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.
Can blockchain help solve the Henrietta Lacks problem?
Science has come a long way since Henrietta Lacks, a Black woman from Baltimore, succumbed to cervical cancer at age 31 in 1951 -- only eight months after her diagnosis. Since then, research involving her cancer cells has advanced scientific understanding of the human papilloma virus, polio vaccines, medications for HIV/AIDS and in vitro fertilization.
Today, the World Health Organization reports that those cells are essential in mounting a COVID-19 response. But they were commercialized without the awareness or permission of Lacks or her family, who have filed a lawsuit against a biotech company for profiting from these “HeLa” cells.
While obtaining an individual's informed consent has become standard procedure before the use of tissues in medical research, many patients still don’t know what happens to their samples. Now, a new phone-based app is aiming to change that.
Tissue donors can track what scientists do with their samples while safeguarding privacy, through a pilot program initiated in October by researchers at the Johns Hopkins Berman Institute of Bioethics and the University of Pittsburgh’s Institute for Precision Medicine. The program uses blockchain technology to offer patients this opportunity through the University of Pittsburgh's Breast Disease Research Repository, while assuring that their identities remain anonymous to investigators.
A blockchain is a digital, tamper-proof ledger of transactions duplicated and distributed across a computer system network. Whenever a transaction occurs with a patient’s sample, multiple stakeholders can track it while the owner’s identity remains encrypted. Special certificates called “nonfungible tokens,” or NFTs, represent patients’ unique samples on a trusted and widely used blockchain that reinforces transparency.
Blockchain could be used to notify people if cancer researchers discover that they have certain risk factors.
“Healthcare is very data rich, but control of that data often does not lie with the patient,” said Julius Bogdan, vice president of analytics for North America at the Healthcare Information and Management Systems Society (HIMSS), a Chicago-based global technology nonprofit. “NFTs allow for the encapsulation of a patient’s data in a digital asset controlled by the patient.” He added that this technology enables a more secure and informed method of participating in clinical and research trials.
Without this technology, de-identification of patients’ samples during biomedical research had the unintended consequence of preventing them from discovering what researchers find -- even if that data could benefit their health. A solution was urgently needed, said Marielle Gross, assistant professor of obstetrics, gynecology and reproductive science and bioethics at the University of Pittsburgh School of Medicine.
“A researcher can learn something from your bio samples or medical records that could be life-saving information for you, and they have no way to let you or your doctor know,” said Gross, who is also an affiliate assistant professor at the Berman Institute. “There’s no good reason for that to stay the way that it is.”
For instance, blockchain could be used to notify people if cancer researchers discover that they have certain risk factors. Gross estimated that less than half of breast cancer patients are tested for mutations in BRCA1 and BRCA2 — tumor suppressor genes that are important in combating cancer. With normal function, these genes help prevent breast, ovarian and other cells from proliferating in an uncontrolled manner. If researchers find mutations, it’s relevant for a patient’s and family’s follow-up care — and that’s a prime example of how this newly designed app could play a life-saving role, she said.
Liz Burton was one of the first patients at the University of Pittsburgh to opt for the app -- called de-bi, which is short for decentralized biobank -- before undergoing a mastectomy for early-stage breast cancer in November, after it was diagnosed on a routine mammogram. She often takes part in medical research and looks forward to tracking her tissues.
“Anytime there’s a scientific experiment or study, I’m quick to participate -- to advance my own wellness as well as knowledge in general,” said Burton, 49, a life insurance service representative who lives in Carnegie, Pa. “It’s my way of contributing.”
Liz Burton was one of the first patients at the University of Pittsburgh to opt for the app before undergoing a mastectomy for early-stage breast cancer.
Liz Burton
The pilot program raises the issue of what investigators may owe study participants, especially since certain populations, such as Black and indigenous peoples, historically were not treated in an ethical manner for scientific purposes. “It’s a truly laudable effort,” Tamar Schiff, a postdoctoral fellow in medical ethics at New York University’s Grossman School of Medicine, said of the endeavor. “Research participants are beautifully altruistic.”
Lauren Sankary, a bioethicist and associate director of the neuroethics program at Cleveland Clinic, agrees that the pilot program provides increased transparency for study participants regarding how scientists use their tissues while acknowledging individuals’ contributions to research.
However, she added, “it may require researchers to develop a process for ongoing communication to be responsive to additional input from research participants.”
Peter H. Schwartz, professor of medicine and director of Indiana University’s Center for Bioethics in Indianapolis, said the program is promising, but he wonders what will happen if a patient has concerns about a particular research project involving their tissues.
