A mosquito under the microscope.
The association between climate and infectious disease is poorly understood, says Irina Tezaur, a computational scientist at Sandia National Laboratories. “Correlations have been observed but it’s not known if these correlations translate to causal relationships.”
To make accurate longer-term predictions, scientists need more empirical data, multiple datasets specific to locations and diseases, and the ability to calculate risks that depend on unpredictable nature and human behavior. Another obstacle is that climate scientists and epidemiologists are not collaborating effectively, so some researchers are calling for a multidisciplinary approach, a new field called Outbreak Science.
Climate scientists are far ahead of epidemiologists in gathering essential data.
Earth System Models—combining the interactions of atmosphere, ocean, land, ice and biosphere—have been in place for two decades to monitor the effects of global climate change. These models must be combined with epidemiological and human model research, areas that are easily skewed by unpredictable elements, from extreme weather events to public environmental policy shifts.
“There is never just one driver in tracking the impact of climate on infectious disease,” says Joacim Rocklöv, a professor at the Heidelberg Institute of Global Health & Heidelberg Interdisciplinary Centre for Scientific Computing in Germany. Rocklöv has studied how climate affects vector-borne diseases—those transmitted to humans by mosquitoes, ticks or fleas. “You need to disentangle the variables to find out how much difference climate makes to the outcome and how much is other factors.” Determinants from deforestation to population density to lack of healthcare access influence the spread of disease.
Even though climate change is not the primary driver of infectious disease today, it poses a major threat to public health in the future, says Rocklöv.
The promise of predictive modeling
“Models are simplifications of a system we’re trying to understand,” says Jeremy Hess, who directs the Center for Health and the Global Environment at University of Washington in Seattle. “They’re tools for learning that improve over time with new observations.”
Accurate predictions depend on high-quality, long-term observational data but models must start with assumptions. “It’s not possible to apply an evidence-based approach for the next 40 years,” says Rocklöv. “Using models to experiment and learn is the only way to figure out what climate means for infectious disease. We collect data and analyze what already happened. What we do today will not make a difference for several decades.”
To improve accuracy, scientists develop and draw on thousands of models to cover as many scenarios as possible. One model may capture the dynamics of disease transmission while another focuses on immunity data or ocean influences or seasonal components of a virus. Further, each model needs to be disease-specific and often location-specific to be useful.
“All models have biases so it’s important to use a suite of models,” Tezaur stresses.
The modeling scientist chooses the drivers of change and parameters based on the question explored. The drivers could be increased precipitation, poverty or mosquito prevalence, for instance. Later, the scientist may need to isolate the effect of one driver so that will require another model.
There have been some related successes, such as the latest models for mosquito-borne diseases like Dengue, Zika and malaria as well as those for flu and tick-borne diseases, says Hess.
Rocklöv was part of a research team that used test data from 2018 and 2019 to identify regions at risk for West Nile virus outbreaks. Using AI, scientists were able to forecast outbreaks of the virus for the entire transmission season in Europe. “In the end, we want data-driven models; that’s what AI can accomplish,” says Rocklöv. Other researchers are making an important headway in creating a framework to predict novel host–parasite interactions.
Modeling studies can run months, years or decades. “The scientist is working with layers of data. The challenge is how to transform and couple different models together on a planetary scale,” says Jeanne Fair, a scientist at Los Alamos National Laboratory, Biosecurity and Public Health, in New Mexico.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts a tall spatial and temporal resolutions.
And it’s a constantly changing picture. A modeling study in an April 2022 issue of Nature predicted that thousands of animals will migrate to cooler locales as temperatures rise. This means that various species will come into closer contact with people and other mammals for the first time. This is likely to increase the risk of emerging infectious disease transmitted from animals to humans, especially in Africa and Asia.
Other things can happen too. Global warming could precipitate viral mutations or new infectious diseases that don’t respond to antimicrobial treatments. Insecticide-resistant mosquitoes could evolve. Weather-related food insecurity could increase malnutrition and weaken people’s immune systems. And the impact of an epidemic will be worse if it co-occurs during a heatwave, flood, or drought, says Hess.
The devil is in the climate variables
Solid predictions about the future of climate and disease are not possible with so many uncertainties. Difficult-to-measure drivers must be added to the empirical model mix, such as land and water use, ecosystem changes or the public’s willingness to accept a vaccine or practice social distancing. Nor is there any precedent for calculating the effect of climate changes that are accelerating at a faster speed than ever before.
The most critical climate variables thought to influence disease spread are temperature, precipitation, humidity, sunshine and wind, according to Tezaur’s research. And then there are variables within variables. Influenza scientists, for example, found that warm winters were predictors of the most severe flu seasons in the following year.
The human factor may be the most challenging determinant. To what degree will people curtail greenhouse gas emissions, if at all? The swift development of effective COVID-19 vaccines was a game-changer, but will scientists be able to repeat it during the next pandemic? Plus, no model could predict the amount of internet-fueled COVID-19 misinformation, Fair noted. To tackle this issue, infectious disease teams are looking to include more sociologists and political scientists in their modeling.
Addressing the gaps
Currently, researchers are focusing on the near future, predicting for next year, says Fair. “When it comes to long-term, that’s where we have the most work to do.” While scientists cannot foresee how political influences and misinformation spread will affect models, they are positioned to make headway in collecting and assessing new data streams that have never been merged.
Disease forecasting will require a significant investment into the infrastructure needed to collect data about the environment, vectors, and hosts at all spatial and temporal resolutions, Fair and her co-authors stated in their recent study. For example real-time data on mosquito prevalence and diversity in various settings and times is limited or non-existent. Fair also would like to see standards set in mosquito data collection in every country. “Standardizing across the US would be a huge accomplishment,” she says.
Understanding how climate change contributes to the spread of disease is critical for thwarting future calamities.
Jeanne Fair
Hess points to a dearth of data in local and regional datasets about how extreme weather events play out in different geographic locations. His research indicates that Africa and the Middle East experienced substantial climate shifts, for example, but are unrepresented in the evidentiary database, which limits conclusions. “A model for dengue may be good in Singapore but not necessarily in Port-au-Prince,” Hess explains. And, he adds, scientists need a way of evaluating models for how effective they are.
The hope, Rocklöv says, is that in the future we will have data-driven models rather than theoretical ones. In turn, sharper statistical analyses can inform resource allocation and intervention strategies to prevent outbreaks.
Most of all, experts emphasize that epidemiologists and climate scientists must stop working in silos. If scientists can successfully merge epidemiological data with climatic, biological, environmental, ecological and demographic data, they will make better predictions about complex disease patterns. Modeling “cross talk” and among disciplines and, in some cases, refusal to release data between countries is hindering discovery and advances.
It’s time for bold transdisciplinary action, says Hess. He points to initiatives that need funding in disease surveillance and control; developing and testing interventions; community education and social mobilization; decision-support analytics to predict when and where infections will emerge; advanced methodologies to improve modeling; training scientists in data management and integrated surveillance.
Establishing a new field of Outbreak Science to coordinate collaboration would accelerate progress. Investment in decision-support modeling tools for public health teams, policy makers, and other long-term planning stakeholders is imperative, too. We need to invest in programs that encourage people from climate modeling and epidemiology to work together in a cohesive fashion, says Tezaur. Joining forces is the only way to solve the formidable challenges ahead.
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.
Rodney Gorham, an Australian living with ALS, has reconnected with the world, thanks to a brain-machine interface called the Stentrode.
The brain-computer interface enabling this feat is called the Stentrode. It's the brainchild of Synchron, a company backed by Amazon’s Jeff Bezos and Microsoft cofounder Bill Gates. After Gorham’s neurologist recommended that he try it, he became one of the first volunteers to have an 8mm stent, laced with small electrodes, implanted into his jugular vein and guided by a surgeon into a blood vessel near the part of his brain that controls movement.
After arriving at their destination, these tiny sensors can detect neural activity. They relay these messages through a small receiver implanted under the skin to a computer, which then translates the information into words. This minimally invasive surgery takes a day and is painless, according to Gorham. Recovery time is typically short, about two days.
When a paralyzed patient thinks about trying to move their arms or legs, the motor cortex will fire patterns that are specific to the patient’s thoughts.
When a paralyzed patient such as Gorham thinks about trying to move their arms or legs, the motor cortex will fire patterns that are specific to the patient’s thoughts. This pattern is detected by the Stentrode and relayed to a computer that learns to associate this pattern with the patient’s physical movements. The computer recognizes thoughts about kicking, making a fist and other movements as signals for clicking a mouse or pushing certain letters on a keyboard. An additional eye-tracking device controls the movement of the computer cursor.
The process works on a letter by letter basis. That’s why longer and more nuanced responses often involve some trial and error. “I have been using this for about two years, and I enjoy the sessions,” Gorham typed during our chat session. Zafar Faraz, field clinical engineer at Synchron, sat next to Gorham, providing help when required. Gorham had suffered without internet access, but now he looks forward to surfing the web and playing video games.
Gorham, age 63, has been enjoying Stentrode sessions for about two years.
Rodeny Dekker
The BCI revolution
In the summer of 2021, Synchron became the first company to receive the FDA’s Investigational Device Exemption, which allows research trials on the Stentrode in human patients. This past summer, the company, together with scientists from Icahn School of Medicine at Mount Sinai and the Neurology and Neurosurgery Department at Utrecht University, published a paper offering a framework for how to develop BCIs for patients with severe paralysis – those who can't use their upper limbs to type or use digital devices.
Three months ago, Synchron announced the enrollment of six patients in a study called COMMAND based in the U.S. The company will seek approval next year from the FDA to make the Stentrode available for sale commercially. Meanwhile, other companies are making progress in the field of BCIs. In August, Neuralink announced a $280 million financing round, the biggest fundraiser yet in the field. Last December, Synchron announced a $75 million financing round. “One thing I can promise you, in five years from now, we’re not going to be where we are today. We're going to be in a very different place,” says Elad I. Levy, professor of neurosurgery and radiology at State University of New York in Buffalo.
