BAA_solicitation_Final_to_FBO.docx

CENTERS FOR DISEASE CONTROL AND PREVENTION (CDC)

Applied Research to Address Emerging Public Health Priorities

BROAD AGENCY ANNOUNCEMENT (BAA)

FY2017-OADS-01

TABLE OF CONTENTS

Section Page

PART 1 - INTRODUCTION 3

PART ll - RESEARCH INTERESTS 11

PART lll - WHITE PAPER SUBMISSION 33

PART lV - PROPOSAL PREPARATION AND SUBMISSION 35

General Information 35

Proposal Preparation Instructions 40

Cost Section Contents 44

PART V - PROPOSAL EVALUATION 45

PART VI - PROPOSAL FORMS 47

PART I - INTRODUCTION

Authority

The Centers for Disease Control and Prevention (CDC), the Office of the Associate Director for Science (OADS) issues this Broad Agency Announcement (BAA) under the provisions of FAR 35.016 and FAR 6.102(d)(2) which provides for the competitive selection of research proposals. Contracts that are awarded based on responses to this BAA are as a result of full and open competition and therefore in full compliance with the provisions of PL 98-369, "The Competition in Contracting Act of 1984."

CDC contracts with educational institutions, nonprofit organizations, state and local government, and private industry for research and development (R&D) in those areas covered in Part II of this BAA. The government reserves the right to make multiple awards under this announcement.

Process

The following four-step sequence is established for offerors contemplating submission of a proposal under this BAA. This sequence allows for an early determination of the potential for interest based on technical merit, applicability to CDC and projected funding. This process is designed to limit offeror and Government expenditure of effort to prepare and review formal proposals for research that may have little chance of being supported.

Funding of research within CDC will be determined by funding availability and research priorities set during each budget cycle. White papers can be submitted without prior approval/invitation. However, those interested in one or more of the specified research areas are encouraged to contact the CDC BAA Technical Coordinator for general BAA questions or the Subject Matter Expert (SME) Technical Point of Contact (POC) as noted below to determine whether the research addresses programmatic needs and to ask clarifying questions. For all email inquiries to the Subject Matter Expert Technical POC, copy the CDC BAA Technical Coordinator on all emails.

BAA POINTS OF CONTACT

CDC BAA Technical Coordinator is Mim Kelly, PhD, MKelly2@cdc.gov

CDC Contracting Officer Representative is Alan Kotch, MBA, AKotch@cdc.gov

CDC Contractual POC is Leonard (Mac) Mutter, BBA, LMutter@cdc.gov

Step 1 – Email Contact (Technical Dialogue)

This step initiates a technical dialogue between the Government and the potential offeror. Investigators interested in having scientific discussions with the subject matter expert (SME) point of contact (POC) and the BAA Technical Coordinator are encouraged to send an email to both CDC contacts requesting a technical discussion. The email request should also summarize the intended research proposal in order to facilitate the discussion for programmatic alignment. The scientific points of contact for each area of research interest identified in Part II are provided below:

Email

Area of Interest #1: New Diagnostic, Sequencing, and Metagenomic Tools for AR Detection and Improved Antibiotic Use

Area of Interest #2: International Transmission, Colonization, and Prevention of AR Pathogens

Area of Interest #3: Domestic Transmission, Colonization, and Prevention of AR Pathogens and CDI

3.9 Natural history of Clostridium difficile carriage or multidrug resistant organism (MDRO) gram-negative pathogen carriage

Justin O’Hagan JOHagan@cdc.gov

Area of Interest #4: Microbiome Disruption

Area of Interest #5: Antibiotic resistant pathogens and genes in water systems and the environment and their contribution to human infections

AKirby@cdc.gov

5.3 Antibiotic use as a crop pesticide on the presence of antibiotic resistance genes and pathogens on the farm

5.5 The development of resistant Aspergillus Fumigatus: connections between human health and the environment

5.6 The Emergence of Candida Auris and potential environmental sources

Area of Interest #6: Medication Safety and Antibiotic Stewardship

Area of Interest #7: Improving the Timeliness Accuracy, and Usability of Public Health Emergency Management, Surveillance, Survey Information and Data

7.1 Develop solutions to inform and simplify the process of collecting timely, accurate, and usable public health surveillance and survey data.

