NSF APPEX focuses on enabling multidisciplinary collaborations specifically focused on combinatorial risk scenarios that need simultaneous consideration by multiple academic domains and disciplines. In this way, APPEX provides for the development of a rigorous hierarchy of evidence for pandemic risk, leading to improved methodologies for scenario-to-scenario comparison, and creates and meets audacious challenges in multidisciplinary hypothesis generation, model/tool building, and information infrastructure.
Graphic by Jessica Rozek Cañizares

Core Research Foci

A Case-Control Study of Outbreaks in Wapanoag Histories
This team will work to analyze the specific case study of historic infectious disease outbreaks in 17th century Wapanoag using a Case-Control framework 

 

Case Studies in Case-Control Epidemiology 1
This is one of the teams that will identify useful case-study examples and apply the Case-Control framework and methods to analyze those examples

 

Case Studies in Case-Control Epidemiology 2
This is one of the teams that will identify useful case-study examples and apply the Case-Control framework and methods to analyze those examples
Cutting Edge Ensemble Models
This team will work on filling in identified gaps among types of ensemble methods approaches and suggesting new application areas for existing methods
Designing New MultiFactorial Analytic Methods
This team will use elements of voting theory, computational and algorithmic complexity theory, and statistics to design new methods for multifactorial analysis

 

(Delayed Start) Applications of MultiFactorial Analytic Methods
Once the design team makes some progress, this delayed-start team will test the methods in application to particular case-studies

 

Employing a MultiDisciplinary Simulation Sandbox to Ask Questions in Socio-Econ-Epidemiology - 1, 2, & 3
These teams will employ the just-completed Socio-Econ-Epidemiological simulation sandbox tool to explore specific combinations of factors and how they are likely to impact outbreak dynamics

 

 

Theory Group on Simulation Best Practices
This team will work on foundational theory to provide best practices for simulation studies
Generative AI Hypothesis Discovery
This team will work to build a general framework for fine tuning and querying generative AI tools and LLMs to enable discovery of new domain sources of relevance and successfully reject others
MetaAnnotation for Multidisciplinary Data - Architecture
This team will design and develop an APPEX-Semantic Framework platform for integrated, unified, and shared access to the relevant data extracted from existing heterogeneous databases and repositories to enable creation/emergence of communities of interest

 

MetaAnnotation for Multidisciplinary Data - User Desdirata
This team will act as a client focus group, brainstorming desired properties and features for our APPEX-Semantic Framework
Risk in topology of buildings
This team will work on methods to map and predict epidemiological risks within buildings based on the structural topology of the building

 

Compromised Urban-Suburban-Rural Infrastructure and Waterborne Infection Risks
This team will consider the specific challenges of built infrastructure of many types relating to water to predict waterborne disease risks

Multiscale ecological/epidemiological pattern identification 1, 2 & 3

This is one of the teams that will develop physically-based and causally-informed data analysis techniques that can differentiate between statistical flukes and meaningless correlations vs. causally-meaningful and explainable patterns

 

Spruce Budworm Prediction/Hindcasting
This team will bring together economic, ecological, and epidemiological principles to try to understand and predict the specific case study of outbreaks of Spruce Budworm in North American forests

Domestic Regional PovertyTraps

This team will work to analyze the socio-spatio-temporal patterns in housing, resource, and healthcare access and outcomes in the US

Case-control frameworks for healthcare users and consumers

This team will work to identify which factors in the human healthcare systems are mutable, comparing mutual perceptions of healthcare providers and consumers/users in different populations, and translating descriptions of outcomes as they are defined across multiple disciplines and members of affected communities

Understanding outbreak epidemiology in hospital systems

This team will work to develop a framework for modeling how differences in hospital management and antibiotic stewardship impact nosocomial outbreak dynamics

 

Explore Outbreak Dynamics

NSF APPEX Goes Beyond

We go beyond existing research on disciplinarily targeted factors affecting pandemic risks and instead provides an enabling framework for synergy, complementing domain-driven research efforts. As such, NSF APPEX ensures that the vision of pandemic science is proactive, focusing on framing how to meet complex challenges, improving both our ability to respond to existing disease threats and to be flexible, nimble, and adaptable to the next emerging pathogen we cannot yet anticipate to increase health security regionally, nationally, and globally.

Connect with us 
on social media:

contact@appex.org
This material is based upon work supported by the National Science Foundation under Award No. 2412115. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation