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.
Have you felt a bit like an armchair epidemiologist lately? Maybe you've been poring over coronavirus statistics on your county health department's website or on the pages of your local newspaper.
If the percentage of positive tests steadily stays under 8 percent, that's generally a good sign.
You're likely to find numbers and charts but little guidance about how to interpret them, let alone use them to make day-to-day decisions about pandemic safety precautions.
Enter the gurus. We asked several experts to provide guidance for laypeople about how to navigate the numbers. Here's a look at several common COVID-19 statistics along with tips about how to understand them.
Case Counts: Consider the Context
The number of confirmed COVID-19 cases in American counties is widely available. Local and state health departments should provide them online, or you can easily look them up at The New York Times' coronavirus database. However, you need to be cautious about interpreting them.
"Case counts are the obvious numbers to look at. But they're probably the hardest thing to sort out," said Dr. Jeff Martin, an epidemiologist at the University of California at San Francisco.
That's because case counts by themselves aren't a good window into how the coronavirus is affecting your community since they rely on testing. And testing itself varies widely from day to day and community to community.
"The more testing that's done, the more infections you'll pick up," explained Dr. F. Perry Wilson, a physician at Yale University. The numbers can also be thrown off when tests are limited to certain groups of people.
"If the tests are being mostly given to people with a high probability of having been infected -- for example, they have had symptoms or work in a high-risk setting -- then we expect lots of the tests to be positive. But that doesn't tell us what proportion of the general public is likely to have been infected," said Eleanor Murray, an epidemiologist at Boston University.
These Stats Are More Meaningful
According to Dr. Wilson, it's more useful to keep two other statistics in mind: the number of COVID tests that are being performed in your community and the percentage that turn up positive, showing that people have the disease. (These numbers may or may not be available locally. Check the websites of your community's health department and local news media outlets.)
If the number of people being tested is going up, but the percentage of positive tests is going down, Dr. Wilson said, that's a good sign. But if both numbers are going up – the number of people tested and the percentage of positive results – then "that's a sign that there are more infections burning in the community."
It's especially worrisome if the percentage of positive cases is growing compared to previous days or weeks, he said. According to him, that's a warning of a "high-risk situation."
Dr. George Rutherford, an epidemiologist at University of California at San Francisco, offered this tip: If the percentage of positive tests steadily stays under 8 percent, that's generally a good sign.
There's one more caveat about case counts. It takes an average of a week for someone to be infected with COVID-19, develop symptoms, and get tested, Dr. Rutherford said. It can take an additional several days for those test results to be reported to the county health department. This means that case numbers don't represent infections happening right now, but instead are a picture of the state of the pandemic more than a week ago.
Hospitalizations: Focus on Current Statistics
You should be able to find numbers about how many people in your community are currently hospitalized – or have been hospitalized – with diagnoses of COVID-19. But experts say these numbers aren't especially revealing unless you're able to see the number of new hospitalizations over time and track whether they're rising or falling. This number often isn't publicly available, however.
If new hospitalizations are increasing, "you may want to react by being more careful yourself."
And there's an important caveat: "The problem with hospitalizations is that they do lag," UC San Francisco's Dr. Martin said, since it takes time for someone to become ill enough to need to be hospitalized. "They tell you how much virus was being transmitted in your community 2 or 2.5 weeks ago."
Also, he said, people should be cautious about comparing new hospitalization rates between communities unless they're adjusted to account for the number of more-vulnerable older people.
Still, if new hospitalizations are increasing, he said, "you may want to react by being more careful yourself."
Deaths: They're an Even More Delayed Headline
Cable news networks obsessively track the number of coronavirus deaths nationwide, and death counts for every county in the country are available online. Local health departments and media websites may provide charts tracking the growth in deaths over time in your community.
But while death rates offer insight into the disease's horrific toll, they're not useful as an instant snapshot of the pandemic in your community because severely ill patients are typically sick for weeks. Instead, think of them as a delayed headline.
"These numbers don't tell you what's happening today. They tell you how much virus was being transmitted 3-4 weeks ago," Dr. Martin said.
'Reproduction Value': It May Be Revealing
You're not likely to find an available "reproduction value" for your community, but it is available for your state and may be useful.
A reproduction value, also known as R0 or R-naught, "tells us how many people on average we expect will be infected from a single case if we don't take any measures to intervene and if no one has been infected before," said Boston University's Murray.
