Foa_Content_of_CDC-RFA-FT-23-0069 (4).pdf

Signature Date

Centers for Disease Control and Prevention

Center for Forecasting and Outbreak Analytics

Centers for Outbreak Analytics and Disease Modeling

CDC-RFA-FT-23-0069

07/14/2023

Table of Contents A. Funding Opportunity Description

B. Award Information

C. Eligibility Information

D. Required Registrations

E. Review and Selection Process

F. Award Administration Information

G. Agency Contacts

H. Other Information

I. Glossary

Part I. Overview

Applicants must go to the synopsis page of this announcement at www.grants.gov and click on the "Subscribe" button link to ensure they receive notifications of any changes to CDC-RFA-FT- 23-0069. Applicants also must provide an e-mail address to www.grants.gov to receive notifications of changes.

A. Federal Agency Name:

Centers for Disease Control and Prevention (CDC) B. Notice of Funding Opportunity (NOFO) Title:

Centers for Outbreak Analytics and Disease Modeling C. Announcement Type: New - Type 1:

This announcement is only for non-research activities supported by CDC. If research is proposed, the application will not be considered. For purposes of this NOFO, research is defined as set forth in 45 CFR 75.2 and, for further clarity, as set forth in 42 CFR 52.2 (see eCFR :: 45 CFR 75.2 -- Definitions and https://www.gpo.gov/fdsys/pkg/CFR-2007-title42-vol1/pdf/CFR- 2007-title42-vol1-sec52-2.pdf. In addition, for purposes of research involving human subjects and available exceptions for public health activities, please see 45 CFR 46.102(l) (https://www.ecfr.gov/current/title-45/subtitle-A/subchapter-A/part-46/subpart-A/section- 46.102#p-46.102(l)).

Please note that for this particular NOFO, CDC-RFA-FT23-0069, notwithstanding the language above, research activities involving human subjects are ALLOWABLE subject to all applicable laws, regulations and policy requirements. Note research and human subjects' protection requirements inserted throughout this NOFO. All instructions related to research should be https://www.grants.gov/ https://www.grants.gov/ https://www.gpo.gov/fdsys/pkg/CFR-2007-title42-vol1/pdf/CFR-2007-title42-vol1-sec52-2.pdf https://www.gpo.gov/fdsys/pkg/CFR-2007-title42-vol1/pdf/CFR-2007-title42-vol1-sec52-2.pdf https://www.ecfr.gov/current/title-45/subtitle-A/subchapter-A/part-46/subpart-A/section-46.102#p-46.102(l) https://www.ecfr.gov/current/title-45/subtitle-A/subchapter-A/part-46/subpart-A/section-46.102#p-46.102(l) addressed and followed as indicated in this NOFO. Please refer to Strategies and Activities for more details.

D. Agency Notice of Funding Opportunity Number:

CDC-RFA-FT-23-0069

E. Assistance Listings Number:

93.823 F. Dates:

1. Due Date for Letter of Intent (LOI):

06/17/2023 Required

2. Due Date for Applications:

07/14/2023 11:59 p.m. U.S. Eastern Standard Time, at www.grants.gov.

3. Due Date for Informational Conference Call An informational webinar is scheduled for Monday, May 22nd from 1 - 2:30 EST

Register in advance for this webinar:

https://cdc.zoomgov.com/webinar/register/WN_U9aiVnLZRVmT6eogsOC8rg

Frequently asked questions (FAQs) and more information can be found at CFA's website:

https://www.cdc.gov/forecast-outbreak-analytics/nofo.html

F. Executive Summary:

Summary Paragraph This NOFO includes five components, one Mandatory and four Optional. The underlying objective of the Centers for Outbreak Analytics and Disease Modeling (OADM) NOFO is to develop a network of innovators to design, prototype, test, refine, evaluate, and implement new and enhanced capabilities to improve disease modeling and analytics that enhance decision support during outbreaks of infectious diseases. Partnership and collaboration between academia, public health organizations, and the private sector is at the core of this NOFO. The OADM network is intended to enable the United States public health system to better respond to infectious disease threats by enabling a pipeline of research and development for novel data sources, modeling methods, and analytical tools that tests promising innovations in real-world settings and then supports the scale-up of successful innovations into routine practice. The network is also intended to enhance communication and collaboration among innovators, integrators, and implementors in analytic methods and public health partners in federal, state, tribal, local, and territorial governments to improve outbreak response and enhance the ability to better control epidemics and pandemics.

https://www.grants.gov/ https://cdc.zoomgov.com/webinar/register/WN_U9aiVnLZRVmT6eogsOC8rg

a. Eligible Applicants:

Open Competition

b. NOFO Type:

CA (Cooperative Agreement)

c. Approximate Number of Awards Up to 13 total awards

Mandatory Component 1 (Outbreak Analytics and Disease Modeling Public Health Response): 13 awards

Optional Component 2 (Innovations in Outbreak Analytics and Disease Modeling): 5 awards

Optional Component 3 (Integration of Outbreak Analytics and Disease Modeling into Practice): 5 awards

Optional Component 4 (Centers for Implementation in Outbreak Analytics and Disease Modeling): 3 awards

Optional Component 5 (Coordinator for the Outbreak Analytics and Disease Modeling Network): 1 award

d. Total Period of Performance Funding:

$262,500,000

e. Average One Year Award Amount:

$5,500,000 Depending on optional components applied for—range could be from $3,500,000 to $6,500,000

Mandatory Component 1 (Outbreak Analytics and Disease Modeling Public Health Response) - $500,000

Optional Component 2 (Centers for Innovation in Outbreak Analytics and Disease Modeling) - $3,000,000

Optional Component 3 (Centers for Integration of Outbreak Analytics and Disease Modeling into Practice) - $3,000,000

Optional Component 4 (Centers for Implementation of Outbreak Analytics and Disease Modeling) - $5,000,000

Optional Component 5 (Coordinator of the Outbreak Analytics and Disease Modeling Network) - $1,000,000

f. Total Period of Performance Length:

5 year(s)

g. Estimated Award Date:

September 15, 2023

h. Cost Sharing and / or Matching Requirements:

No Part II. Full Text

A. Funding Opportunity Description

1. Background

a. Overview The COVID-19 pandemic highlighted the importance of timely evidence for decision-making during outbreak responses and the challenge of providing actionable insights with existing data sources and analytical tools. Disease modeling and forecasting has become a critical tool for guiding decision-making in outbreaks and during the COVID-19 pandemic. However, disease modeling and forecasting within the U.S. public health system has not been broadly resourced and systematically operationalized. This NOFO intends to help fill those gaps by developing a network of performers that will build, evaluate, and scale methods, tools, and technologies to apply and communicate modeling and forecasting before, during, and post a public health emergency. This NOFO intends to build capabilities in collaboration with state, tribal, local, and territorial public health partners and aims to strengthen the outbreak and pandemic response capabilities in the U.S. public health system. This includes training and workforce development for the public health workforce and public health emergency response decision makers. This NOFO intends to support four sets of performers – innovators, integrators, implementors, and a network coordinator. This network intends to build new capabilities, test those capabilities in collaboration with practicing public health professionals, and scale successful capabilities among jurisdictions. This network intends to advance operational disease modeling and forecasting capabilities among federal, state, local, territorial, and tribal partners so that the nation is better prepared to respond to outbreaks and pandemics.

b. Statutory Authorities Section 301 of the Public Health Service Act (42 U.S.C. section 241)

Section 317(k)(2) of the PHS Act (42 U.S.C. section 247b(k)(2))

c. Healthy People 2030 Emergency Preparedness: https://health.gov/healthypeople/objectives-and-data/browse-objectives/emergency-preparedness

Public Health Infrastructure: https://health.gov/healthypeople/objectives-and-data/browse-objectives/public-health-infrastructure

Health IT: https://health.gov/healthypeople/objectives-and-data/browse-objectives/health-it

Global Health: https://health.gov/healthypeople/objectives-and-data/browse-objectives/global-health

d. Other National Public Health Priorities and Strategies National Biodefense Strategy and Implementation Plan: Goal 1 Objective 1, Goal 3 Objective 4 https://health.gov/healthypeople/objectives-and-data/browse-objectives/emergency-preparedness https://health.gov/healthypeople/objectives-and-data/browse-objectives/emergency-preparedness https://health.gov/healthypeople/objectives-and-data/browse-objectives/public-health-infrastructure https://health.gov/healthypeople/objectives-and-data/browse-objectives/public-health-infrastructure https://health.gov/healthypeople/objectives-and-data/browse-objectives/health-it https://health.gov/healthypeople/objectives-and-data/browse-objectives/global-health https://health.gov/healthypeople/objectives-and-data/browse-objectives/global-health https://www.whitehouse.gov/wp-content/uploads/2022/10/National-Biodefense-Strategy-and- Implementation-Plan-Final.pdf

e. Relevant Work In this NOFO, outbreak analytics is defined as described in Polonsky JA, Baidjoe A, Kamvar ZN, Cori A, Durski K, Edmunds WJ, Eggo RM, Funk S, Kaiser L, Keating P, de Waroux OLP, Marks M, Moraga P, Morgan O, Nouvellet P, Ratnayake R, Roberts CH, Whitworth J, Jombart T. Outbreak analytics: a developing data science for informing the response to emerging pathogens. Philos Trans R Soc Lond B Biol Sci. 2019 Jul 8;374(1776):20180276. doi:

10.1098/rstb.2018.0276. PMID: 31104603; PMCID: PMC6558557

Other useful references include:

Pollett S, Johansson MA, Reich NG, Brett-Major D, Del Valle SY, Venkatramanan S, et al.

(2021) Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines | PLOS Medicine. PLoS Med 18(10): e1003793.

Daniel B. Jernigan, Dylan George, Marc Lipsitch, Learning From COVID-19 to Improve Surveillance for Emerging Threats | AJPH | Vol. 113 Issue 5 (aphapublications.org)

2. CDC Project Description

a. Approach

Bold indicates period of performance outcome.

CDC-RFA-FT-23-0069 Logic Model: Centers for Outbreak Analytics and Disease Modeling

Strategies and Activities Short-Term Outcomes Intermediate Outcomes Long-Term Outcomes

Strategy 1 (Mandatory Component 1) Plan, prepare and respond

Established foundational infrastructure for response activities, such as staffing plans, protocols and data use agreements

Improved identification of key areas of focus in a public health emergency (e.g., model development, contribution of model output, data standardization, field applications, Improved relationships between the recipients and decision makers that could be activated in a public health emergency and provide technical assistance

Increased quantity and quality of analytic support provided to decision makers in the context of a public health emergency including greater flexibility to address emerging issues

Development of a network of organizations, systems, and subject matter experts who are response ready to support STLT jurisdictional partners with advanced outbreak analytics, disease modeling and technical support during a public health emergency

Improved ability to contribute analytic and decision support to a global, national, regional, state or local public health https://www.whitehouse.gov/wp-content/uploads/2022/10/National-Biodefense-Strategy-and-Implementation-Plan-Final.pdf https://www.whitehouse.gov/wp-content/uploads/2022/10/National-Biodefense-Strategy-and-Implementation-Plan-Final.pdf https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003793 https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003793 https://ajph.aphapublications.org/doi/full/10.2105/AJPH.2023.307261?role=tab https://ajph.aphapublications.org/doi/full/10.2105/AJPH.2023.307261?role=tab deployment of technical experts)

Established connections with potential state, tribal, local, and territorial (STLT) jurisdictions that would benefit from support during a public health emergency emergency response in an agile manner

Strategy 2 (Optional Component 2) Develop new (or enhance existing) analytic tools and platforms by applying new technologies

Identification of end user/decision maker needs for new tools or enhancements of existing tools

Identification and testing of new technologies, or use of existing technology in new ways to support modeling and outbreak analytics

Developed, calibrated, and validated models and outbreak analytics specific to a disease and/or route of transmission

Increased evaluation of new tools to determine suitability for testing in real world settings

Documentation of lessons learned from both successful and unsuccessful development

Establish and maintain a platform for ongoing innovation and exploration of new models and analytic tools at the cutting edge

New analytic tools and platforms created and enhanced for disease modeling and outbreak analytics

Strategy 3 (Optional Component 2) Produce innovative analytic products and output by using novel data or synthesizing diverse data

Identification of and access gained to novel data sources with potential to inform model development and outbreak analytics

Increased availability of new analytic products that use novel data sources or syntheses of data from multiple sources

Improved speed, representativeness, completeness and accuracy of data collection needed to power outbreak analytics and disease modeling output

Strategy 4 (Optional Component 2) Train and develop pipeline of infectious disease modelers

Increased availability and accessibility of disease modeling and outbreak analytics training at the masters, doctoral and post-doctoral levels, with an emphasis on diversity, equity and inclusion

Established mechanisms for career development opportunities and job placement of qualified students and graduates within the Federal, state, local, territorial and tribal public health system, with an emphasis on diversity, equity, inclusion and accessibility

Increased capacity in the public health workforce for carrying out disease modeling and outbreak analytics (strategy 4 and 7)

Increased diversity, equity, inclusion and accessibility in the disease modeling and outbreak analytics workforce

Strategy 5 (Optional Component 3) Pilot test disease modeling and outbreak analytics in real world settings

Increased integration of partnerships across sectors that support decision makers in a variety of settings with data collection and analytic output to guide actions during a public health emergency

Increased identification and availability of promising data collection, analytic, decision support and data visualization approaches for testing in real world settings

Increased integration of disease modeling, outbreak analytics into practice in public health, health care, and private sector settings

Increased innovative modeling and analytic approaches rigorously tested in real world settings, with success and failures carefully documented

Improved decision-making in public health emergencies among identified integration partners

Increased access to promising modeling, analytic and data collection approaches for potential scale-up across organizations, jurisdictions or sectors

New approaches for visualization or communication of modeling and analytic results identified

Strategy 6 (Optional Component 4) Bring proven/tested approaches to scale across

Increased access to promising modeling, forecasting, outbreak analytic and decision support tools, methods, and practices with

Increased partnerships established with decision makers across jurisdictions and sectors to tailor analytic output, tools and technical assistance to effectively meet real-time

Identification of approaches that have been rigorously tested in real world settings are brought to scale across organizations and jurisdictions potential for scale-up at the regional, national or international level needs to support action at scale during public health emergencies organizations, jurisdictions and sectors

Strategy 7 (Optional Component 4) Outbreak analytics and disease modeling upskilling and continuing education for public health professionals

