Honorees announced for 2026 undergraduate research recognition awards

Xin Cen | How Local DNA Sequence Patterns Influence the Mutation Rate in Escherichia coli

Antibiotic resistance is a major population health challenge because resistant bacteria can spread rapidly across hospitals, communities, and global populations, limiting the effectiveness of treatments that modern medicine relies on. My research addresses this challenge by investigating the biological processes that generate antibiotic resistance in the first place. This project examines how small, random changes in bacterial DNA leads to resistance against rifampicin, an antibiotic used to treat serious infections. While resistance is often discussed in clinical or epidemiological terms, it ultimately arises from rare mutations within growing bacterial populations. By studying how frequently specific mutations occur—and why some occur more often than others—my work connects molecular biology with population-level health outcomes. Using many parallel bacterial populations and DNA sequencing, I measure how often individual DNA changes appear under identical conditions.

My findings suggest that the surrounding DNA sequence can strongly influence mutation rates, making certain sites more likely to generate resistance. This insight helps explain why resistance may emerge repeatedly and predictably in different populations exposed to the same antibiotic. Understanding the factors that shape mutation rates has important implications for population health. If resistance arises more readily at certain genetic sites, this knowledge can improve predictions of how quickly resistance will spread and inform strategies to slow its emergence. By clarifying the biological origins of antibiotic resistance, this research supports broader efforts in public health, medicine and policy to preserve the effectiveness of antibiotics and protect population health.

Suji Jang | From Personal to Proxy Agency: The Transformation of Control and Resource Direction During Functional Changes

My project directly aligns with the Population Health Initiative’s mission by reconstructing an interdisciplinary model of health that bridges the Digital Humanities, historical epidemiology and social behavioral theory. Utilizing the extensive longitudinal diaries of Joseph Svoboda (Ottoman Baghdad), I analyzed his detailed health entries alongside his daily social interactions and network activity. This creates a unique dataset for examining the social determinants of health in a pre-industrial context.

Beyond descriptive data, this project investigates the mechanisms of resilience. Applying Bandura’s social cognitive theory to historical content analysis, I track how patients navigate “retrospective functional decline.” My preliminary findings reveal that as physical capacity diminishes, agency does not disappear; rather, it transforms into “proxy agency,” where patients delegate control to social networks to secure survival.

This historical case study is vital for modern population health, particularly in a post-COVID world. It demonstrates that health resilience is not merely an individual physical trait but a collective social process. By quantifying how “proxy agency” functions as a survival mechanism during acute crises, this research underscores the necessity of integrating social capital and community support systems into holistic public health strategies. It offers historical evidence that during periods of biological stress, the ability to mobilize a social network is as critical to population survival as clinical intervention.

Durva Patil | Functional Assembly of Split Protein Pairs via a Chemically Activated SpyLigation

My research aligns with the theme of population health by advancing technologies that improve the safety, precision, and scalability of next-generation biomedical interventions. As gene editing, engineered cell therapies, and synthetic biology platforms move closer to clinical translation, one of the central challenges is achieving reliable control over biological function without introducing unintended or irreversible consequences. Technologies that allow precise, externally triggered control of protein activity offer an important step toward safer therapeutic design, moving away from permanent gene therapies.

At a clinical scale, improved control over engineered proteins can reduce off-target effects, enhance treatment specificity and provide clinicians with greater temporal regulation over therapeutic activity. This level of control is most valuable in applications such as immunotherapy, regenerative medicine, and targeted gene regulation, where excessive or mistimed activation can lead to toxicity or diminished efficacy. By prioritizing safety and modularity, such platforms help bridge the gap between experimental innovation and real-world patient care.

From a population health perspective, technologies that are precise, programmable and broadly adaptable can increase the reliability and scalability of advanced therapies. More predictable systems reduce variability in patient outcomes and improve the feasibility of translating complex biological tools into standardized treatments. Ultimately, enabling safer and more controllable biomedical technologies supports equitable access to innovative therapies and contributes to improving health outcomes at scale across diverse patient populations.

Lauren Ellis | Utilizing Low-Gradient Magnetic Separation of Heterogenous Catalysts Comprised of Magnetic Nanoparticles for Liquid Phase Catalysis

My research aligns with the University of Washington Population Health Initiative’s vision of creating a world where all people can live healthier and more fulfilling lives by addressing environmental drivers of health through sustainable chemical engineering solutions. Plastic waste, fossil-intensive manufacturing and inefficient recycling systems contribute to pollution, climate change, and environmental degradation, all of which disproportionately affect community health outcomes. In the Rorrer lab, I investigate catalyst recoverability to enable scalable chemical recycling technologies of waste polyolefins into value-added hydrocarbons while reducing reliance on fossil resources. A major barrier to deploying these systems is coke accumulation on catalysts, which increases energy demand for regeneration, limiting the viability of low-carbon manufacturing pathways.

To address this challenge, I developed a magnetic separation imaging apparatus that is electrifiable as an alternative to filtration and centrifugation, both of which are mechanically intensive and contribute to process emissions. Because magnetic separation requires only electrical input, it is inherently compatible with renewable energy and supports the transition to cleaner industrial infrastructure. By correlating coke deposition with measurable change, my research establishes a non-destructive diagnostic framework capable of reducing material loss and preventing metal release into the environment.

Beyond technological innovation, this work advances strategies that reduce plastic accumulation in ecosystems, which is an environmental challenge that first motivated my academic trajectory. By integrating reaction engineering and separations, this work reduces hazardous exposures, supports healthier environments for pollution-burdened communities and advances population health at a systems level.

Leah Jamaleddine | Investigating the Association Between Sex Differences and Left Atrial Epicardial Adipose Tissue Using High-Resolution CMR Imaging

This project aligns strongly with the theme of population health because it examines how biological sex, aging, and hormonal transitions contribute to differential cardiovascular risk at the population level. Atrial fibrillation (AF) is a highly prevalent arrhythmia associated with substantial morbidity, mortality, and healthcare utilization. Identifying structural and inflammatory contributors, such as left atrial epicardial adipose tissue (LA EAT), provides insight into mechanisms that may explain observed disparities in AF risk between men and women, particularly post-menopausal women.

Population health emphasizes understanding patterns of disease distribution and determinants across defined groups. This study investigates whether sex-specific differences in LA EAT volume, potentially influenced by hormonal changes during menopause, contribute to increased AF risk in women. By integrating advanced cardiac MRI phenotyping with demographic data, the project moves beyond individual-level pathology to evaluate biologically and socially relevant risk stratifiers that affect broader populations.

Importantly, EAT represents a modifiable cardiometabolic substrate linked to inflammation and atrial remodeling. If increased LA EAT volume is confirmed as a sex-associated risk marker, findings could inform targeted screening, risk stratification and preventive interventions for higher-risk populations, particularly aging women. Such strategies may reduce AF incidence, procedural burden (e.g., ablation) and downstream complications like stroke and heart failure.

By identifying mechanisms underlying sex-based disparities in AF, this research contributes to more equitable, precision-informed prevention approaches, which are core goals of population health.

Charlotte Hsu | Elucidating the Relationship Between Macrocycle MDCK Permeability and Phase I Metabolism

This research aligns with population health by addressing a fundamental barrier in drug development that affects whether promising therapies can ultimately reach patients. Macrocyclic peptides represent a growing class of therapeutics with potential applications in cancer, infectious disease and chronic conditions driven by intracellular protein-protein interactions. However, many drug candidates fail during development due to poor oral absorption or rapid metabolic degradation, limiting their clinical usefulness and increasing healthcare costs.

By investigating the relationship between membrane permeability and metabolic stability, this project contributes to a deeper understanding of how molecular properties influence a drug’s ability to be safely and effectively delivered in the body. Improving oral drug-like properties is particularly relevant to population health, as orally available medications are generally more accessible, affordable and easier to administer than injectable therapies. This can increase treatment adherence, reduce reliance on clinical settings and improve health equity across diverse populations.

The interdisciplinary nature of this work integrates principles from biochemistry, pharmacokinetics, analytical chemistry and pharmaceutical sciences to address challenges that sit at the interface of basic science and public health impact. The findings from this research may inform the rational design of peptide-based therapeutics with improved stability and absorption, helping streamline drug development and reduce late-stage failure.

As an undergraduate researcher, I am contributing to foundational knowledge supporting the development of more effective and accessible therapies. By improving how drug candidates are designed and evaluated early in development, this research supports population health outcomes through safer, more reliable and more widely usable treatments.

Adarina Uthman, Basil Mayhan, Alastar Diem, Yonathan Dagnew | Student Experience of Structural Instability, University Support Systems, and Wellbeing

This research aligns with population health with its focus on how structural and institutional conditions influence mental well-being among the population of university students. Rather than focusing solely on individual psychological traits, this study assesses how systemic instability – financial strain, scheduling unpredictability, housing insecurity and intricate institutional processes – shapes anxiety, academic engagement and access to supportive resources.

Population health stresses the social and structural determinants that influence health outcomes across cohorts. University students represent a diverse cohort experiencing evolving socioeconomic pressures and institutional complexity. By synthesizing quantitative survey data with qualitative interviews this project identifies patterns of instability and assesses how institutional structures may either mitigate or exacerbate psychological stress.

More importantly, the study intentionally centers student perspectives for improving campus systems, highlighting potential structural interventions rather than individual-based coping strategies. Understanding how institutional environments influence mental health can inform policies that endorse stability, equity and accessible support services.

By situating student wellbeing within broader systemic contexts, this research contributes to interdisciplinary efforts to address mental health disparities and improve conditions that support thriving of educational communities.

Grace Jung | Implementation Barriers to Universal SEBMH Screening in Washington State Schools: Administrator Perspectives

In 2024, the Washington State Legislature directed the University of Washington School Mental Health Assessment, Research, and Training Center to conduct a landscape analysis on how universal social, emotional, behavioral, and mental health (SEBMH) screening data are collected and used in public schools. This work examines how universal SEBMH screening fits within multitiered systems of support and integrated student support frameworks, and it analyzes current statutes, school practices and implementation challenges. Universal SEBMH screening refers to the routine, proactive assessment of students’ social, emotional and behavioral strengths and risks to guide and identify students who may need additional services.

This project draws on that effort by analyzing listening session transcripts from the UW SMART Center to better understand how school- and district-level administrators experience the implementation of universal SEBMH screening in practice. Using qualitative content analysis, this study focuses on the concerns administrators raise and the recommendations they offer. Early patterns indicate recurring issues related to the need for additional counseling support for students, trauma-informed training, clinical support and stable district-level funding and infrastructure, as well as questions about data systems and policy alignment.

These challenges shape whether schools can provide consistent and equitable mental health support across communities, which makes this a population health issue rather than an individual one. By focusing on systems, policies and school capacity, this project connects education policy to youth mental health outcomes at scale and offers practical insight for strengthening sustainable and equitable school-based mental health supports across Washington State.

Victoria Lopez-Wilkerson | Equity in Emergency: Planning Community Resilience Hubs for Seattle’s Underserved Neighborhoods

My capstone project, Equity in Emergency: Planning Community Resilience Hubs for Seattle’s Underserved Neighborhoods, directly embodies the mission of population health by addressing the interconnected health and social determinants that shape well-being at the community level. Through my research question “How can Seattle map and design Community Resilience HUBs for multi-hazard risk neighborhoods?” I explore an innovative, systems-based approach to enhance health equity, resilience and disaster preparedness in communities that experience disproportionate vulnerabilities due to structural inequities.