As The New York Times explained, "R0 is messier than it might look. It is built on hard science, forensic investigation, complex mathematical models — and often a good deal of guesswork. It can vary radically from place to place and day to day, pushed up or down by local conditions and human behavior."
It may be impossible to find the R0 for your community. However, a website created by data specialists is providing updated estimates of a related number -- effective reproduction number, or Rt – for each state. (The R0 refers to how infectious the disease is in general and if precautions aren't taken. The Rt measures its infectiousness at a specific time – the "t" in Rt.) The site is at rt.live.
"The main thing to look at is whether the number is bigger than 1, meaning the outbreak is currently growing in your area, or smaller than 1, meaning the outbreak is currently decreasing in your area," Murray said. "It's also important to remember that this number depends on the prevention measures your community is taking. If the Rt is estimated to be 0.9 in your area and you are currently under lockdown, then to keep it below 1 you may need to remain under lockdown. Relaxing the lockdown could mean that Rt increases above 1 again."
"Whether they're on the upswing or downswing, no state is safe enough to ignore the precautions about mask wearing and social distancing."
Keep in mind that you can still become infected even if an outbreak in your community appears to be slowing. Low risk doesn't mean no risk.
Putting It All Together: Why the Numbers Matter
So you've reviewed COVID-19 statistics in your community. Now what?
Dr. Wilson suggests using the data to remind yourself that the coronavirus pandemic "is still out there. You need to take it seriously and continue precautions," he said. "Whether they're on the upswing or downswing, no state is safe enough to ignore the precautions about mask wearing and social distancing. 'My state is doing well, no one I know is sick, is it time to have a dinner party?' No."
He also recommends that laypeople avoid tracking COVID-19 statistics every day. "Check in once a week or twice a month to see how things are going," he suggested. "Don't stress too much. Just let it remind you to put that mask on before you get out of your car [and are around others]."
GOOD10: The Pandemic Issue explores big-picture ways that science innovation and communication can usher in a more equitable, more progress-oriented, and safer world.
This issue is a collaboration among GOOD, leapsmag, and the Aspen Institute Science & Society Program.
The GOOD10 format explores fundamental issues facing humanity through the lenses of ten forces pushing the needle toward progress: Places, Philanthropists, Celebrities, Whistleblowers, Companies, Media, Products, Politicians, Scientists, and Actions. Across these categories, we seek to present unexpected and encouraging paradigms emerging from this historic crisis.
This special issue is available as an e-reader version for both desktop and mobile. It is also available as a free downloadable PDF.
TABLE OF CONTENTS:
- PLACES:
55 Lessons Learned About Science Communication Around the World; Quarantining Our Way Into Outer Space - PLACES:
Quarantining Our Way Into Outer Space - PHILANTHROPISTS:
An Exclusive Interview with Wendy Schmidt about Science in the Pandemic Era - CELEBRITIES:
Neil deGrasse Tyson Wants Celebrities to Promote Scientists - WHISTLEBLOWERS:
The Science Sleuths Holding Fraudulent Research Accountable - COMPANIES:
The Biggest Challenge for a COVID-19 Vaccine: Making It Accessible and Affordable - MEDIA:
Isaac Asimov on the History of Infectious Disease—And How Humanity Learned To Fight Back - PRODUCTS:
Will COVID-19 Pave the Way For DIY Precision Medicine? - POLITICIANS:
Will the Pandemic Propel STEM Experts to Political Power? - SCIENTISTS:
Would a Broad-Spectrum Antiviral Drug Stop the Pandemic? - ACTIONS:
Pseudoscience is Rampant: How Not to Fall For It - ACTIONS:
How COVID-19 Could Usher In a New Age of Collective Drug Discovery
THE EVENT:
"The Pandemic Science Summit" focused on how science innovation is key to society's future stability as we emerge from the pandemic, featuring:
Christopher Bailey – Arts and Health Lead, World Health Organization
Elisabeth Bik, Ph.D. – Microbiologist and scientific integrity consultant
Margaret Hamburg, M.D. – Foreign Secretary, National Academy of Medicine; former Commissioner, U.S. Food and Drug Administration
Peggy Oti-Boateng, Ph.D. – Director, Division of Science Policy and Capacity- Building, UNESCO
George Yancopoulos, M.D., Ph.D. – President and Chief Scientific Officer, Regeneron Pharmaceuticals
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.