“I can imagine a situation where a patient objects to their sample being used for some disease they’ve never heard about, or which carries some kind of stigma like a mental illness,” Schwartz said, noting that researchers would have to evaluate how to react. “There’s no simple answer to those questions, but the technology has to be assessed with an eye to the problems it could raise.”
To truly make a difference, blockchain must enable broad consent from patients, not just de-identification.
As a result, researchers may need to factor in how much information to share with patients and how to explain it, Schiff said. There are also concerns that in tracking their samples, patients could tell others what they learned before researchers are ready to publicly release this information. However, Bogdan, the vice president of the HIMSS nonprofit, believes only a minimal study identifier would be stored in an NFT, not patient data, research results or any type of proprietary trial information.
Some patients may be confused by blockchain and reluctant to embrace it. “The complexity of NFTs may prevent the average citizen from capitalizing on their potential or vendors willing to participate in the blockchain network,” Bogdan said. “Blockchain technology is also quite costly in terms of computational power and energy consumption, contributing to greenhouse gas emissions and climate change.”
In addition, this nascent, groundbreaking technology is immature and vulnerable to data security flaws, disputes over intellectual property rights and privacy issues, though it does offer baseline protections to maintain confidentiality. To truly make a difference, blockchain must enable broad consent from patients, not just de-identification, said Robyn Shapiro, a bioethicist and founding attorney at Health Sciences Law Group near Milwaukee.
The Henrietta Lacks story is a prime example, Shapiro noted. During her treatment for cervical cancer at Johns Hopkins, Lacks’s tissue was de-identified (albeit not entirely, because her cell line, HeLa, bore her initials). After her death, those cells were replicated and distributed for important and lucrative research and product development purposes without her knowledge or consent.
Nonetheless, Shapiro thinks that the initiative by the University of Pittsburgh and Johns Hopkins has potential to solve some ethical challenges involved in research use of biospecimens. “Compared to the system that allowed Lacks’s cells to be used without her permission, Shapiro said, “blockchain technology using nonfungible tokens that allow patients to follow their samples may enhance transparency, accountability and respect for persons who contribute their tissue and clinical data for research.”
Read more about laws that have prevented people from the rights to their own cells.
New tech for prison reform spreads to 11 states
A new non-profit called Recidiviz is using data technology to reduce the size of the U.S. criminal justice system. The bi-coastal company (SF and NYC) is currently working with 11 states to improve their systems and, so far, has helped remove nearly 69,000 people — ones left floundering in jail or on parole when they should have been released.
“The root cause is fragmentation,” says Clementine Jacoby, 31, a software engineer who worked at Google before co-founding Recidiviz in 2019. In the 1970s and 80s, the U.S. built a series of disconnected data systems, and this patchwork is still being used by criminal justice authorities today. It requires parole officers to manually calculate release dates, leading to errors in many cases. “[They] have done everything they need to do to earn their release, but they're still stuck in the system,” Jacoby says.
Recidiviz has built a platform that connects the different databases, with the goal of identifying people who are already qualified for release but remain behind bars or on supervision. “Think of Recidiviz like Google Maps,” says Jacoby, who worked on Maps when she was at the tech giant. Google Maps takes in data from different sources – satellite images, street maps, local business data — and organizes it into one easy view. “Recidiviz does something similar with criminal justice data,” Jacoby explains, “making it easy to identify people eligible to come home or to move to less intensive levels of supervision.”
People like Jacoby’s uncle. His experience with incarceration is what inspired her passion for criminal justice reform in the first place.
The problems are vast
The U.S. has the highest incarceration rate in the world — 2 million people according to the watchdog group, Prison Policy Initiative — at a cost of $182 billion a year. The numbers could be a lot lower if not for an array of problems including inaccurate sentencing calculations, flawed algorithms and parole violations laws.
Sentencing miscalculations
To determine eligibility for release, the current system requires corrections officers to check 21 different requirements spread across five different databases for each of the 90 to 100 people under their supervision. These manual calculations are time prohibitive, says Jacoby, and fall victim to human error.
In addition, Recidiviz found that policies aimed at helping to reduce the prison population don’t always work correctly. A key example is time off for good behavior laws that allow inmates to earn one day off for every 30 days of good behavior. Some states' data systems are built to calculate time off as one day per month of good behavior, rather than per day. Over the course of a decade-long sentence, Jacoby says these miscalculations can lead to a huge discrepancy in the calculated release data and the actual release date.
Algorithms
Commercial algorithm-based software systems for risk assessment continue to be widely used in the criminal justice system, even though a 2018 study published in Science Advances exposed their limitations. After the study went viral, it took three years for the Justice Department to issue a report on their own flawed algorithms used to reduce the federal prison population as part of the 2018 First Step Act. The program, it was determined, overestimated the risk of putting inmates of color into early-release programs.
