Center for Implementation in Outbreak Analytics and Disease Modeling: Multi-Scale Outbreak Decision-Support Tools - This application is for Mandatory Component 1 and Optional Component 4. A team of experts from eight academic and one industry organization and officials from seven state, regional and local government agencies that serve over 11% of the US population proposes to expand analytic capabilities and build strong institutional partnerships across state, tribal, local, or territorial (STLT) jurisdictions to bolster national readiness for future pathogen threats. For over 20 years, our modeling team has collaborated with officials worldwide to provide real-time decision support during public health crises and build innovative, durable, and scalable analytic tools for tracking, forecasting, and mitigating outbreaks. Our Component 1 activities will expand our capacity to partner with the Center for Forecasting and Outbreak Analytics (CFA) and Centers for Disease Control and Prevention (CDC) in supporting global outbreak responses by maintaining flexible models, expanding a widely-used toolkit for model coordination, creating infrastructure to accelerate engagement and surge staff, and cultivating trusted partnerships between modelers and public health professionals. Our Component 4-Strategy 6 activities will take an Agile systems engineering approach to assessing needs, prioritizing, designing, building, testing, and deploying high-priority proven analytical tools. Implementation will be initially launched in collaboration with the public health core team in Massachusetts and Texas, and then expanded nationwide. Our list of candidate tools includes over a dozen designed by our team members and deployed by CDC and others during prior emergencies, including the 2009 H1N1 influenza pandemic, the 2013-16 West African Ebola virus epidemic, the 2015-2016 Zika outbreak, multiple influenza seasons, and the COVID-19 pandemic. Each was developed with support from a collaborating agency, including the CFA, CDC, Council of State and Territorial Epidemiologists (CSTE), Defense Threat Reduction Agency (DTRA), Association for Public Health Labs (APHL), Defense Advanced Research Projects Agency (DARPA), Department of Homeland Security (DHS), and Texas Department of State Health Services. They include: (a) the Hubverse platform currently used by the CDC to aggregate and display COVID and influenza forecasts submitted weekly by research teams worldwide; (b) multiple COVID and influenza nowcasting and forecasting analytics across spatial scales, from individual ZIP-codes to the US; (c) an optimization platform to support rapid evaluation and integration of novel data sources into forecasting models; (d) technology for designing staged-alert systems to guide public risk communication and intervention policies; (e) a suite of optimization tools to support stockpiling, allocation and distribution of diagnostic tests, therapeutics, vaccines, ventilators, and other medical countermeasures; and (f) an interactive epidemic simulator to support tabletop exercises. Our Component 4-Strategy 7 activities will ascertain gaps in analytical skills and training needs for public health professionals across STLT jurisdictions, and produce a portfolio of online courses, tutorials and live game-based exercises to meet those needs. These resources will be co-created by our public health core and experienced academic educators, who have developed innovative curricula for analytical upskilling, and will leverage highly-subscribed online public health training platforms at the University of Texas at Austin’s Center for Health Communication, CSTE, and CDC. Throughout the project, we will collaborate with the Centers for Outbreak Analytics and Disease Modeling Network, CFA, CDC, CSTE, Association of State and Territorial Health Officials (ASTHO), and National Association of County and City Health Officials (NACCHO) to promote alignment, efficiency, and successful national scaling of our response-ready capabilities, analytic decision-support tools, and educational resources.