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Home > Global Health Matters Sep/Oct 2024 > Partnering with innovative modeling group extends Fogarty’s reach: Q&A with Kaiyuan Sun, PhD Print

Partnering with innovative modeling group extends Fogarty’s reach: Q&A with Kaiyuan Sun, PhD

September/October 2024 | Volume 23 Number 5

The photo on this page is a of Dr. Kaiyuan Sun, wearing a blue collared shirt and glasses. He is standing next to a plaque about Ellis McKenzie, the namesake of the library in the Stone House on the NIH CampusFogarty International CenterDr. Kaiyuan Sun is a research scientist in Fogarty’s Division of International Epidemiology and Population Studies (DIEPS)

Dr. Kaiyuan Sun earned a PhD in physics at Northeastern University. His dissertation focused on complex system modeling of infectious disease dynamics and his PhD advisor was Professor Alessandro Vespignani. He joined Fogarty in 2018 as a postdoctoral visiting fellow and has worked as an in-house research scientist in the Division of International Epidemiology and Population Studies (DIEPS) since 2021. He has studied pathogens that cause global public health emergencies, including Ebola, Zika and SARS-CoV-2, and is particularly interested in using mathematical models to translate findings of epidemiological studies into population-level impact and to inform public health decision-making.

Why focus on infectious disease modeling?

If you think about infectious disease, it's kind of like a perfect system to reflect biological complexity. There’s the human population (host) and a pathogen, and there’s this arms race between the two, right? The pathogen will infect us and then it will evolve to evade immunity and to find as many ways to infect as many hosts as possible. From the human perspective, we can mount an adaptive immune response to a pathogen, and that either lessens the severity of response to the pathogen (disease) or prevents infection altogether. Humans also have the advantage of the invention of vaccination, so we can start the arms race even before pathogens infect us!

It’s a very dynamic interaction and that's interesting to me. At the same time, infectious disease modeling and public health have practical applications. Having experienced the COVID-19 pandemic, I know this work has impact in the real world.

What are the findings from your recent Nature Medicine paper?

This study is unique because we’re looking at immunity induced by prior infections—not immunity induced by vaccines—and how that might protect us in the future. We're also using a “correlate of protection,” which is an immune biomarker that can reliably predict the extent of protective immunity. For example, seeing neutralizing antibodies in your blood indicates that you’ve already been exposed to an infection; and higher titers should mean better protection against a future infection.

We did this study when two variants—delta and omicron—were circulating in South Africa. So, we measured the neutralizing antibody titers prior to the delta wave and prior to the omicron wave and then we looked at how those titers potentially protected against reinfection. Our study confirms that neutralizing antibody titers correlate with protection against SARS-CoV-2, just as previous studies of vaccine-derived immunity showed.

The more interesting finding, however, is that the neutralizing antibody titer levels don't explain the majority of protection. For the delta wave, they explain just one third of the protection, while for the omicron wave, they explain even less: just 10%.

What does this mean?

This raises the question, What provides the remaining protection and what immune markers correlate with that? We need to look at other compartments of adaptive immunity and how they protect us against SARS-CoV-2 instead of focusing exclusively on neutralizing antibodies. For example, recent flu studies show immune markers like T cell responses or innate response correlate with protection independent of neutralizing antibodies.

Another direction of future research is mucosal immunity. A key difference between immunity from prior infections and immunity from vaccination is that, with a natural infection, the virus first infects the upper respiratory tract, so it's more likely to trigger localized immunity in the mucosal tissues. (By contrast, vaccines are administered intramuscularly and predominantly trigger a systemic immune response.) Localized immunities at the site of viral entry (the upper respiratory tract) may not correlate with systemic immunity levels measured in the blood and may play a more important role in protecting against infection and transmission. I want to understand this and to learn how to design a next-generation vaccine based on this knowledge.

What’s PHIRST? Why is it so special?

Our study of infection-induced immunity would not be possible without the groundbreaking design of PHIRST—the Prospective Household cohort study of Influenza, Respiratory Syncytial virus, and other respiratory pathogens community burden and Transmission dynamics in South Africa. The PHIRST studies are the genius of Dr. Cheryl Cohen's team at NICD (National Institute for Communicable Diseases), South Africa.

To understand the transmission of respiratory viruses, Cohen’s team set up cohorts of people who get twice weekly PCR testing for influenza and RSV, irrespective of symptoms. This high intensity approach captures the subclinical or asymptomatic infections that you won't see in a symptom-based testing scheme. In an early PHIRST study of influenza, Cohen’s team found that asymptomatic influenza infection and transmission are much more common than we previously thought. Their findings really changed our perspective on how influenza spreads. 

When the SARS-CoV-2 pandemic hit, they swiftly adapted their preestablished cohort infrastructure and protocol to create the PHIRST-C study (where “C” represents “COVID-19”).  We’ve collaborated prior to and throughout the pandemic and published a number of papers together, including the Nature Medicine paper.

What’s next for you?

A priority is to share my knowledge and expertise in mathematical modeling with my brilliant South Africa colleagues. I’m working closely with Dr. Jackie Kleynhans, a scientist on the PHIRST team, to model the impact of influenza vaccine and the potential impact of introducing pediatric vaccines to reduce influenza transmission. Despite this being her first modeling project, Jackie spearheaded the development of a detailed influenza transmission model that takes full advantage of the rich evidence generated by PHIRST. She’s also laid the groundwork for vaccine trial planning and potential policy implementations.

As an infectious disease modeler, I’m grateful for the opportunity to find answers to important scientific questions by developing novel modeling methods and analytical frameworks tailored to the PHIRST design. What’s even more fulfilling, though, is training the next generation of infectious disease modelers in South Africa.

Want to share any lessons learned?

Talk to people who are not in your field and try to establish interdisciplinary interactions. I’ve learned the most by not staying within my comfort zone.  Interacting with scientists from other disciplines allows us to gain new perspectives, generate fresh ideas, integrate our knowledge and expertise, and collaborate as a team to push the boundaries of our fields.

More Information

Updated October 2, 2024


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