STLT Outbreak and Analytics Response (SOAR)
A epidemiological surveillance system designed for state, tribal, local, and territorial (STLT) public health departments. The STLT Outbreak and Analytic Response (SOAR) system integrates multiple forecasting models and genomic tree assessments. The systems also has additional functionality, such as alerting systems and ensemble modeling to support evidence-based decision making in respiratory surveillance.
SOAR Video Tutorials
A series of video tutorials that provide step-by-step guidance on how to optimize its various features and functionalities to support effective public health decision-making and emergency response. These videos will be embedded within the SOAR platform.
SOAR Demo
Instructor-led facilitations of the SOAR platform that provide STLT partners with an overview and step-by-step guide to navigating the platform for independent use.
Mastering SOAR: An online platform for Public Health Surveillance, Forecasting and Outbreak Response.
This course is a self-paced, asynchronous training series designed to introduce public health professionals to the nowcasting and forecasting capabilities of the SOAR platform.
Simulation Games
Develop serious simulation games and planning to host workshops focused on these games.
Mpox Forecasting Model
Multi-variate time-series forecasting model of weekly Mpox cases for San Diego county and other U.S jurisdictions. Key objectives include developing a forecasting model that incorporates the lagged cases from other jurisdictions and that provides a ‘better’ forecast than a simple naive estimate. Performance metrics such as the bias and RMSE are used to assess the…
Hepatitis A person to person transmission epidemic model
Dynamic, deterministic compartmental model of person to person hepatitis a virus transmission and vaccination among a single risk group. The model includes stratification by susceptible, latently infected, infectious, temporary remission, and immune. The model is calibrated to surveillance data (diagnosed cases) using maximum likelihood estimation. The model can be used for short-term forecasting, scenario analysis,…
Forecasting