Population health prioritizes the health outcomes of entire populations and emphasizes the social, economic, and environmental factors that impact those outcomes. In Seattle’s historically underserved neighborhoods, residents frequently face heightened exposure to hazards such as earthquakes, flooding and extreme heat, while also contending with barriers to essential services, healthcare access, and social support. My project integrates spatial analysis with community-centered design to identify where resilience hubs; localized resource centers offering emergency support, health services and social connectivity can most effectively reduce health disparities and improve collective capacity to respond to crises.

By centering historically marginalized voices and leveraging interdisciplinary methods from public health, urban planning and disaster management, this research not only identifies risk but also co-creates solutions that strengthen community health infrastructure. Ultimately, this work advances a population health framework by promoting equitable access to resources, fostering community resilience and addressing the upstream determinants that shape health outcomes across Seattle’s diverse neighborhoods.

Douglas Lin | EHR-JEPA: World Model of Health Trajectories

My research focuses on the construction of accurate digital twins for patient care. Such twins improve clinical outcomes by providing a sort of sandbox for clinicians to model the impact of different treatments on patient outcomes. Each twin representation generated by my model is customized for each patient, which enables significantly superior standards of care for patients that may have unique health challenges or rare conditions. JEPA models are unique in their ability to distill the most important features of a patient’s health from potentially unstructured input. They can thus make customized predictions for each patient, based on their unique health conditions and backgrounds.

JEPA models are also comparatively smaller than large language models, which allows them to potentially be hosted internally by hospitals. Locally hosting such models results in better control over sensitive patient information.

Widespread adoption of our model would enable population-wide improvement of healthcare outcomes through a better understanding of individual health backgrounds. Simple downstream fine-tuning tasks may also be able to extract more information from the learned digital twin representation, such as risk for re-hospitalization or hidden signs of diabetes and heart disease. A model that learns the dynamics of patient health could also detect signs that a doctor might miss within the vast amounts of data that describes someone’s health condition. This work lays the foundation for the creation of accurate digital twins with a JEPA style model that encodes the most important features of a patient’s health.

Haley Neumiller | Modeling Osteosarcoma Metastasis with 3D Fibrin

Osteosarcoma (OS) is the most prevalent bone cancer affecting children and adolescents. Metastatic disease, which occurs when OS cells spread and form new tumors, is associated with five-year survival rates below 30%. OS places heavy emotional and financial burdens on patients and their families, often requiring intensive treatments such as surgeries and chemotherapies. Despite decades of care, survival rates have remained largely unchanged because the mechanisms driving OS metastasis are still poorly understood. Progress in understanding OS metastasis is limited by the widespread use of two-dimensional cell culture models. These models fail to replicate the physical and biochemical features of the tumor microenvironment (TME) that influence tumor growth, drug resistance, and metastasis. Fibrin deposits are an early marker of poor prognosis, as blood clot formation can trap circulating tumor cells and facilitate spread. Anticoagulant drugs (warfarin) may improve patient survival by inhibiting fibrin formation, though testing this approach requires models that accurately mimic the TME.

This research addresses this gap by developing a tunable, three-dimensional (3D) fibrin hydrogel model. Utilizing this blood clot-like environment, we measure how OS cells survive and grow in different fibrin densities and examine how introducing warfarin with chemotherapy affects their response. Assessing cellular behavior and matrix properties reveals how the physical and biochemical features of the microenvironment shape OS progression and metastasis. By generating knowledge to inform more effective treatments and establishing a physiologically relevant 3D model, this work advances population health goals by supporting future efforts to improve survival for those affected by OS.

