New tools could catch disease outbreaks earlier - or predict them
Every year, the villages which lie in the so-called ‘Nipah belt’— which stretches along the western border between Bangladesh and India, brace themselves for the latest outbreak. For since 1998, when Nipah virus—a form of hemorrhagic fever most common in Bangladesh—first spilled over into humans, it has been a grim annual visitor to the people of this region.
With a 70 percent fatality rate, no vaccine, and no known treatments, Nipah virus has been dubbed in the Western world as ‘the worst disease no one has ever heard of.’ Currently, outbreaks tend to be relatively contained because it is not very transmissible. The virus circulates throughout Asia in fruit eating bats, and only tends to be passed on to people who consume contaminated date palm sap, a sweet drink which is harvested across Bangladesh.
But as SARS-CoV-2 has shown the world, this can quickly change.
“Nipah virus is among what virologists call ‘the Big 10,’ along with things like Lassa fever and Crimean Congo hemorrhagic fever,” says Noam Ross, a disease ecologist at New York-based non-profit EcoHealth Alliance. “These are pretty dangerous viruses from a lethality perspective, which don’t currently have the capacity to spread into broader human populations. But that can evolve, and you could very well see a variant emerge that has human-human transmission capability.”
That’s not an overstatement. Surveys suggest that mammals harbour about 40,000 viruses, with roughly a quarter capable of infecting humans. The vast majority never get a chance to do so because we don’t encounter them, but climate change can alter that. Recent studies have found that as animals relocate to new habitats due to shifting environmental conditions, the coming decades will bring around 300,000 first encounters between species which normally don’t interact, especially in tropical Africa and southeast Asia. All these interactions will make it far more likely for hitherto unknown viruses to cross paths with humans.
That’s why for the last 16 years, EcoHealth Alliance has been conducting ongoing viral surveillance projects across Bangladesh. The goal is to understand why Nipah is so much more prevalent in the western part of the country, compared to the east, and keep a watchful eye out for new Nipah strains as well as other dangerous pathogens like Ebola.
"There are a lot of different infectious agents that are sensitive to climate change that don't have these sorts of software tools being developed for them," says Cat Lippi, medical geography researcher at the University of Florida.
Until very recently this kind of work has been hampered by the limitations of viral surveillance technology. The PREDICT project, a $200 million initiative funded by the United States Agency for International Development, which conducted surveillance across the Amazon Basin, Congo Basin and extensive parts of South and Southeast Asia, relied upon so-called nucleic acid assays which enabled scientists to search for the genetic material of viruses in animal samples.
However, the project came under criticism for being highly inefficient. “That approach requires a big sampling effort, because of the rarity of individual infections,” says Ross. “Any particular animal may be infected for a couple of weeks, maybe once or twice in its lifetime. So if you sample thousands and thousands of animals, you'll eventually get one that has an Ebola virus infection right now.”
Ross explains that there is now far more interest in serological sampling—the scientific term for the process of drawing blood for antibody testing. By searching for the presence of antibodies in the blood of humans and animals, scientists have a greater chance of detecting viruses which started circulating recently.
Despite the controversy surrounding EcoHealth Alliance’s involvement in so-called gain of function research—experiments that study whether viruses might mutate into deadlier strains—the organization’s separate efforts to stay one step ahead of pathogen evolution are key to stopping the next pandemic.
“Having really cheap and fast surveillance is really important,” says Ross. “Particularly in a place where there's persistent, low level, moderate infections that potentially have the ability to develop into more epidemic or pandemic situations. It means there’s a pathway that something more dangerous can come through."
Scientists are searching for the presence of antibodies in the blood of humans and animals in hopes to detect viruses that recently started circulating.
EcoHealth Alliance
In Bangladesh, EcoHealth Alliance is attempting to do this using a newer serological technology known as a multiplex Luminex assay, which tests samples against a panel of known antibodies against many different viruses. It collects what Ross describes as a ‘footprint of information,’ which allows scientists to tell whether the sample contains the presence of a known pathogen or something completely different and needs to be investigated further.
By using this technology to sample human and animal populations across the country, they hope to gain an idea of whether there are any novel Nipah virus variants or strains from the same family, as well as other deadly viral families like Ebola.
This is just one of several novel tools being used for viral discovery in surveillance projects around the globe. Multiple research groups are taking PREDICT’s approach of looking for novel viruses in animals in various hotspots. They collect environmental DNA—mucus, faeces or shed skin left behind in soil, sediment or water—which can then be genetically sequenced.
