or not). This pandemic will not be the last, but hopefully it will be the worst—because we will learn from it and prepare. The conditions are ripe for new diseases to catch us off guard, but we have the technology and the partnerships to respond. This moment is transformative, pushing science and collaborations to their highest potential.
I still have moments where the reality of COVID-19 hits me hard—we never thought it would be this bad. But I try to stay positive and be grateful each day for nature, for the people in my life, for living in our amazing state of New Mexico, and for my health. I also know that tough times never last, but tough people do! And to be honest, waking up with a pressing purpose in the morning can be a good thing. LDRD