Hesham Katabi | IV-Safe: A Low-Cost Color-Changing Dressing for Early Detection of Peripheral IV Failure

Peripheral intravenous (PIV) catheters are among the most widely used medical devices in the world, touching nearly every hospitalized patient, yet their high failure rate represents a persistent and largely preventable population health problem. Nearly half of all PIVs infiltrate, and the consequences—tissue injury, infection risk, pain, prolonged hospitalization, additional procedures and increased healthcare costs—are not borne equally across populations. Neonates, older adults, and patients in under-resourced hospitals or low nurse-to-patient ratio settings are disproportionately affected because timely detection depends on frequent visual monitoring that is difficult to maintain in high-burden environments.

Our IV-Safe project directly addresses this gap by developing a low-cost, passive and scalable technology that shifts the burden of detection away from constant clinician surveillance and toward an automatic visual alert system embedded in standard care. By integrating mechanochromic and leakage-responsive sensing into a routine IV dressing, IV-Safe enables earlier recognition of infiltration at the point of care without requiring electricity, electronics or additional training, features that are critical for implementation in resource-limited settings. This work aligns with population health by prioritizing patient safety, reducing preventable harm, decreasing downstream healthcare utilization and promoting more equitable care delivery across diverse clinical environments. If successful, IV-Safe has the potential to improve outcomes for millions of patients annually while supporting overextended healthcare systems through a simple, affordable and widely deployable intervention.

Vanshika Sindhu | Spatial Metabolomic Profiling Reveals Pregnancy-Specific Responses to Influenza A Virus Infection

Pregnant individuals consistently experience more severe influenza outcomes, yet the biological basis for this disparity remains incompletely understood. This knowledge gap represents a critical population health challenge, as pregnancy-associated vulnerability contributes to preventable maternal morbidity, adverse birth outcomes and strain on healthcare systems during seasonal epidemics and pandemics.

My research addresses this disparity by investigating how pregnancy alters host responses to influenza infection at the tissue level. By identifying pregnancy-specific metabolic and lipid pathway disruptions in the lung, this work provides mechanistic insight into why respiratory viral infections can become disproportionately severe during pregnancy. Understanding these pathways is essential for improving risk prediction, guiding therapeutic development and informing vaccination and treatment strategies tailored to pregnant populations. Rather than treating pregnancy as a generalized risk factor, this research helps define the biological processes that underlie that risk.

This project reflects the core principles of the Population Health Initiative by focusing on a vulnerable population, integrating interdisciplinary approaches across virology, immunology, reproductive biology and metabolomics, and generating knowledge that can inform clinical and public health decision-making. Strengthening our understanding of pregnancy-specific disease mechanisms ultimately supports more equitable healthcare strategies and improves outcomes for both pregnant individuals and their infants at the population level.

Kenna Samples | The Role of ATG4A in Sickle Cell Disease

Sickle cell disease (SCD) affects millions of people worldwide, with mainly sub-Saharan Africa, India, and the Caribbean bearing the burden of disease. Paradoxically, interventions and funding are most resourceful in North America, Europe, and the Middle East (Piel, 2024). Current treatment pathways either require lifelong hydroxyurea usage, which works by reactivating fetal hemoglobin (HbF), or curative gene therapies, which are widely inaccessible. Because the sickling of hemoglobin in red blood cells is caused by a mutation on β-globin gene that is upregulated after birth, finding novel pathways to reactivate HbF instead may improve anemia in SCD patients and increase accessible treatment options.

Our lab recently discovered that the loss of ATG4A, an autophagy protease, in human erythroid progenitors during the autophagy pathway results in the accumulation of fetal RNA binding proteins, LIN28B and IGF2BP1, and the reactivation of HbF. These findings suggest that targeting ATG4A and its increase in HbF production could have an effect on SCD.

My project aims to determine the contribution of Atg4a to SCD in vivo by crossing Atg4a-deficient mice with a murine model of SCD. Our results are anticipate that the loss of Atg4A will improve lower red blood cell counts, overall hemoglobin levels and vaso-occlusion from sickling. If erythroid-specific autophagy regulation is successful in mitigating SCD, it likely will reduce adverse events to other blood cells caused by hydroxyurea and expand the limited treatment options for patients with SCD, ultimately improving access and long-term health outcomes for populations shouldering the burden of disease.