Increased identification of the needs and gaps in knowledge, skills, and abilities in disease modeling, forecasting and outbreak analytics for public health professionals across jurisdictions and sectors

Developed curriculum and training modalities to address challenges and opportunities

Implementation of practical approaches to provide training in disease modeling, forecasting and outbreak analytics to public health professionals

Increased identification of approaches for maintaining skills, integrating new technology and continuing education established

Increased availability of disease modeling, forecasting and outbreak analytics training for public health professionals

Increased capacity of decision makers to use output from disease models, forecasts and outbreak analytics to support public health action in public health emergencies

Strategy 8 (Optional Component 5) Develop a network of innovators in disease modeling and forecasting in active collaboration with practitioners

Regular and ad hoc meetings convened to support information exchange and collaboration among Centers including sharing tools and methods being developed

Increased collaboration with practitioners to continue to inform the activities of the network

Promotion of high-quality outbreak analytics and modeling through initiatives such as standards development, collaborative development, and evaluation of tools and methods

Increased engagement with other networks developing or implementing disease modeling, outbreak analytics, disease surveillance, data or laboratory modernization initiatives, or other related activities

Increased use of common analytic tools and applications across network sites and among public health practitioners

Improved national level capacity and coordination of public health emergency responses

Reduced morbidity and mortality associated with public health emergency responses

i. Purpose The purpose of this NOFO is to 1) integrate novel data sources, methods, or technology into outbreak analytic tools, pipelines, or enterprise capabilities; 2) create, enhance, and/or integrate analytical tools and trained workforce for outbreak response; and 3) develop or enhance approaches for visualization or communication of analytic results to decision makers.

ii. Outcomes The overall outcomes will focus on:

Established foundational infrastructure for response activities, such as staffing plans, protocols and data use agreements

Improved identification of key areas of focus in a public health emergency (e.g., model development, contribution of model output, data standardization, field applications, deployment of technical experts)

Established connections with potential STLT jurisdictions that would benefit from support during a public health emergency

Identification of end user/decision maker needs for new tools or enhancements of existing tools

Identification and testing of new technologies, or use of existing technology in new ways to support modeling and outbreak analytics

Developed, calibrated, and validated models and outbreak analytics specific to a disease and/or route of transmission

Increased evaluation of new tools to determine suitability for testing in real world settings Documentation of lessons learned from both successful and unsuccessful development Identification of and access gained to novel data sources with potential to inform model development and outbreak analytics Increased availability of new analytic products that use novel data sources or syntheses of data from multiple sources Increased availability and accessibility of disease modeling and outbreak analytics training at the masters, doctoral and post-doctoral levels, with an emphasis on diversity, equity and inclusion

Established mechanisms for career development opportunities and job placement of qualified students and graduates within the Federal, state, local, territorial and tribal public health system, with an emphasis on diversity, equity, inclusion and accessibility

Increased capacity in the public health workforce for carrying out disease modeling and outbreak analytics (strategy 4 and 7)

Increased integration of partnerships across sectors that support decision makers in a variety of settings with data collection and analytic output to guide actions during a public health emergency

Increased identification and availability of promising data collection, analytic, decision support and data visualization approaches for testing in real world settings

Increased integration of disease modeling, outbreak analytics into practice in public health, health care, and private sector settings

Increased innovative modeling and analytic approaches rigorously tested in real world settings, with success and failures carefully documented

Increased access to promising modeling, forecasting, outbreak analytic and decision support tools, methods, and practices with potential for scale-up at the regional, national or international level

Increased partnerships established with decision makers across jurisdictions and sectors to tailor analytic output, tools and technical assistance to effectively meet real-time needs to support action at scale during public health emergencies

Increased identification of the needs and gaps in knowledge, skills, and abilities in disease modeling, forecasting and outbreak analytics for public health professionals across jurisdictions and sectors

Developed curriculum and training modalities to address needs and gaps Implementation of practical approaches to provide training in disease modeling, forecasting and outbreak analytics to public health professionals Increased identification of approaches for maintaining skills, integrating new technology and continuing education established Regular and ad hoc meetings convened to support information exchange and collaboration among Centers including sharing tools and methods being developed Promotion of high-quality outbreak analytics and modeling through initiatives such as standards development, collaborative, development, and evaluation of tools and methods

iii. Strategies and Activities Applicants are required to respond to the Mandatory Component 1 and only one of the Optional Components 2-4 (Centers for Innovation, Integration, or Implementation), for a total of two components. Applicants may also choose to respond to the Optional Component 5 (Coordinator for Outbreak Analytics and Disease Modeling Network, for a total of three components.

Separate Narratives and Budgets are required as follows:

a. Mandatory Component 1 - Outbreak Analytics and Disease Modeling Public Health Response (one narrative and one budget)

b. Optional Components 2 - 4 - for one of the three optional components 2-4 selected (one narrative and one budget)

c. Optional Component 5 - Coordinator for the Outbreak Analytics and Disease Modeling Network (one narrative and one budget)

All recipients supported by this NOFO are expected to address the Mandatory Component and one other Optional Component. One recipient is also expected to address the Optional Component (Coordinator for Outbreak Analytics and Disease Modeling Network).