Paula Braun

PABraun@cdc.gov

7.2 Develop modular public health surveillance systems that promote interoperability and which can be deployed and maintained in resource-poor environments.

7.3 Develop solutions to improve the secure transmission of surveillance and survey data from public health partners to CDC and from CDC back to public health partners.

Jim Nasr

JNasr@cdc.gov

PBraun@cdc.gov

7.5 Develop and apply advanced methods for analyzing unstructured and free-form text to identify and obtain contextual information about events of public health significance (e.g., deaths due to specific types of drugs used).

Jim Nasr

JNasr@cdc.gov

7.6 Develop and apply advanced methods to improve CDC’s ability to apply existing coding rules (e.g., ICD-10 World Health Organization Coding rules) to textual data received by CDC.

Paula Braun

PABraun@cdc.gov

7.7 Develop solutions to improve the timely dissemination of public health data sets to the general public.

Jim Nasr

JNasr@cdc.gov

JNasr@cdc.gov

7.9 Develop or repurpose existing public health tools (e.g., Epi Info) to be used in places with limited network connectivity or limited resources for commercial software and professional IT support.

Asad Islam

MIslam@cdc.gov

7.10 Develop solutions to strengthen death investigation and surveillance systems.

Paula Braun

PABraun@cdc.gov

EMeeks@cdc.gov

7.12 Develop and deploy a system using the latest technology, best of breed software components, and a dynamic, interoperable architecture that will allow public health programs and surveillance systems to directly integrate with the system to transport messages and exchange data between CDC, public health agencies and labs, and healthcare providers.

Emory Meeks

EMeeks@cdc.gov

7.13 Multiple public health surveillance systems collect data from the same CDC partners within health departments without coordination. These independent interactions result in a disparate variety of public health questions asked, data elements collected and IT messaging standards used. CDC requires shared services that will enable public health programs to more quickly and efficiently use surveillance data. The platform will develop a core set of services responsive to allow for existing surveillance systems to elect to use the platform and migrate its data collection activities. Responses will be considered from multiple offerors to support services that will run on the platform.

Teresa Kinley

TKinley@cdc.gov

7.14 Develop risk assessment and decision support tools and models that allow dynamic selection and weighting of scope, scale, and PH capacity variables to deliver a rapid quantifiable estimate of risk and mitigation options associated with possible courses-of-action.

Jim Tyson

JTyson@cdc.gov

7.15 Optimize and improve distribution and sharing of Public Health and Emergency Management information to improve Task Force synchronization and Incident Management thru the use of Knowledge Management Portals. Provide anytime, anywhere, immediate access to critical information and knowledge (think WIFI Touch Screen Monitors on the wall capable of linking and providing frequently requested services or information in real-time).

Jim Tyson

JTyson@cdc.gov

7.16 Develop Augmented Reality or Virtual Systems to improve asynchronous access and knowledge augmentation of public health analytics, Geospatial products, and delivery of just-in-time learning and reference data and information via knowledge repositories.

Jim Tyson

JTyson@cdc.gov

7.17 Develop real-time automated text and audio language translation capabilities utilizing mobile devices.

Jim Tyson

JTyson@cdc.gov

7.18 Develop data processing capabilities to analyze satellite imagery or remote sensing data for public health indicators related to vulnerable populations, environmental factors, and population dynamics.

Jim Tyson

JTyson@cdc.gov

7.19 Develop Natural Language processing capabilities to mine and translate emoticons, video, graphics, photos, and other types of multimedia components in social media. The purpose is to derive sentiment (anger, depression, worry, happiness, etc.), criticality (need, scope, scale, immediacy, etc.), and contextual information (contextual background data and info from in images, videos, emoticons related to disease or public health threat.