Five years ago, this would have been a painstaking work requiring bringing collected samples back to labs. Today, thanks to the vast amounts of money spent on new technologies during COVID-19, researchers now have portable sequencing tools they can take out into the field.
Christopher Jerde, a researcher at the UC Santa Barbara Marine Science Institute, points to the Oxford Nanopore MinION sequencer as one example. “I tried one of the early versions of it four years ago, and it was miserable,” he says. “But they’ve really improved, and what we’re going to be able to do in the next five to ten years will be amazing. Instead of having to carefully transport samples back to the lab, we're going to have cigar box-shaped sequencers that we take into the field, plug into a laptop, and do the whole sequencing of an organism.”
In the past, viral surveillance has had to be very targeted and focused on known families of viruses, potentially missing new, previously unknown zoonotic pathogens. Jerde says that the rise of portable sequencers will lead to what he describes as “true surveillance.”
“Before, this was just too complex,” he says. “It had to be very focused, for example, looking for SARS-type viruses. Now we’re able to say, ‘Tell us all the viruses that are here?’ And this will give us true surveillance – we’ll be able to see the diversity of all the pathogens which are in these spots and have an understanding of which ones are coming into the population and causing damage.”
But being able to discover more viruses also comes with certain challenges. Some scientists fear that the speed of viral discovery will soon outpace the human capacity to analyze them all and assess the threat that they pose to us.
“I think we're already there,” says Jason Ladner, assistant professor at Northern Arizona University’s Pathogen and Microbiome Institute. “If you look at all the papers on the expanding RNA virus sphere, there are all of these deposited partial or complete viral sequences in groups that we just don't know anything really about yet.” Bats, for example, carry a myriad of viruses, whose ability to infect human cells we understand very poorly.
Cultivating these viruses under laboratory conditions and testing them on organoids— miniature, simplified versions of organs created from stem cells—can help with these assessments, but it is a slow and painstaking work. One hope is that in the future, machine learning could help automate this process. The new SpillOver Viral Risk Ranking platform aims to assess the risk level of a given virus based on 31 different metrics, while other computer models have tried to do the same based on the similarity of a virus’s genomic sequence to known zoonotic threats.
However, Ladner says that these types of comparisons are still overly simplistic. For one thing, scientists are still only aware of a few hundred zoonotic viruses, which is a very limited data sample for accurately assessing a novel pathogen. Instead, he says that there is a need for virologists to develop models which can determine viral compatibility with human cells, based on genomic data.
“One thing which is really useful, but can be challenging to do, is understand the cell surface receptors that a given virus might use,” he says. “Understanding whether a virus is likely to be able to use proteins on the surface of human cells to gain entry can be very informative.”
As the Earth’s climate heats up, scientists also need to better model the so-called vector borne diseases such as dengue, Zika, chikungunya and yellow fever. Transmitted by the Aedes mosquito residing in humid climates, these blights currently disproportionally affect people in low-income nations. But predictions suggest that as the planet warms and the pests find new homes, an estimated one billion people who currently don’t encounter them might be threatened by their bites by 2080. “When it comes to mosquito-borne diseases we have to worry about shifts in suitable habitat,” says Cat Lippi, a medical geography researcher at the University of Florida. “As climate patterns change on these big scales, we expect to see shifts in where people will be at risk for contracting these diseases.”
Public health practitioners and government decision-makers need tools to make climate-informed decisions about the evolving threat of different infectious diseases. Some projects are already underway. An ongoing collaboration between the Catalan Institution for Research and Advanced Studies and researchers in Brazil and Peru is utilizing drones and weather stations to collect data on how mosquitoes change their breeding patterns in response to climate shifts. This information will then be fed into computer algorithms to predict the impact of mosquito-borne illnesses on different regions.
The team at the Catalan Institution for Research and Advanced Studies is using drones and weather stations to collect data on how mosquito breeding patterns change due to climate shifts.
Gabriel Carrasco
Lippi says that similar models are urgently needed to predict how changing climate patterns affect respiratory, foodborne, waterborne and soilborne illnesses. The UK-based Wellcome Trust has allocated significant assets to fund such projects, which should allow scientists to monitor the impact of climate on a much broader range of infections. “There are a lot of different infectious agents that are sensitive to climate change that don't have these sorts of software tools being developed for them,” she says.