In order to achieve the objectives and strategies of this award, all code and tools developed under this award must be available for sharing within the network and made publicly available to the largest extent feasible, including through the use of open-source code, licensing, and similar platforms. Applicants may consider developing no-code (i.e., user-friendly) versions of tools for use by stakeholders without programming backgrounds. See applicable regulations found at 45 CFR 75, including subpart 75.322 concerning intangible property

Innovation and translation are the main ongoing objectives of the Outbreak Analytics and Disease Modeling Network, and is directed toward identifying, developing, testing, evaluating, and implementing new technology, analytic and decision support approaches that improve the effectiveness of U.S. public health responses.

The public health response strategy relies on contributing to a national, regional, state or local public health response in a flexible and rapid manner. This may include, for example, assisting with producing modeling and forecasting results, collection or synthesis of data from a variety of sources, producing reports, supporting decision makers in the interpretation of results and providing insights based on qualitative or quantitative risk assessments.

Mandatory Component 1—Outbreak Analytics and Disease Modeling Public Health Response

Strategy 1. Plan, prepare and respond

Applications should describe foundational activities such as preparing data use agreements as needed to access relevant data, memoranda of understanding and institutional review board (IRB) protocols where required to allow rapid scale-up of efforts across the network. In addition, applications should describe an approach to surging staff as needed in the context of a large-scale emergency. During an emergency, these staff and others identified throughout the application will perform modeling, forecasting and other analytics.

With initial funding, recipients should plan the types of research studies and non-research activities that could be done in the event of an infectious threat, including analyzing and synthesizing data to inform public health action. Applications should include working with funded partners in the network to create ensemble forecasts and/or prepare informational reports. The network is expected to make informational reports public in a timely way. These reports will provide an objective overview of recent information for use by local, state, and federal public health agencies. These reports are not intended to provide recommendations.

Applications should describe response implementation activities in one or more of these areas:

1. Development, calibration, and validation of models and outbreak analytics specific to a disease and/or route of transmission

2. Contribution of model output to ensembles and production of forecasts of cases, hospitalizations, deaths and other priority outcome

3. Data standardization/data security/data stewardship/data integration and reporting/data linkage/data science/data analytics/data visualization including of genomic, epidemiologic, clinical, biological, environmental, geospatial, behavioral, social and other types of data together

4. Critical data collection and analyses to gather new or emerging data and create evidence for inclusion in existing or new models

5. Field applications and investigations in support of state, local, territorial, tribal jurisdictional needs

6. Identification of human resources for deployment to CDC or other public health partners in the context of an emergency response, as well as the timely mechanisms to do so

Response implementation consistent with the terms of this cooperative agreement may be funded via post-award supplements should infectious threat conditions warrant. Specific activities, consistent with the terms of this cooperative agreement, may include but are not limited to the following:

In collaboration with relevant subject-matter groups from CDC, develop or adapt analytic and modeling methods for new or emerging disease threats

Address analytic requirements specific to a response

Develop and integrate outbreak analytics to rapidly analyze, interpret, visualize, integrate, and support public health decision making

Expand networks of partnerships across public health, academia and the private sector that can be rapidly engaged for infectious threats.

Provide decision support and interpretation of analytic output related to their implications for public health

Provide regular and timely reports to public health and, as appropriate, relevant third parties, including advisory committees (e.g., CDC Board of Scientific Counselors), in response to infectious threats.

These activities should provide coordinated, rapid, and scalable actions in responding to infectious threats. Following initial award, a Network Response Plan will be developed collaboratively across the network. Applicants should describe how they would use their expertise in areas that may be useful during responses to infectious threats.

Optional Component 2 (Centers for Innovation in Outbreak Analytics and Disease Modeling)

Funded recipients of this optional component are expected to function as a technology and innovation “incubator” for outbreak analytics and disease modeling in public health. To this end, recipients are expected to establish and maintain a research and evaluation “platform” that allows them to readily identify, develop, adapt, and evaluate new models, analytic approaches, novel data, and technological tools at the cutting edge.

The proposed approach is expected to involve a team of innovators (scientists, engineers, developers, and others) and public health partners (non-profit, federal and STLT leaders), led by an individual with a strong background in outbreak response and analytics. Applicants should identify a lead with this background as well as key supporting innovation team members with the combined expertise to accomplish the innovation activities in this component. Curriculum vitae for these key personnel that document their qualifications should be uploaded as a PDF to www.grants.gov.

Applications should include a well-defined plan for evaluating the impact of their innovations on the public health practice of the implementing partners. Documentation of both promising approaches with the potential for scale up, and those that were tried and failed are both considered key deliverables from these activities. Promising innovations generated through the work of recipients for this optional component may be pilot tested or implemented by other members of the Outbreak Analytics and Disease Modeling Network in future funding cycles.