Jim Tyson

JTyson@cdc.gov

Step 2 - White Paper Submission

This step is a continuation of the technical dialogue for projects of interest. Submission of a white paper does not require an explicit request or invitation from CDC. However, if sufficient interest is determined based on the technical dialogue discussion, the scientific point of contact may suggest submission of a white paper no more than 4 pages in length (exclusive of resumes, references and diagrams) to facilitate their understanding of the scientific and technical aspects of the proposed research project. Review of the white papers is intended to determine which projects are scientifically sound and are consistent with programmatic priorities at CDC. White papers should specifically address and provide a technical solution to one of the areas of interest subtopics listed in the BAA. White papers will be used to determine those projects that receive an invitation to submit a formal research proposal as described in Part IV; therefore, informal white papers should not be so lengthy or detailed as to constitute a formal proposal (see Part IV). White papers should contain a Rough Order of Magnitude estimate (Estimated Cost) to perform the work described.

White papers should reflect a high-level solution to one or more of the problems (areas of interest subtopics) stated in Part II of the BAA. Projects need to be scaled for a 12 month period of performance and should represent a standalone project with clear deliverables at the end of the 12 months. For projects that lend themselves to extended tasks beyond the initial 12 months, option years may be proposed. Option years will be considered based on programmatic fit and the availability of funds.

The technical dialogue can continue during the white paper phase and program staff may contact offerors with questions or clarifications. All submitted papers will undergo an initial review for technical merit and program applicability. The technical review team may discuss the proposed project with the potential offeror, as required, to facilitate the Government’s understanding of the scientific and technical aspects of the proposed research project. Offerors are instructed to check FedBizOps during the white paper period for any updates or modifications to the current solicitation.

Specific information of what should be included in the white papers can be found in Part lll.

Step 3 - Research Proposal Submission

If there is sufficient interest in a proposed research project, the Contracting Officer will officially invite the offeror to submit a research proposal (see Part IV). Once invitations for full proposals are distributed, the technical dialogue period ends. Communication between scientific personnel and the offeror is permitted only as authorized by the Contracting Officer. Details about the proposal preparation and submission process can be found in Part IV.

Step 4 - Contract Award

Following the proposal evaluation and negotiation, the Contracting Officer will notify the offeror, in writing, whether the proposal will be processed for award. The primary basis for selecting proposals for award shall be scientific rigor/technical merit, importance to programmatic priorities, and organizational capacity. Cost will be evaluated as a factor in every proposal review. Past performance will also be considered. See Part V for specific evaluation criteria.

Government Obligation of Funds

Persons submitting white papers and proposals are cautioned that only a Contracting Officer may obligate the Government to a contract involving expenditure of Government funds. The Government is under no obligation to pay for the cost of a white paper or proposal. There is no commitment on behalf of the Government to fund any proposal. Interested parties are cautioned that the submission of a white paper and a proposal is submitted strictly on a voluntary basis.

PART II - CDC RESEARCH INTERESTS

Overview

The Centers for Disease Control and Prevention (CDC) works to protect the U.S. from health, safety and security threats, both foreign and domestic. Specifically, CDC works with its partners to monitor health, detect and investigate health problems, conduct research to enhance and implement prevention strategies, develop and promote sound public health policies, promote healthy behaviors, foster safe and healthful environments, respond to current and emerging threats, and provide public health leadership and training.

CDC’s role as the nation’s health protection agency is to operate 24/7 in order to keep people healthy and safe. The agency accomplishes this goal by working to: detect and respond to new and emerging health threats; address the biggest health problems causing death and disability; move science and advanced technology into actions to prevent disease; promote health and safe behaviors, communities and environments; develop leaders by training the public health workforce; and understand the health pulse of the nation.