Despite its name, Recidiviz does not build these types of algorithms for predicting recidivism, or whether someone will commit another crime after being released from prison. Rather, Jacoby says the company’s "descriptive analytics” approach is specifically intended to weed out incarceration inequalities and avoid algorithmic pitfalls.
Parole violation laws
Research shows that 350,000 people a year — about a quarter of the total prison population — are sent back not because they’ve committed another crime, but because they’ve broken a specific rule of their probation. “Things that wouldn't send you or I to prison, but would send someone on parole,” such as crossing county lines or being in the presence of alcohol when they shouldn’t be, are inflating the prison population, says Jacoby.
It’s personal for the co-founder and CEO
“I grew up with an uncle who went into the prison system,” Jacoby says. At 19, he was sentenced to ten years in prison for a non-violent crime. A few months after being released from jail, he was sent back for a non-violent parole violation.
“For my family, the fact that one in four prison admissions are driven not by a crime but by someone who's broken a rule on probation and parole was really profound because that happened to my uncle,” Jacoby says. The experience led her to begin studying criminal justice in high school, then college. She continued her dive into how the criminal justice system works as part of her Passion Project while at Google, a program that allows employees to spend 20 percent of their time on pro-bono work. Two colleagues whose family members had also been stuck in the system joined her.
As part of the project, Jacoby interviewed hundreds of people involved in the criminal justice system. “Those on the right, those on the left, agreed that bad data was slowing down reform,” she says. Their research brought them to North Dakota where they began to understand the root of the problem. The corrections department is making “huge, consequential decisions every day [without] … the data,” Jacoby says. In a new video by Recidiviz not yet released, Jacoby recounts her exchange with the state’s director of corrections who told her, “‘It’s not that we have the data and we just don’t know how to make it public; we don’t have the information you think we have.'"
A mock-up (with fake data) of the types of dashboards and insights that Recidiviz provides to state governments.
Recidiviz
As a software engineer, Jacoby says the comment made no sense to her — until she witnessed it first-hand. “We spent a lot of time driving around in cars with corrections directors and parole officers watching them use these incredibly taxing, frankly terrible, old data systems,” Jacoby says.
As they weeded through thousands of files — some computerized, some on paper — they unearthed the consequences of bad data: Hundreds of people in prison well past their release date and thousands more whose release from parole was delayed because of minor paperwork issues. They found individuals stuck in parole because they hadn’t checked one last item off their eligibility list — like simply failing to provide their parole officer with a paystub. And, even when parolees advocated for themselves, the archaic system made it difficult for their parole officers to confirm their eligibility, so they remained in the system. Jacoby and her team also unpacked specific policies that drive racial disparities — such as fines and fees.
The Solution
It’s more than a trivial technical challenge to bring the incomplete, fragmented data onto a 21st century data platform. It takes months for Recidiviz to sift through a state’s information systems to connect databases “with the goal of tracking a person all the way through their journey and find out what’s working for 18- to 25-year-old men, what’s working for new mothers,” explains Jacoby in the video.
TED Talk: How bad data traps people in the U.S. justice system
TED Fellow Clementine Jacoby's TED Talk went live on Jan. 13. It describes how we can fix bad data in the criminal justice system, "bringing thousands of people home, reducing costs and improving public safety along the way."
Clementine Jacoby • TED2022
Ojmarrh Mitchell, an associate professor in the School of Criminology and Criminal Justice at Arizona State University, who is not involved with the company, says what Recidiviz is doing is “remarkable.” His perspective goes beyond academic analysis. In his pre-academic years, Mitchell was a probation officer, working within the framework of the “well known, but invisible” information sharing issues that plague criminal justice departments. The flexibility of Recidiviz’s approach is what makes it especially innovative, he says. “They identify the specific gaps in each jurisdiction and tailor a solution for that jurisdiction.”
On the downside, the process used by Recidiviz is “a bit opaque,” Mitchell says, with few details available on how Recidiviz designs its tools and tracks outcomes. By sharing more information about how its actions lead to progress in a given jurisdiction, Recidiviz could help reformers in other places figure out which programs have the best potential to work well.
The eleven states in which Recidiviz is working include California, Colorado, Maine, Michigan, Missouri, Pennsylvania and Tennessee. And a pilot program launched last year in Idaho, if scaled nationally, with could reduce the number of people in the criminal justice system by a quarter of a million people, Jacoby says. As part of the pilot, rather than relying on manual calculations, Recidiviz is equipping leaders and the probation officers with actionable information with a few clicks of an app that Recidiviz built.
Mitchell is disappointed that there’s even the need for Recidiviz. “This is a problem that government agencies have a responsibility to address,” he says. “But they haven’t.” For one company to come along and fill such a large gap is “remarkable.”