Strategy 2 Develop new (or enhance existing) analytic tools and platforms by applying new technologies

Applicants should describe how they propose to improve outbreak response modeling and analytics by creating new tools and/or developing enhancements to existing tools. These proposals should have a clear link to improving decision-making and have considered how they would be employed by federal and/or STLT end-users. Example innovations could include:

Creating improved nowcasting models that can handle common real-world data defects https://www.grants.gov/

Developing and testing novel inference methods for high-dimensional problems with applications to transmission model fitting

Designing and testing improved forecasting ensembling techniques Testing the use of artificial intelligence and/or machine learning (AI/ML) techniques for efficient calibration of large-scale simulation models through surrogates Developing simulation-based decision support tools for targeting interventions or setting intervention decision thresholds from real-world indicators

Strategy 3 Produce innovative analytic products and output by using novel data or synthesizing diverse data

Applicants should describe how they propose to leverage novel data sources or synthesize multiple sources to create new analytic products. These techniques should consider the timeliness, reliability, and robustness of analytic insight derived from these approaches as compared to existing methods and applicants should have plans for demonstrating real-world improvement. These techniques should also address ethical concerns associated with novel data sources including strategies for reducing bias and protecting privacy. Examples of these approaches could include:

Integrating wastewater, genomic, and/or mobility data and other laboratory-derived data into forecasts or analyses

Applying multi-sensor data fusion techniques to combine internet-derived data with existing public health data streams to develop nowcasts that reduce latency

Developing novel survey approaches, particularly related to behavior around preventative measures during infectious disease epidemics (e.g., mobility, work-from-home frequency, compliance with other non-pharmaceutical interventions such as masks, and vaccine behavior/hesitancy)

Data collection may not encompass more than 1/3 of this optional component’s budget, as the primary focus should be on the development of new approaches for using data as opposed to its collection.

Strategy 4 Train and develop pipeline of infectious disease modelers

All centers will be expected, in collaboration with the Coordinator for the Outbreak Analytics and Disease Modeling network and with CDC, to contribute to the development of training materials, resources and other training activities. Specifically, applicants for this optional component (Centers for Innovation in Outbreak Analytics and Disease Modeling) should include narrative:

Description of training opportunities to be provided at the masters, doctorate and post-doctorate levels

Identification of mechanisms for enabling students and trainees to participate in public health emergency responses or develop analytic projects with collaborators in the Federal, state, local, territorial and tribal public health systems

Outlining approaches and mechanisms for job placement of qualified graduates with advanced training in infectious disease modeling in the Federal, state, local, territorial and tribal public health systems

All activities should speak to including and supporting a diverse and inclusive workforce.

Optional Component 3 (Centers for Integration of Outbreak Analytics and Disease Modeling into Practice)

Strategy 5 Pilot test innovations in real world settings

Recipients of the Optional Component 3 (Integration of Outbreak Analytics and Disease Modeling into Practice) are expected to include the organization in which the identified approaches will be tested, which could be either the recipient themselves or as a sub-recipient.

These partners could include a STLT health department, health care organization (purchaser, provider, payor), large employer, or other relevant entity identified in the application.

Applicants should describe the extent of current collaboration with the implementing partner(s).

Applicants must file a letter of support from the implementing partner(s), name the file “Implementing Partner Letter of Support”, and upload it as a PDF file at www.grants.gov

Applicants for this optional component are expected to have identified a portfolio of candidate innovative analytic approaches or tools that they intend to test with their identified implementing partner. Applicants should describe how these pilot testing efforts, if successful, would be expected to support improved decision-making for their implementing partner in future public health emergencies. Applicants for this optional component should also describe how they will work, with their identified implementing partner to address activities, including but not limited to:

Refining, implementing and evaluating analytic approaches for use by the implementing partner

Enabling availability of tools and practices for use in real-world settings Implementing methods, tools and practices through developing tailored approaches that support implementing partner decision requirements Transitioning outbreak analytic and disease modeling innovations to operations of the implementing partner Establishing mechanisms that support “always on” or response-ready data collection in the context of the implementing partner’s data system and infrastructure Evaluating and documenting the process and results of the integration effort in supporting public health emergency response decision making and effectiveness Developing or enhancing approaches for visualization or communication of analytic results to meet the unique needs of the implementing partner Implementing publicly available, user-friendly analytic or communication tools that will improve the ability of the implementing partner to make key decisions in a public health emergency

Optional Component 4 (Centers for Implementation of Outbreak Analytics and Disease Modeling)

Strategy 6 Bring proven/tested approaches to scale across organizations and jurisdictions

Identifying, developing, refining, disseminating, scaling, and supporting the implementation of promising outbreak analytic and decision support tools and practices across geographically diverse and varied U.S. public health jurisdictions http://www.grants.gov

Partnering with decision makers across jurisdictions and sectors to tailor analytic output, tools and technical assistance to effectively meet the real-time needs to support action during public health emergencies

Applicants for this optional component are expected to have identified candidate innovative analytic approaches or tools that have already been demonstrated in pilot settings to improve decision-making during public health emergencies and that they plan to scale across organizations and/or jurisdictions. Applicants should detail these approaches and describe how they have been successfully applied. Applicants should also describe their approach to scaling these innovations and indicate how this scaling, if successful, would clearly demonstrate that the approach can be used across a wide range of jurisdictions or organizations throughout the nation.