For this announcement, CDC has identified the following research areas of interest:

1. New diagnostic, sequencing and metagenomic tools for antibiotic detection and improved antibiotic use

2. International Transmission, colonization, and prevention of antibiotic resistance (AR) pathogens

3. Domestic transmission, colonization, and prevention of antibiotic resistance pathogens and Clostridium difficile infections (CDI)

4. Microbiome disruption

5. Antibiotic resistance pathogens and genes in water systems and the environment and their contribution to human infections

6. Medication safety and antibiotic stewardship

7. Improving the timeliness, accuracy, and usability of public health emergency management, surveillance and survey information data

Interested parties are invited to consider innovative approaches to support advanced research and development strategies in the following research areas of interest and specific sub-topics within each area:

Area of Interest #1: New Diagnostic, Sequencing, and Metagenomic Tools for Antibiotic Resistance Detection and Improved Antibiotic Use

1.1 Development and evaluation of new diagnostic tools to detect antibiotic resistance and antibiotic resistance markers in Neisseria Gonorrhea.

N. gonorrhea (NG) has progressively developed resistance or decreased susceptibility to multiple classes of antibiotics, including penicillins, sulphonamides, tetracyclines, quinolones, macrolides and cephalosporins (CDC, 2014, Disease Surveillance profile. WHO, 2011, WHO/RHR/11.14). In line with the rapidly changing resistance profile of NG, identification of antibiotic susceptibility of NG at the point-of-care (POC) is essential for recommending personalized treatment strategies.

Nucleic acid amplification tests (NAATs) are currently used for identification of NG from clinical specimens (2000-present), however the technology to determine antibiotic resistance independent of culture is not yet commercially available. As advances are made in the whole genome sequencing of the organisms and the characterization of antimicrobial resistance determinants, fast and accurate molecular assays to detect antimicrobial resistant NG are needed to provide an alternative to the conventional culture-based antimicrobial susceptibility testing that are laborious and time-consuming.

CDC seeks to support the development and evaluation of a rapid molecular assay for the simultaneous detection of NG and antibiotic resistance markers from clinical specimens. Such an assay/s could be useful in predicting antimicrobial resistant gonococcal strains in order to support outbreak investigations and enhance surveillance of antimicrobial resistant NG. Ultimately, they may also be useful for diagnostic applications and in guiding individual patient management.

The expectation is that applicants work with clinical sites to obtain MIC data and the remnants of NG-positive NAAT samples from male and female urogenital, rectal and oropharyngeal specimens for assay development and evaluation. The presence and abundance of NG and commensal Neisseria spp. within the samples from different anatomical sites and different stages of infection are anticipated to vary and, thus may require additional optimization and evaluation of the assay.

· Development and evaluation of rapid molecular assay for detection of NG and antibiotic resistance markers in clinical specimens

· Focus is to include the following antibiotics: cephalosporins (ceftriaxone, cefixime), quinolones (ciprofloxacin), macrolides (azithromycin)

· Selection of predictive variants

· Assay design, detection technology, and instrumentation

· Validation of sensitivity and specificity in identifying the gonococcal strains with decreased susceptibility or resistant to antibiotics above.

· Evaluation and optimization of the assay performance for specimens from different anatomical sites.

1.2 High-throughput Targeted Sequencing of Antimicrobial Resistance Determinants from Complex Metagenomic Samples.

The rapid characterization of the resistome (the set of all antibiotic resistance genes in both pathogenic and non-pathogenic bacteria found in a sample) of complex metagenomic samples has broad applications for medicine, public health, environmental monitoring, and food safety. Next-generation sequencing capacity is increasing across local, state, and federal agencies charged with detecting and mitigating antimicrobial resistance (AMR), but there is not yet a scalable, comprehensive method for detecting AMR determinants in complex microbial communities like those encountered in stool and environmental samples. Targeted sequencing of AMR determinants using primers to amplify them before sequencing greatly reduces the amount of sequencing effort required to detect even relatively rare determinants. CDC seeks the creation of a resource accessible to both public and private organizations engaged in AMR surveillance and mitigation that supports the high-throughput, low cost, and short turnaround time necessary for an effective response when AMR is detected. Specific goals include:

· Cataloging the known, validated AMR genetic determinants and designing broadly conserved primers to detect those regions. Primers should be designed in such a way as to be adaptable to the major sequencing platforms in use at laboratories.

