Events
Beyond the Pathogen: Disease-Agnostic, Scalable Models for Public Health Preparedness and Decision-Making | Webinar
Date
September 10, 2025 12:00pm - 01:00pm
US/Eastern
In a world where new public health threats can emerge at any time, professionals across health, research, and emergency response need more than isolated data models. They need integrated, adaptable frameworks. Register now to learn how these approaches can transform public health preparedness.
This webinar will highlight how a Disease X modeling framework can offer a multi-scale, modular approach to track, simulate, and mitigate emerging and re-emerging infectious diseases. Attendees will explore how tools like CASSANDRA, RTI SynthPop, and geospatial mapping can accurately simulate real-world transmission dynamics across populations and environments to improve your planning and response.
Learn how synthetic population data and environmental modeling can strengthen preparedness strategies, including resource deployment, targeted surveillance, and antiviral use. Through real-world applications such as mpox, tick-borne diseases, and health care-associated infections, RTI experts will show how this disease-agnostic framework supports faster, smarter decision-making at every level of public health preparedness and response.
Webinar Objectives:
- Identify limitations of current modeling approaches and the need for flexible, multi-scale tools
- Introduce an integrated Disease X modeling framework to support public health preparedness and response
- Demonstrate how tools such as CASSANDRA, RTI SynthPop, and geospatial mapping simulate disease spread and support scenario planning
- Highlight how synthetic populations, cost-effectiveness modeling, and geospatial data inform real-world response decisions, including outbreak mitigation, resource allocation, and surveillance
- Showcase how this model can be effectively applied across efforts around mpox, tick-borne illness, health care-associated infections, and more
Meet the Presenters
Joella W. Adams, PhD
Joella Adams is an epidemiologist at RTI specializing in simulation modeling and cost-effectiveness analysis to inform public health policy. She leads modeling efforts for opioid use and SARS-CoV-2 spread in North Carolina. Her work focuses on evaluating interventions for infectious diseases and opioid use disorder, building on prior research at Boston University on overdose prevention and treatment strategies.
Donal Bisanzio, PhD
Donal Bisanzio is an infectious disease expert specializing in diseases affecting both humans and animals. Since joining RTI's global health team in 2017, he has applied his veterinary medicine background and extensive field experience, including trapping and collecting wild animals, to study vector-borne and zoonotic diseases such as malaria, Lyme disease, West Nile virus, and parasitism. Skilled in spatio-temporal statistical models, network analysis, remote sensing, and GIS, he uses advanced methods to analyze disease spread and inform targeted interventions.
Claire Quiner, MPH
Claire Quiner is an infectious disease epidemiologist specializing in U.S.-based disease surveillance, spatial analysis, and data-driven decision-making. At RTI, she works on CDC-funded projects, including evaluating post-pandemic COVID-19 surveillance systems and developing coordinated sentinel surveillance for emerging pathogens using metagenomic sequencing. She brings expertise in study design, diagnostics, and spatial modeling with R, QGIS, and ArcGIS to strengthen detection and response systems for infectious disease threats.
James Rineer, CPC
James Rineer is a registered civil engineer and spatial data scientist who manages RTI’s Geospatial Science and Technology program. He specializes in developing GIS-based tools, synthetic population datasets, and analytic systems used in infectious disease modeling and surveillance. His work spans web, desktop, and mobile platforms, integrating advanced mapping, big data analytics, and modeling frameworks to predict disease spread and support public health decision-making.