Sophia Li | West Nile Virus Surveillance: Mosquito Abundance and Geographic Factors in Yakima County, Washington

West Nile Virus (WNV) is the leading cause of mosquito-borne disease in the United States, and poses significant risks to outdoor workers, the elderly and immunocompromised populations. Yakima County experiences elevated WNV risks, due to a unique intersection of environmental conditions, agricultural land use and socioeconomic factors. WNV is a zoonotic disease, which spreads between birds, animals, humans and horses.

This project applied the One Health framework to West Nile Virus Surveillance to account for environmental, animal and human connections. Traps were set along the Yakima River where bird migration paths, fishing ponds and mosquito populations intersect. Within Yakima County, agriculture is the leading industry, and the region is disproportionately impacted by environmental health disparities.

The WNV Surveillance Program is a collaboration with the Washington State Department of Health and Yakima Health District, focused on filling surveillance gaps in rural areas with high occupational exposures and recreational activity. Farm workers in the region face high occupational exposures. As climate change and rising temperatures increase viral replication within female Culex mosquitoes, early detection and prevention remain critical to keep communities safe.

By linking environmental, entomologic, avian and human health data, this research supports timely public health messaging and resource allocation to Granger and Sunnyside. Advancing interdisciplinary and preventive approaches reduces the burden of WNV, strengthens public health preparedness and helps create healthier communities across interconnected ecological systems.

Jack Nims, Immashiya Tanko | Are we missing people with diabetes? Diagnostic accuracy of HbA1c vs. the oral glucose tolerance test in Africa

Our research aligns closely with the theme of population health by addressing gaps in diabetes detection at the population level in African settings, where the burden of disease is rising rapidly and health system resources are often limited. Diabetes is a major contributor to morbidity and premature mortality worldwide, and in Africa nearly half of affected individuals remain undiagnosed, increasing the risk of preventable complications and widening health inequities. Accurate, accessible, and scalable diagnostic strategies are therefore essential for improving population health outcomes.

This study evaluates the diagnostic performance of haemoglobin A1c (HbA1c) compared with the oral glucose tolerance test (OGTT), the current reference standard, using a systematic review and meta-analysis of studies conducted in African adult populations. By synthesizing evidence across diverse settings, our research provides population-level estimates of sensitivity and specificity that are directly relevant to screening programs, surveillance efforts and national diagnostic guidelines. The findings highlight a critical trade-off between feasibility and accuracy: while HbA1c offers logistical advantages for large-scale screening, its limited sensitivity may lead to substantial under-diagnosis at the population level.

Importantly, this work situates diagnostic accuracy within broader population health considerations, including structural barriers to care, resource constraints and biological factors such as the high prevalence of haemoglobinopathies that may affect test performance. By identifying limitations of widely used diagnostic tools, our research informs evidence-based policy decisions and supports the development of context-appropriate strategies to improve early detection, reduce health disparities and strengthen diabetes prevention and management across populations.

Himathaarini Senthil | Improving Dendritic Cell Uptake of PLGA Nanoparticles Using PEI Surface Coating

Cancer continues to be a leading cause of death worldwide, and immunotherapies that stimulate the immune system to target tumor cells offer a promising alternative to traditional treatments such as chemotherapy and radiation. However, ensuring that dendritic cells efficiently uptake these immune stimulating drugs remains a significant challenge. Dendritic cells play a central role in activating T cells, which can then recognize and destroy tumor cells. Improving how these cells receive and process therapeutic signals could strengthen immune responses and lead to more effective treatments for large and diverse patient populations across the world.