· Validating the primers in the wet lab. A successful project will demonstrate that the primers are functional in vitro.

· Establishing a freely available online resource for the publication of methods, source materials, and the primers. Furthermore, procedures should be established for the ongoing expansion of the resource as additional AMR determinants are validated and new technologies become available.

1.3 Bioinformatic Sorting of Mutational Resistance Determinants in Mixed Infections Housekeeping gene mutations are one of the sources of antimicrobial resistance (AMR) in foodborne bacterial pathogens. Currently, isolates are sequenced to obtain genome sequences in which mutational resistance determinants can be found and tracked, along with other subtyping information. However, the declining availability of pathogen isolates is forcing a shift to methods that can obtain the same data from clinical specimens like blood, sputum, and stool. The amplification of multilocus sequence typing (MLST) targets from metagenomic DNA samples is one of the most promising methods for outbreak surveillance. It scales well to different numbers of targets, requires no a priori knowledge of the genome of the pathogen, and facilitates communication between labs by using a consistent set of markers. Like the current shotgun-based approach, extended MLST will provide a rich dataset containing both mutational resistance determinants and strain level subtyping. However, infections caused by multiple strains of the same pathogen and infections with pathogens closely related to commensal bacteria cannot be effectively typed by MLST used on metagenomics samples, because the individual amplicons cannot be linked to separate strains. CDC seeks the development of a bioinformatic tool that can be used to sort MLST data obtained from mixed, closely related strains. A successful tool will be able to accomplish the following:

· Identify the MLST alleles occurring in raw or minimally processed sequencing data using a reference database of known alleles.

· Use a statistical model to identify within some confidence interval the number of strains present in the sample and the strain of origin of each allele present.

· Scale to perform these tasks with an MLST scheme containing hundreds or thousands of loci in a manner compatible with both the available CDC computing resources and the time-sensitive nature of outbreak investigations.

· Demonstrate tool efficacy using data generated from known bacterial mixtures provided by CDC.

1.4 Establishing a Biobank of Healthy Stool Samples with Well Curated Antimicrobial Use Data

Background antimicrobial resistance element content in the healthy stools of the general population is not well understood. Both pathogen subtyping and AMR assays, in particular quantitative assays, need to be validated against a representative set of healthy stool samples that accurately reflect the general population. Without this validation, the significance of AMR frequency cannot be accurately assessed. Although microbiome-oriented biobanks exist, current challenges include small sample sizes (<1 mL), lack of population representativeness, lack of antimicrobial use metadata, and limited accessibility by other laboratories. CDC seeks to support existing and emerging biobanks in collecting and curating bulk stool samples along with detailed antimicrobial use data from healthy individuals of varying age, ethnicity, diet, and lifestyle. Specific goals include:

· Collecting large quantity samples (>200 mL) from individuals. Bulk samples are needed to allow extraction of sufficient DNA for amplicon and metagenomics assays, as well as experimental replicates for validation.

· Representative population sampling. Collecting sufficient numbers of samples across a representative range of the population, especially children, the elderly, and other underserved populations, is important, as these are groups typically vulnerable to foodborne illness.

· Collecting well-curated metadata on antimicrobial use in these healthy individuals.

· Establishing broad access. CDC collaborates with a number of different institutions, agencies, and other laboratories. A central resource for gathering and sharing samples would encourage further collaboration.