The risk of hacking exists, always. Cybercriminals, for example, might steal sensitive personal data for financial reasons, blackmailing, or to spread malware to other connected devices while extremist groups could potentially hack BCIs to manipulate individuals into supporting their causes or carrying out actions on their behalf.
“The prospect of bestowing individuals with paralysis a renewed avenue for communication and motor functionality is a step forward in neurotech,” says Hayley Nelson, a neuroscientist and founder of The Academy of Cognitive and Behavioral Neuroscience. “It is an exciting breakthrough in a world of devastating, scary diseases,” says Neil McArthur, a professor of philosophy and director of the Centre for Professional and Applied Ethics at the University of Manitoba. “To connect with the world when you are trapped inside your body is incredible.”
While the benefits for the paraplegic community are promising, the Stentrode’s long-term effectiveness and overall impact needs more research on safety. “Potential risks like inflammation, damage to neural tissue, or unexpected shifts in synaptic transmission due to the implant warrant thorough exploration,” Nelson says.
There are also concens about data privacy concerns and the policies of companies to safeguard information processed through BCIs. “Often, Big Tech is ahead of the regulators because the latter didn’t envisage such a turn of events...and companies take advantage of the lack of legal framework to push forward,” McArthur says. Hacking is another risk. Cybercriminals could steal sensitive personal data for financial reasons, blackmailing, or to spread malware to other connected devices. Extremist groups could potentially hack BCIs to manipulate individuals into supporting their causes or carrying out actions on their behalf.
“We have to protect patient identity, patient safety and patient integrity,” Levy says. “In the same way that we protect our phones or computers from hackers, we have to stay ahead with anti-hacking software.” Even so, Levy thinks the anticipated benefits for the quadriplegic community outweigh the potential risks. “We are on the precipice of an amazing technology. In the future, we would be able to connect patients to peripheral devices that enhance their quality of life.”
In the near future, the Stentrode could enable patients to use the Stentrode to activate their wheelchairs, iPods or voice modulators. Synchron's focus is on using its BCI to help patients with significant mobility restrictions—not to enhance the lives of healthy people without any illnesses. Levy says we are not prepared for the implications of endowing people with superpowers.
I wondered what Gorham thought about that. “Pardon my question, but do you feel like you have sort of transcended human nature, being the first in a big line of cybernetic people doing marvelous things with their mind only?” was my last question to Gorham.
A slight smile formed on his lips. In less than a minute, he typed: “I do a little.”
XPRIZE founder and chairman Peter Diamandis launches XPRIZE Healthspan at an event on November 29.
In this competition, called XPRIZE Healthspan, multiple awards are available, depending on what’s achieved, with support from the nonprofit Hevolution Foundation and Chip Wilson, the founder of Lululemon and nonprofit SOLVE FSHD. The biggest prize, $81 million, is for improvements in cognition, muscle and immunity by 20 years. An improvement of 15 years will net $71 million, and 10 years will net $61 million.
In our conversation for this episode, Peter talks about his plans for XPRIZE Healthspan and why exponential technologies make the current era - even with all of its challenges - the most exciting time in human history. We discuss the best mental outlook that supports a person in becoming truly innovative, as well as the downsides of too much risk aversion. We talk about how to overcome the negativity bias in ourselves and in mainstream media, how Peter has shifted his own mindset to become more positive over the years, how to inspire a culture of innovation, Peter’s personal recommendations for lifestyle strategies to live longer and healthier, the innovations we can expect in various fields by 2030, the future of education and the importance of democratizing tech and innovation.
In addition to Peter’s pioneering leadership of XPRIZE, he is also the Executive Founder of Singularity University. In 2014, he was named by Fortune as one of the “World’s 50 Greatest Leaders.” As an entrepreneur, he’s started over 25 companies in the areas of health-tech, space, venture capital and education. He’s Co-founder and Vice-Chairman of two public companies, Celularity and Vaxxinity, plus being Co-founder & Chairman of Fountain Life, a fully-integrated platform delivering predictive, preventative, personalized and data-driven health. He also serves as Co-founder of BOLD Capital Partners, a venture fund with a half-billion dollars under management being invested in exponential technologies and longevity companies. Peter is a New York Times Bestselling author of four books, noted during our conversation and in the show notes of this episode. He has degrees in molecular genetics and aerospace engineering from MIT and holds an M.D. from Harvard Medical School.
Show links
- Peter Diamandis bio
- New XPRIZE Healthspan
- Peter Diamandis books
- 27 XPRIZE competitions and counting
- Life Force by Peter Diamandis and Tony Robbins
- Peter Diamandis Twitter
- Longevity Insider newsletter – AI identifies the news
- Peter Diamandis Longevity Handbook
- Hevolution funding for longevity
XPRIZE Founder Peter Diamandis speaks with Mehmoud Khan, CEO of Hevolution Foundation, at the launch of XPRIZE Healthspan.
Hevolution Foundation