My research in the Panyam Lab focuses on improving nanoparticle based cancer immunotherapies by enhancing drug uptake into dendritic cells. Polylactic-co-glycolic acid (PLGA) nanoparticles are commonly used as biodegradable drug carriers, but their uptake by dendritic cells can be limited. I am investigating whether coating PLGA nanoparticles with polyethylenimine (PEI), a positively charged polymer, can improve uptake through favorable electrostatic interactions with the negatively charged cell membrane.

The nanoparticles carry the TLR7/8 agonist imiquimod, an immune stimulating drug. By varying the amount of PEI, I study how surface charge affects uptake, drug loading and cytotoxicity. This work aims to identify an optimal balance between increased immune activation and human safety.

By improving the efficiency of immunotherapy delivery, this research could help reduce required drug dosages, minimize side effects, and lower treatment costs. Ultimately, these advances may contribute to more accessible and effective cancer treatments, reducing the overall burden of cancer on patients and healthcare systems worldwide.

Shaan Chetanwala | Investigating the Role of Age-Related Mitochondrial Dysfunction in Primary Aortic Smooth Muscle Cell Mechanobiology Utilizing a 3D-Engineered Tissue Model

Cardiovascular disease remains the leading cause of death worldwide, and age-related vascular dysfunction is a major contributor to this burden. My research investigates the behavior of aortic smooth muscle cells (ASMCs), which play a critical role in maintaining vascular integrity and function. Dysregulation of these cells contributes to arterial stiffening, aneurysm formation and other pathologies that disproportionately affect aging populations. By developing three-dimensional collagen-based constructs containing ASMCs, I aim to model the structural and mechanical environment of the aortic wall more accurately than traditional two-dimensional systems allow.

This biomimetic platform enables longitudinal imaging of cell activity, morphology and contractile behavior within a physiologically relevant extracellular matrix. Understanding how ASMCs respond to their microenvironment provides insight into early cellular mechanisms underlying vascular remodeling and degeneration. Because vascular aging is influenced by both biological processes and broader demographic trends, identifying these mechanisms is essential for improving prevention and treatment strategies at the population level.

Population health emphasizes not only clinical care but also upstream determinants of disease burden. By advancing foundational knowledge of vascular cell behavior in aging, this research contributes to the long-term goal of reducing cardiovascular morbidity and mortality. Improved mechanistic understanding may inform therapeutic development and ultimately support healthier aging across diverse populations.

Vishya Adipudi, Shripad Guntur | Developing a machine/deep learning MRI-based tool for disease quantification and monitoring in CNO

Children affected by rare diseases, including chronic nonbacterial osteomyelitis (CNO), suffer from years of diagnostic confusion and fragmented care, which exacerbates their pain and symptoms. Limited availability of pediatric subspecialty clinicians further compounds with existing disparities between socioeconomic status, geographic location, and race. Improving the timeliness and consistency of care to children with rare diseases should be a leading population health objective.

Patients seen through our program often travel to Seattle from rural locations throughout the WWAMI region because nearby community health systems do not provide access to subspecialty care. To reduce the barrier to care for patients with CNO and other rare diseases, our computational machine learning strategy will provide automated MRI-related diagnostic capabilities for evaluating the nature of the patient’s condition, resulting in improved and standardized disease evaluations without depending on expert practitioners who may not have resources in the respective health system. Enhancing access to expert-level diagnosis will allow for earlier and more effective identification of children with CNO.

We are also leveraging the integration of clinical and imaging datasets to create algorithms that can predict a favorable treatment response through a personalized medicine approach. Decreasing the amount of trial-and-error before reaching proper treatment will result in reduced suffering by patients and a reduction in total healthcare costs.

Our work is intended to address existing structural inefficiencies in rare disease management, improve equitable access to quality evaluation independent of a child’s geographic location and promote scalable, data-driven approaches to improve outcomes for children with rare diseases.

