Ivan Kairatov is a leading biopharma and public health expert with extensive experience in research and development, particularly focusing on how technological innovation can be leveraged to combat infectious diseases. With a career spanning over a decade, he has become a pivotal voice in the integration of high-tech modeling and grassroots field interventions to address complex health crises. His recent analysis of long-term epidemiological studies in China offers a profound look at the final stages of disease eradication, where traditional methods often falter.
The following discussion explores the nuanced transition from broad, village-level health strategies to hyper-localized, household-centered interventions. We delve into the persistent challenges of schistosomiasis, a parasitic infection affecting 200 million people globally, and examine why the last few cases are always the most difficult to resolve. By synthesizing data on agricultural practices, animal monitoring, and the rise of artificial intelligence in public health, this interview provides a roadmap for ending neglected tropical diseases.
Large-scale control programs often see diminishing returns as a disease reaches its final pockets. How does the transition to household-level monitoring change daily operations for field teams, and what specific metrics determine when a region is ready to shift toward this fine-scale surveillance?
When a region moves toward the “last mile” of elimination, the workload for field teams actually becomes more intense and personalized because the targets are no longer entire populations, but specific homes. Daily operations shift from mass drug administrations to “shoe-leather” epidemiology, where teams must conduct door-to-door environmental assessments and individual health surveys. We look for a tipping point where overall village infection rates are low, yet sporadic cases continue to appear in “hotspots” despite repeated interventions. In these scenarios, the metrics shift from broad prevalence percentages to household-specific indicators, such as the exact acreage of land a family manages or the presence of an improved toilet. This transition is essential because, as our 13-year study shows, the risk factors become highly localized, meaning a single household’s habits can sustain the parasite for an entire neighborhood.
Using human waste as fertilizer and maintaining vast rice fields can sustain parasitic hotspots even after decades of control. What are the economic hurdles of transitioning to safer farming practices, and how can local sanitation infrastructure be upgraded to effectively break the transmission cycle?
The economic hurdles are significant because traditional farming practices, such as using human waste as fertilizer, are deeply embedded in the rural economy as a low-cost, nutrient-rich solution. Transitioning to safer alternatives often requires a total overhaul of local infrastructure, moving away from simple pit latrines to “improved toilets” that properly sequester waste from the water supply. In the areas we studied in southwest China, the persistence of large rice-growing tracts creates a perfect environment for the parasite’s intermediate snail hosts, making it hard to decouple the local economy from the infection risk. Upgrading sanitation isn’t just about building toilets; it’s about ensuring that those facilities are integrated into a system that prevents runoff into the irrigation channels where people work daily. Breaking this cycle requires a heavy investment in modernizing agricultural inputs so that farmers don’t feel forced to rely on hazardous, traditional methods for their livelihoods.
Household factors like the presence of domestic animals and the lack of improved toilets have become critical predictors of infection in persistent hotspots. How do you coordinate the monitoring of cats and dogs within a human health framework, and what specific household-level interventions have proven most successful?
In the final stages of elimination, we must adopt a “One Health” framework that acknowledges that cats and dogs are not just pets, but potential reservoirs for the Schistosoma japonicum parasite. Coordinating this means that public health teams must now work alongside veterinary services to test and treat domestic animals simultaneously with their human owners. Our research highlighted that the ownership of these animals became a much more significant predictor of infection as human-to-human transmission declined. The most successful household-level interventions have been those that combine the installation of improved sanitation with targeted education on animal management. By ensuring that a family has a functional, modern toilet and that their domestic animals are regularly screened, we can effectively seal off the pathways the parasite uses to survive in these small, stubborn pockets.
Demographic data suggests that older adults increasingly represent the majority of new infections in regions near elimination. What social or environmental factors contribute to this age-related shift, and how must public health messaging change to engage seniors who may have lived with these risks for decades?
The shift toward older adults as the primary risk group is a reflection of changing demographics in rural areas, where younger generations often migrate to cities, leaving seniors to manage the labor-intensive farming tasks. These older individuals have often spent decades in the fields, and their risk is tied to a lifetime of environmental exposure and perhaps a lower perceived need to change habits that have been part of their daily lives for 50 years. Public health messaging must evolve from generic posters to culturally sensitive, direct engagement that respects their experience while explaining why the “old ways” are now the final barrier to a disease-free community. We need to focus on the sensory and physical benefits of elimination, such as reducing the anemia and fatigue that many seniors might mistakenly attribute simply to old age. It is about empowering them as the guardians of the family’s health rather than just treating them as patients.
AI algorithms can now analyze thousands of environmental and behavioral data points to predict infection patterns. In practical terms, how does this technology change the way fieldwork is conducted, and what are the primary challenges of integrating high-tech modeling with traditional, manual investigations?
AI has completely revolutionized our ability to prioritize where field teams spend their limited time and resources. Instead of checking every single village, we use algorithms to crunch thousands of data points—from satellite-derived environmental data to household survey results—to predict exactly which households are at the highest risk. This allows “shoe-leather” investigators to go directly to the most vulnerable spots with a level of precision that was impossible ten years ago. However, the primary challenge remains the “data gap” between sophisticated models and the messy reality of the field; an algorithm is only as good as the manual data fed into it. Integrating these requires a constant feedback loop where manual investigations validate the AI’s predictions, ensuring that the high-tech modeling actually reflects the lived reality of the farmers on the ground.
What is your forecast for the global elimination of schistosomiasis?
My forecast for the global elimination of schistosomiasis is one of cautious optimism, provided we can successfully pivot from mass-scale strategies to the hyper-local precision we have discussed. In the next decade, I expect several more regions in China and eventually other countries to reach “interruption of transmission” status by utilizing AI-driven surveillance and household-level sanitation upgrades. However, the real test will be in sub-Saharan Africa, where the scale of infection—currently affecting 200 million people—is much larger and the infrastructure is less developed. If we can apply these lessons of monitoring domestic animals and focusing on the “last mile” demographics, we could see a 70% to 80% reduction in global cases by 2035. The fight will not be won with a single vaccine or drug, but through the persistent, data-driven modernization of rural life and the unwavering commitment to treating every single household as a frontline in global health.