1.5 Improving and Maintaining Molecular Detection of AR for Public Health

Although there are several databases that catalogue most or all genetic sequences of currently known antibiotic resistant determinants, there are outstanding needs to collate, adapt, update, and maintain one consensus database for public health purposes. In addition, it is important to quickly translate new discovery of determinants into public health action, including checking whether current assay primer sets will detect them and determining how genotypes effect phenotype. CDC is interested in studies in each of the following areas:

· Merge the major AR gene databases (e.g., Resfinder, ARG-ANNOT, CARD, Lahey/NCBI) to build a curated database of AR genes for launch and maintenance by the CDC . Currently there is no single database that pulls, verifies, and curates all reported AR genes. This would include removal redundant genes and non-AR genes, and exclude partial genes Either CDC or the recipient could add a “threat level” to each AR gene in terms of public health concern

· Develop two tools to ensure we are able to detect newly identified AR determinants and variants of known alleles

· A tool to scan existing databases and flag newly reported AR determinants and variants of known alleles

· A tool to test in silico the performance of our PCR and RT-PCR primers

· Develop an algorithm for correlating genotype with phenotype for certain highest threat-level resistance-species phenotypes

1.6 Utilizing Recombination Events in Tracking Transmission of AR Pathogens

Increasing application of whole genomic sequencing to public health has made it possible to track person-to-person transmission of antibiotic resistant organisms like never before. The principal current method for tracking such transmission events that are close in span across the ‘evolutionary time clock’ is single nucleotide polymorphism (SNP) or variant (SNV) within a core genome. However, recombination is another event that may occur quickly in evolutionary time and yet go uncaptured in current transmission analysis pipelines. This sub-focus is for the development of a sophisticated algorithm for identifying recombination events in WGS data that can be worked into existing pipelines for SNP analysis.

1.7 Using Whole Genomic Sequence Data to Develop an Inter-facility Transmission Index for Clostridium difficile Across a Region

Current state-of-the-art methods for determining the transmission of multidrug-resistant organisms (MDROs) between facilities within a region include outbreak investigations of emerging MDRO clinical isolates and/or active admission and discharge screening of patients colonized by endemic MDROs (or some combination of the two), followed by whole-genomic sequencing (WGS) with single nucleotide polymorphism (SNP) analysis. An alternative approach with a highly endemic MDRO such as Clostridium difficile may be to use a combination of phylogenetic analysis combined with SNP analysis to determine a WGS-derived ‘transmission index’ based upon a systematic sample of clinical isolates alone. Use WGS on an existing comprehensive collection of clinical isolates of C. difficile from multiple healthcare facilities and outpatient settings across a region to determine relationships between isolates that reflect likely inter-facility transmission and directionality of the flow of strains across the continuum of care. Investigate the minimum number of isolates necessary from each facility or setting necessary to reliably determine inter-facility transmission pathways. Consider validation of patient flow and transmission pathways via either individual patient chart review for detailed outpatient and inpatient care histories or the use of additional data sources for network analysis as described in Area of Interest #3, Section 3.2.

1.8 Comprehensive Study of Multidrug Resistance Determinants and Drivers in the Major Fungal Pathogen Candida glabrata

Among cases of candidemia, those caused by Candida glabrata can be some of the most challenging to manage owing to the frequency of resistance that occurs in this species. While resistance to azoles has been a longstanding problem with a prevalence that varies geographically, resistance to the echinocandins, which were introduced in the 1990s, is also rising in several institutions. The recent emergence of isolates with acquired resistance to both classes of agents is a major concern since alternative therapeutic options are scarce. Studies are need to better understand the molecular epidemiology of echinocandin resistance:

· Based on current understanding of the prevalence of drug resistance determinants (mutations in FKS1/2 and PDR1) and drivers (mutations in MSH2) in Candida glabrata, and the genomic lineages (based on whole genomic sequence data) of major C. glabrata clades, complete development and validation of a novel diagnostic platform for rapid identification of echinocandin-‐resistant C. glabrata strains.