Applicants should also describe how they will manage scale-up risk.

Strategy 7 Outbreak analytics and disease modeling up-skilling and continuing education

Developing practical training in outbreak analytics, modeling, and forecasting for current public health professionals

Applicants for this optional component should describe how they will contribute to the development of online training resources and other training activities in collaboration with the OADM Network Coordinator and with CDC. Applicants should propose online courses or training activities, provide a high-level outline of the curriculum, and describe how the proposed activities are relevant to public health practice. Applicants should also describe expertise among the proposed team that would enable the identification of training needs and the development and delivery of training materials.

Optional Component 5 (Coordinator of the Outbreak Analytics and Disease Modeling Network)

Strategy 8 Develop a network of innovators in disease modeling and forecasting in active collaboration with practitioners

In order to apply for the Coordinator for Outbreak Analytics and Disease Modeling Network, an applicant must apply for the mandatory component and one additional optional component for a total of 3 components.

The work plan for Optional Component (Coordinator for the Outbreak Analytics and Disease Modeling Network) must address the following activities:

Leading the network by convening regular and ad hoc meetings, supporting information and personnel exchange

Coordinating communication activities related to work of all the recipients Engage with CDC along with National organizations representing various public health groups to expand awareness, training, and sharing of best practices Promoting high-quality outbreak analytics and modeling through initiatives such as standards development and collaborative sharing of analytic tools and modeling

1. Collaborations

a. With other CDC programs and CDC-funded organizations:

Recipients are expected to collaborate with CDC programs that are relevant to the projects the network is pursuing. This may include leaders within CDC’s Incident Management Structure, Pathogen Genomics Centers of Excellence, the Centers of Excellence in Vector-Borne Diseases, or program specific subject matter experts. Recipients should collaborate with each other to function with other recipients funded through this NOFO as a network.

Applicants should describe their knowledge and experience in outbreak analytics or modeling, innovative methodologies, and collaborations with federal and STLT partners on infectious disease outbreak response.

Recipients of the Optional Component (Integration of Outbreak Analytics and Disease Modeling into Practice) are expected to include the organization in which the identified approaches will be tested, which could be either the recipient themselves or as a sub-recipient. These partners could include a STLT health department, health care organization (purchaser, provider, payor), large employer, or other relevant entity identified in the application. Applicants should describe the extent of current collaboration with the implementing partner(s). Applicants must file a letter of support from the implementing partner(s), name the file “Implementing Partner Letter of Support”, and upload it as a PDF file at www.grants.gov.

b. With organizations not funded by CDC:

The network will function as a platform for innovation, integration and implementation of outbreak analytics and disease modeling and recipients will be expected to collaborate with organizations such as other Federal agencies; state, local, territorial and tribal governments, health care systems, non-governmental organizations and academic institutions. Recipients are also expected to engage with National organizations representing various public health groups and other health departments and academic institutions to expand training, cross-appointments, sharing of best practices and uses of outbreak analytics and disease modeling in public health responses

2. Population(s) of Focus The NOFO doesn't have a pre-determined focus on a specific target population, but rather asks recipients to consider those populations at greatest risk for adverse outcomes related to a public health emergency or emergencies. Existing modeling and analytic approaches often rely on data sources that aren't fully representative of the entire population and may not include groups that experience higher risk. This might include essential workers, people experiencing homelessness, and those without access to health care.

This NOFO, including funding and eligibility, is not limited based on, and does not discriminate on the basis of race, color, national origin, disability, age, sex (including gender identity, sexual orientation, and pregnancy) or other constitutionally protected statuses.

a. Health Disparities The goal of health equity is for everyone to have a fair and just opportunity to attain their highest level of health. Achieving this requires focused and ongoing societal efforts to address historical and contemporary injustices; overcome economic, social, and other obstacles to health and healthcare; and eliminate preventable health disparities.

Broadly defined, social determinants of health are non-medical factors that influence health outcomes. They are the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life. These forces (e.g., racism, http://www.grants.gov climate) and systems include economic policies and systems, development agendas, social norms, social policies, and political systems. See content below and in other sections (e.g., Approach, Collaborations, Populations of Focus) for information on how this specific NOFO affects social determinants of health.

