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.
7 Reasons Why We Should Not Need Boosters for COVID-19
There are at least 7 reasons why immunity after vaccination or infection with COVID-19 should likely be long-lived. If durable, I do not think boosters will be necessary in the future, despite CEOs of pharmaceutical companies (who stand to profit from boosters) messaging that they may and readying such boosters. To explain these reasons, let's orient ourselves to the main components of the immune system.
There are two major arms of the immune system: B cells (which produce antibodies) and T cells (which are formed specifically to attack and kill pathogens). T cells are divided into two types, CD4 cells ("helper" T cells) and CD8 cells ("cytotoxic" T cells).
Each arm, once stimulated by infection or vaccine, should hopefully make "memory" banks. So if the body sees the pathogen in the future, these defenses should come roaring back to attack the virus and protect you from getting sick. Plenty of research in COVID-19 indicates a likely long-lasting response to the vaccine or infection. Here are seven of the most compelling reasons:
REASON 1: Memory B Cells Are Produced By Vaccines and Natural Infection
In one study, 12 volunteers who had never had Covid-19--and were fully vaccinated with two Pfizer/BioNTech shots-- underwent biopsies of their lymph nodes. This is where memory B cells are stored in places called "germinal centers". The biopsies were performed three, four, six, and seven weeks after the first mRNA vaccine shot, and were stained to reveal that germinal center memory B cells in the lymph nodes increased in concentration over time.
Natural infection also generates memory B cells. Even after antibody levels wane over time, strong memory B cells were detected in the blood of individuals six and eight months after infection in different studies. Indeed, the half-lives of the memory B cells seen in the study examining patients 8 months after COVID-19 led the authors to conclude that "B cell memory to SARS-CoV-2 was robust and is likely long-lasting." Reason #2 tells us that memory B cells can be active for a very long time indeed.
REASON #2: Memory B Cells Can Produce Neutralizing Antibodies If They See Infection Again Decades Later
Demonstrated production of memory B cells after vaccination or natural infection with COVID-19 is so important because memory B cells, once generated, can be activated to produce high levels of neutralizing antibodies against the pathogen even if encountered many years after the initial exposure. In one amazing study (published in 2008), researchers isolated memory B cells against the 1918 flu strain from the blood of 32 individuals aged 91-101 years. These people had been born on or before 1915 and had survived that pandemic.
Their memory B cells, when exposed to the 1918 flu strain in a test tube, generated high levels of neutralizing antibodies against the virus -- antibodies that then protected mice from lethal infection with this deadly strain. The ability of memory B cells to produce complex antibody responses against an infection nine decades after exposure speaks to their durability.
REASON #3: Vaccines or Natural Infection Trigger Strong Memory T Cell Immunity
All of the trials of the major COVID-19 vaccine candidates measured strong T cell immunity following vaccination, most often assessed by measuring SARS-CoV-2 specific T cells in the phase I/II safety and immunogenicity studies. There are a number of studies that demonstrate the production of strong T cell immunity to COVID-19 after natural infection as well, even when the infection was mild or asymptomatic.
The same study that showed us robust memory B cell production 8 months after natural infection also demonstrated strong and sustained memory T cell production. In fact, the half-lives of the memory T cells in this cohort were long (~125-225 days for CD8+ and ~94-153 days for CD4+ T cells), comparable to the 123-day half-life observed for memory CD8+ T cells after yellow fever immunization (a vaccine usually given once over a lifetime).
A recent study of individuals recovered from COVID-19 show that the initial T cells generated by natural infection mature and differentiate over time into memory T cells that will be "put in the bank" for sustained periods.
REASON #4: T Cell Immunity Following Vaccinations for Other Infections Is Long-Lasting
Last year, we were fortunate to be able to measure how T cell immunity is generated by COVID-19 vaccines, which was not possible in earlier eras when vaccine trials were done for other infections (such as measles, mumps, rubella, pertussis, diphtheria). Antibodies are just the "tip of the iceberg" when assessing the response to vaccination, but were the only arm of the immune response that could be measured following vaccination in the past.
Measuring pathogen-specific T cell responses takes sophisticated technology. However, T cell responses, when assessed years after vaccination for other pathogens, has been shown to be long-lasting. For example, in one study of 56 volunteers who had undergone measles vaccination when they were much younger, strong CD8 and CD4 cell responses to vaccination could be detected up to 34 years later.
REASON #5: T Cell Immunity to Related Coronaviruses That Caused Severe Disease is Long-Lasting
SARS-CoV-2 is a coronavirus that causes severe disease, unlike coronaviruses that cause the common cold. Two other coronaviruses in the recent past caused severe disease, specifically Severely Acute Respiratory Distress Syndrome (SARS) in late 2002-2003 and Middle East Respiratory Syndrome (MERS) in 2011.
A study performed in 2020 demonstrated that the blood of 23 recovered SARS patients possess long-lasting memory T cells that were still reactive to SARS 17 years after the outbreak in 2003. Many scientists expect that T cell immunity to SARS-CoV-2 will be equally durable to that of its cousin.
REASON #6: T Cell Responses from Vaccination and Natural Infection With the Ancestral Strain of COVID-19 Are Robust Against Variants
Even though antibody responses from vaccination may be slightly lower against various COVID-19 variants of concern that have emerged in recent months, T cell immunity after vaccination has been shown to be unperturbed by mutations in the spike protein (in the variants). For instance, T cell responses after mRNA vaccines maintained strong activity against different variants (including P.1 Brazil variant, B.1.1.7 UK variant, B.1.351 South Africa variant and the CA.20.C California variant) in a recent study.
Another study showed that the vaccines generated robust T cell immunity that was unfazed by different variants, including B.1.351 and B.1.1.7. The CD4 and CD8 responses generated after natural infection are equally robust, showing activity against multiple "epitopes" (little segments) of the spike protein of the virus. For instance, CD8 cells responds to 52 epitopes and CD4 cells respond to 57 epitopes across the spike protein, so that a few mutations in the variants cannot knock out such a robust and in-breadth T cell response. Indeed, a recent paper showed that mRNA vaccines were 97.4 percent effective against severe COVID-19 disease in Qatar, even when the majority of circulating virus there was from variants of concern (B.1.351 and B.1.1.7).
REASON #7: Coronaviruses Don't Mutate Quickly Like Influenza, Which Requires Annual Booster Shots
Coronaviruses are RNA viruses, like influenza and HIV (which is actually a retrovirus), but do not mutate as quickly as either one. The reason that coronaviruses don't mutate very rapidly is that their replicating mechanism (polymerase) has a strong proofreading mechanism: If the virus mutates, it usually goes back and self-corrects. Mutations can arise with high rates of replication when transmission is very frequent -- as has been seen in recent months with the emergence of SARS-CoV-2 variants during surges. However, the COVID-19 virus will not be mutating like this when we tamp down transmission with mass vaccination.
In conclusion, I and many of my infectious disease colleagues expect the immunity from natural infection or vaccination to COVID-19 to be durable. Let's put discussion of boosters aside and work hard on global vaccine equity and distribution since the pandemic is not over until it is over for us all.
The "Making Sense of Science" podcast features interviews with leading medical and scientific experts about the latest developments and the big ethical and societal questions they raise. This monthly podcast is hosted by journalist Kira Peikoff, founding editor of the award-winning science outlet Leaps.org.
Hear the 30-second trailer:
Listen to the whole episode:
.
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.