Laura Biassio | Agricultural Land and Ecosystem-Based Disaster Risk Reduction for Flooding in Rio Grande do Sul, Brazil

Climate-related flooding is an escalating public health threat that disrupts the physical, social, and environmental systems on which communities depend. Flooding events damage critical infrastructure that range from water supply, sanitation, transportation, food systems and health services, creating cascading health risks that extend far beyond the floodwaters themselves. In the Taquari River Valley, the floods of 2024 caused widespread displacement, infrastructure failure and exposure to hazards such as waterborne disease, injury, food insecurity and mental health stress that will last a lifetime. These impacts fall most heavily on rural and low-capacity communities, making flood mitigation a critical strategy for protecting population health and preventing social breakdown.

My research demonstrates how environmental planning can operate as preventive public health policy, offering scalable strategies for flood-prone regions facing climate-related health challenges. By integrating agricultural landscapes into ecosystem-based disaster risk reduction, it emphasizes interventions that reduce health harms before disasters occur, rather than relying solely on emergency response.

This project uses geographic information systems (GIS) to analyze flood hazard, land use, topography and riparian vegetation to identify locations where agroecological adaptations could reduce flood exposure for nearby populations. As mitigation strategies, they offer direct public health benefits as they aim to mitigate the general negative impacts of flooding events, which are known to be a long-term issue in the area. These feasible, nature-based land-use innovations make the valley more resilient, preventing avoidable harm and helping communities maintain stable, healthy living conditions even during extreme events.

Anna Fuss | Mathematical Models to Identify Mechanism and Potency of SARS-CoV-2 Therapeutic Monoclonal Antibodies

During the Covid-19 pandemic, antiviral drugs were critical in preventing hospitalizations and combatting viral spread. However, viral drugs were slow to reach clinical approval, being licensed a year after vaccines, limiting their efficacy and scope, and potentially leading to unnecessary hospitalizations and deaths nationwide. This issue is multifactorial; effective drugs were not tested efficiently, ineffective drugs were widely used despite lacking efficacy and clinical trials were performed on inappropriate, clinically ill, candidates, rather than patients at the start of infection.

By generating a mathematical model, we can streamline the drug development process, and fine tune the drugs entering clinical spaces, while expanding our understanding of drug function within our patients. This ensures that drugs are quickly available, are effective in targeting the virus of interest, and are accessible early during infection, and early during a growing pandemic. This has widespread implications for public health.

Cutting down on time to drug development, but improving the accuracy and efficiency with which we are able to optimize and test drugs, allows us to more proactively and rapidly combat future pandemics. Through this, we accept the reality of future pandemics, while preparing ourselves to respond more rapidly and protect human lives. This allows antiviral drugs to be more readily available, reduce hospitalizations and hopefully reduce the impact on pandemics on our communities.

Kyra Schwartz | Stigma and Intimate Partner Violence as Barriers to PrEP and Family Planning Usage in Kenya

HIV poses a profound threat to public health, especially in Eastern and Southern Africa. In 2024, the WHO estimated that over 650,000 people died from HIV-related causes and over 1,300,000 people acquired HIV infections. Of these new cases, 50 percent occurred in Africa, with a higher incidence among females than males. Kisumu, Kenya is particularly burdened by the HIV epidemic. Despite relatively widespread availability, Kisumu still has low uptake of HIV prevention services such as pre-exposure prophylaxis (PrEP), especially in young women and girls who are at high risk of acquiring HIV. Social factors can profoundly influence the effectiveness of medical interventions, yet they are often overlooked.

Our project investigates social barriers to PrEP and Family Planning (FP) initiation and adherence in young women and girls in Kisumu. We found that various forms of stigma and intimate partner violence (IPV) are the primary reasons cited for neglecting or discontinuing use, followed by fear, misinformation and lack of awareness. This informs future PrEP and FP design needs, as well as the development of local education and outreach programs for clinics and communities.

This work brings together knowledge and ideology from the health and social sciences to provide a foundation for holistically addressing disparate health crises. Our results underscore the significant influence that social factors exert on health outcomes and can inform future research and initiatives aimed at improving global health equity.