COVID-19’s havoc boosted funding for infectious disease research, but as its threats begin to fade from policymakers’ focus, the money may dry up. Meanwhile, scientists warn that another major infectious disease outbreak is inevitable, potentially within the next decade, so combing the planet for pathogens is vital. “Surveillance is ultimately a really boring thing that a lot of people don't want to put money into, until we have a wide scale pandemic,” Jerde says, but that vigilance is key to thwarting the next deadly horror. “It takes a lot of patience and perseverance to keep looking.”
This article originally appeared in One Health/One Planet, a single-issue magazine that explores how climate change and other environmental shifts are increasing vulnerabilities to infectious diseases by land and by sea. The magazine probes how scientists are making progress with leaders in other fields toward solutions that embrace diverse perspectives and the interconnectedness of all lifeforms and the planet.
[Editor's Note: This essay is in response to our current Big Question, which we posed to experts with different perspectives: "How should DNA tests for intelligence be used, if at all, by parents and educators?"]
It's 2019. Prenatal genetic tests are being used to help parents select from healthy and diseased eggs. Genetic risk profiles are being created for a range of common diseases. And embryonic gene editing has moved into the clinic. The science community is nearly unanimous on the question of whether we should be consulting our genomes as early as possible to create healthy offspring. If you can predict it, let's prevent it, and the sooner, the better.
There are big issues with IQ genetics that should be considered before parents and educators adopt DNA IQ predictions.
When it comes to care of our babies, kids, and future generations, we are doing things today that we never even dreamed would be possible. But one area that remains murky is the long fraught question of IQ, and whether to use DNA science to tell us something about it. There are big issues with IQ genetics that should be considered before parents and educators adopt DNA IQ predictions.
IQ tests have been around for over a century. They've been used by doctors, teachers, government officials, and a whole host of institutions as a proxy for intelligence, especially in youth. At times in history, test results have been used to determine whether to allow a person to procreate, remain a part of society, or merely stay alive. These abuses seem to be a distant part of our past, and IQ tests have since garnered their fair share of controversy for exhibiting racial and cultural biases. But they continue to be used across society. Indeed, much of the literature aimed at expecting parents justifies its recommendations (more omegas, less formula, etc.) based on promises of raising a baby's IQ.
This is the power of IQ testing sans DNA science. Until recently, the two were separate entities, with IQ tests indicating a coefficient created from individual responses to written questions and genetic tests indicating some disease susceptibility based on a sequence of one's DNA. Yet in recent years, scientists have begun to unlock the secrets of inherited aspects of intelligence with genetic analyses that scan millions of points of variation in DNA. Both bench scientists and direct-to-consumer companies have used these new technologies to find variants associated with exceptional IQ scores. There are a number of tests on the open market that parents and educators can use at will. These tests purport to reveal whether a child is inherently predisposed to be intelligent, and some suggest ways to track them for success.
I started looking into these tests when I was doing research for my book, "Social by Nature: The Promise and Peril of Sociogenomics." This book investigated the new genetic science of social phenomena, like educational attainment and political persuasion, investment strategies, and health habits. I learned that, while many of the scientists doing much of the basic research into these things cautioned that the effects of genetic factors were quite small, most saw testing as one data point among many that could help to somehow level the playing field for young people. The rationale went that in certain circumstances, some needed help more than others. Why not put our collective resources together to help them?
Good nutrition, support at home, and access to healthcare and education make a huge difference in how people do.
Some experts believed so strongly in the power of DNA behavioral prediction that they argued it would be unfair not to use predictors to determine a kid's future, prevent negative outcomes, and promote the possibility for positive ones. The educators out in the wider world that I spoke with agreed. With careful attention, they thought sociogenomic tests could help young people get the push they needed when they possessed DNA sequences that weren't working in their favor. Officials working with troubled youth told me they hoped DNA data could be marshaled early enough that kids would thrive at home and in school, thereby avoiding ending up in their care. While my conversations with folks centered around sociogenomic data in general, genetic IQ prediction was completely entangled in it all.
I present these prevailing views to demonstrate both the widespread appeal of genetic predictors as well as the well-meaning intentions of those in favor of using them. It's a truly progressive notion to help those who need help the most. But we must question whether genetic predictors are data points worth looking at.
When we examine the way DNA IQ predictors are generated, we see scientists grouping people with similar IQ test results and academic achievements, and then searching for the DNA those people have in common. But there's a lot more to scores and achievements than meets the eye. Good nutrition, support at home, and access to healthcare and education make a huge difference in how people do. Therefore, the first problem with using DNA IQ predictors is that the data points themselves may be compromised by numerous inaccuracies.