A health disparity is a preventable difference in the burden of disease, injury, violence, or opportunities to achieve optimal health that are experienced by populations that have been socially, economically, geographically, and environmentally disadvantaged. Health disparities are inextricably linked to a complex blend of social determinants that influence which populations are most disproportionately affected by these diseases and conditions.

The ability to apply mathematical methods to answer health equity questions in infectious disease outbreak and emergency settings is of great interest to the Center for Forecasting and Outbreak Analytics, as is the ability to collect data on the social determinants of health (SDOH) for use in transmission models and forecasting. Applications that address these issues and focus on incorporating social determinants mechanistically into mathematical models are welcomed.

This NOFO also welcomes the application of social epidemiological concepts that recognize that race is not an independent exposure variable, but serves as a proxy for other social determinants, including stigma and racism. Important social determinants for consideration include but are not limited to: geography (rural/urban), household crowding, employment status, occupation, income, and mobility/access to transportation.

iv. Funding Strategy This NOFO intends to fund recipients that have the necessary technical expertise, infrastructure, partnerships and management capabilities to make substantial contributions to the activities and outcomes of the logic model. This NOFO has one Mandatory Component and four Optional Components. Applicants are required to respond to the Mandatory Component 1 and only one of the Optional Component 2-4 (Centers for Innovation, Integration, or Implementation), for a total of two components. Applicants may also choose to respond to the Optional Component 5 (Coordinator for Outbreak Analytics and Disease Modeling Network), for a total of three components. CDC intends to fund one recipient as the Coordinator for the network of centers.

An applicant must receive an award for Component 1 and one Optional Component (Component 2, 3, or 4) to receive an award for Component 5. Separate Narratives and Budgets are required as follows:

a. Mandatory Component 1—Outbreak Analytics and Disease Modeling Public Health Response (one narrative and one budget)

b. Optional Component 2 - 4—for one of the three optional components 2-4 selected (one narrative and one budget)

c. Optional Component 5—Coordinator of the Outbreak Analytics and Disease Modeling Network (one narrative and one budget)

Applicants must clearly state in the Project Abstract Summary for which Optional Component(s) they are applying. When including this information in the Project Abstract Summary, please indicate one of the following: a) “This application is for the Mandatory Component 1 and Optional Component 2, 3 or 4 (select the appropriate single Optional component) or b) This application is for the Mandatory Component, Optional Component 2, 3, 4 (select the appropriate single Optional component and Optional Component 5 (Coordinator of the Outbreak Analytics and Disease Modeling Network)".

Applications must address all of the strategies included in the relevant components in the Project Narratives, Work Plans and Budget Narratives as described below. The Project Narratives, Work Plans and Budget narratives should address the strategies specified for each component in the Project Abstract Summary.

Work proposed by an applicant can be complementary to, but must not be duplicative of, work funded through any other mechanism or source during the period of performance.

Component Funding: A component is a set of activities with an associated budget. CDC will use component funding for activities proposed in an application that received merit review but were not selected for funding in the initial award but may be funded at a later point in the budget period as programmatically necessary and as funding becomes available. This is particularly relevant for the Mandatory Component 1 where response implementation activities, consistent with the terms of this cooperative agreement may be funded via post-award supplements should infectious disease threats warrant. This would be in addition to a base level of funding for the Mandatory Component 1 that supports foundational activities. Please review the following key points about component funding:

Each component must be a discrete set of activities with an associated budget. Distinguishable component budget narratives are required, in addition to the budget for the base level of funding for the Mandatory Component.

Applicants should submit the anticipated components on an SF-424A form as part of their application which shows all components for the budget period.

Any component which is not funded at the time of a new award may be deemed "Approved but Unfunded (ABU). There is no guarantee that all components will be funded in a budget period as ABU components are subject to availability of funds and public health threats that warrant the component.

Coronavirus Disease 2019 (COVID-19) Funds: A recipient of a grant or cooperative agreement awarded by the Department of Health and Human Services (HHS) with funds made available under the Coronavirus Preparedness and Response Supplemental Appropriations Act, 2020 (P.L. 116-123); the Coronavirus Aid, Relief, and Economic Security Act, 2020 (the “CARES Act”) (P.L. 116-136); the Paycheck Protection Program and Health Care Enhancement Act (P.L. 116-139); the Consolidated Appropriations Act and the Coronavirus Response and Relief Supplement Appropriations Act, 2021 (P.L. 116-260) and/or the American Rescue Plan of 2021 [P.L. 117-2] agrees, as applicable to the award, to: 1) comply with existing and/or future directives and guidance from the Secretary regarding control of the spread of COVID-19; 2) in consultation and coordination with HHS, provide, commensurate with the condition of the individual, COVID-19 patient care regardless of the individual’s home jurisdiction and/or appropriate public health measures (e.g., social distancing, home isolation); and 3) assist the United States Government in the implementation and enforcement of federal orders related to quarantine and isolation.

In addition, to the extent applicable, Recipient will comply with Section 18115 of the CARES Act, with respect to the reporting to the HHS Secretary of results of tests intended to…