We must then ask ourselves where the deep, enduring inequities in our society are really coming from. A deluge of research has shown that poor life outcomes are a product of social inequalities, like toxic living conditions, underfunded schools, and unhealthy jobs. A wealth of research has also shown that race, gender, sexuality, and class heavily influence life outcomes in numerous ways. Parents and caregivers feed, talk, and play differently with babies of different genders. Teachers treat girls and boys, as well as members of different racial and ethnic backgrounds, differently to the point where they do better and worse in different subject areas.
Healthcare providers consistently racially profile, using diagnostics and prescribing therapies differently for the same health conditions. Access to good schools and healthcare are strongly mitigated by one's race and socioeconomic status. But even youth from privileged backgrounds suffer worse health and life outcomes when they identify or are identified as queer. These are but a few examples of the ways in which social inequities affect our chances in life. Therefore, the second problem with using DNA IQ predictors is that it obscures these very real, and frankly lethal, determinants. Instead of attending to the social environment, parents and educators take inborn genetics as the reason for a child's successes or failures.
It is time that we shift our priorities from seeking genetic causes to fixing the social causes we know to be real.
The other problem with using DNA IQ predictors is that research into the weightiness of DNA evidence has shown time and again that people take DNA evidence more seriously than they do other kinds of evidence. So it's not realistic to say that we can just consider IQ genetics as merely one tiny data point. People will always give more weight to DNA evidence than it deserves. And given its proven negligible effect, it would be irresponsible to do so.
It is time that we shift our priorities from seeking genetic causes to fixing the social causes we know to be real. Parents and educators need to be wary of solutions aimed at them and their individual children.
[Editor's Note: Read another perspective in the series here.]
You read an online article about climate change, then start scanning the comments on Facebook. Right on cue, Seth the Science Denier chimes in with:
The study found that science deniers whose arguments go unchallenged can harm other people's attitudes toward science.
"Humans didn't cause this. Climate is always changing. The earth has always had cycles of warming and cooling—what's happening now isn't new. The idea that humans are causing something that happened long before humans were even around is absurd."
You know he's wrong. You recognize the fallacy in his argument. Do you take the time to engage with him, or write him off and move along?
New research suggests that countering science deniers like Seth is important—not necessarily to change their minds, but to keep them from influencing others.
Looking at Seth's argument, someone without much of a science background might think it makes sense. After all, climate is always changing. The earth has always gone through cycles, even before humans. Without a scientifically sound response, a reader may begin to doubt that human-caused climate change is really a thing.
A study published in Nature found that science deniers whose arguments go unchallenged can harm other people's attitudes toward science. Many people read discussions without actively engaging themselves, and some may not recognize erroneous information when they see it. Without someone to point out how a denier's statements are false or misleading, people are more likely to be influenced by the denier's arguments.
Researchers tested two strategies for countering science denial—by topic (presenting the facts) and by technique (addressing the illogical argument). Rebutting a science denier with facts and pointing out the fallacies in their arguments both had a positive effect on audience attitudes toward legitimate science. A combination of topic and technique rebuttals also had a positive effect.
"In the light of these findings we recommend that advocates for science train in topic and technique rebuttal," the authors wrote. "Both strategies were equally effective in mitigating the influence of science deniers in public debates. Advocates can choose which strategy they prefer, depending on their levels of expertise and confidence."
Who you're really addressing are the lurkers who might be swayed by misinformation if it isn't countered by real science.
So what does that look like? If we were to counter Seth's statements with a topic rebuttal, focusing on facts, it might look something like this:
Yes, climate has always changed due to varying CO2 levels in the atmosphere. Scientists have tracked that data. But they also have data showing that human activity, such as burning fossil fuels, has dramatically increased CO2 levels. Climate change is now happening at a rate that isn't natural and is dangerous for life as we know it.
A technique rebuttal might focus on how Seth is using selective information and leaving out important facts:
Climate has always changed, that's true. But you've omitted important information about why it changes and what's different about the changes we're seeing now.
Ultimately, we could combine the two techniques in something like this:
Climate has always changed, but you've omitted important information about why it changes and what's different about what we're seeing now. Levels of CO2 in the atmosphere are largely what drives natural climate change, but human activity has increased CO2 beyond natural levels. That's making climate change happen faster than it should, with devastating effects for life on Earth.
Remember that the point is not to convince Seth, though it's great if that happens. Who you're really addressing are the lurkers who might be swayed by misinformation if it isn't countered by truth.
It's a wacky world out there, science lovers. Keep on fighting the good fight.