Area of interest #2: International Transmission, Colonization, and Prevention of AR Pathogens

2.1 Pre and Post Travel Screening of Diverse Travelers

The prevalence of colonization with target multidrug-resistant organisms (MDROs) following travel outside the United States has not been well described. Most prior studies addressing the association between MDROs and travel have been done primarily outside the United States, targeted patrons of travel clinics, and primarily focused on the presence of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae. Further information is required on the role of importation for other MDROs including carbapenemase-producing (CP) Enteorbacteriaceae (CRE), other CP Gram-negative bacilli, Candida auris, and mcr-1 and -2-producing Enterobacteriaceae in order to improve the control of these organisms. While the current state of the art for detecting specific resistance-species phenotypes is selective culture with characterization of isolates, rapid screening with various combinations culture, molecular tests, and even metagenomics may offer favorable economies of scale and increased value to the government. Goals include:

· Further evaluate travel dynamics of AR acquisition using pre- and post-travel screening of rectal or stool samples (potentially other sites depending on organism evaluated) on diverse groups of travelers, potentially including travel clinic patrons, travelers visiting friends and relatives (VFR), and refugees (first entry only, not pre-post) entering the United States to detect the MDROs listed above.

· Propose one or more laboratory screening processes for target organisms so as to achieve greatest efficiency and value. Consider scalable processes and budgets, along with decision points for archiving subsets of specimens or portions of all specimens for later more comprehensive analysis.

· A limited post-travel questionnaire would collect a number of participant and trip characteristics including age, duration of travel, use of antimicrobials (including malaria prophylaxis), healthcare encounters during travel, countries visited, type of travel (e.g., vacation, business, VFR), presence of diarrhea, etc.

· A secondary outcome if logistics and funding allow would be to follow colonized participants monthly to identify if colonized travelers develop a clinical infection with the organism and the duration of colonization.

2.2 Detect and characterize transmission of multi-drug resistant bacteria in global settings to understand the potential global transmission dynamics of spread.

Novel strains of multi-drug resistant bacteria have been increasingly detected and reported throughout the globe. As novel strains occur, spread of these organisms from a geographical region is typically influenced by migration patterns and other factors. International travelers from the United States have been shown to have a high prevalence of colonization of resistant bacteria upon return. However, the major “hot spots” and risk factors are not well characterized.

· Conduct a study to characterize the prevalence of multi-drug resistant bacteria in one or multiple geographic regions, particularly in low- or middle-income countries. The study should provide information on the risk of transmission or colonization in the population, with data to understand the risk factors for acquiring or transmitting resistant bacteria in multiple settings. Data should inform a better understanding of disease or bacteria transmission dynamics particularly with respect to transmission to the United States.

· Data should also help to inform the local understanding of resistance patterns to guide rational antimicrobial use. Develop a predictive model to identify the geographic locations where persons are most likely to acquire resistant bacteria and subsequently transport them to the United States. Such a model may be based on migration patterns of humans and/or animals, background prevalence rates, likelihood of antimicrobial or healthcare exposure, or other pertinent factors. The model could help to identify the major geographic regions (national or sub-national) needing capacity to prevent spread of antimicrobial resistance to the US.

2.3 Development of clinical support tools to facilitate infection control and antimicrobial stewardship in resource-limited settings.

In low- and middle-income countries, the burden of AMR is substantial. However, prevention and containment of antimicrobial resistance in low- and middle-income countries is challenging typically because of limitations in the number or level of training of infection control and antibiotic stewardship staff. While training programs are essential, additional tools are needed to assist infection control staff with the daily implementation of programs aimed at preventing AMR. Furthermore, because laboratory support is inconsistent, clinical practice in acute care hospitals or outpatient settings is to initiate antibiotic therapy empirically, and only seek further diagnostics should initial treatment fail. CDC seeks the development of innovative tools intended for use in resource limited settings:

· A tablet or smartphone based clinical support tool to assist hospital staff to implement infection control precautions for patients with AMR organisms (e.g., carbapenem-resistant Enterobacteriaceae). Tool should be able to link to the facility’s AMR database (WHONet or similar) and provide support for the initiation and tracking of infection control precautions. The objective of the tool should be to enable infection control staff to quickly identify patients requiring additional infection control precautions; assist with the implementation of appropriate precautions; and assist with the collection and tracking of indicators for monitoring implementation of infection control precautions. Data should be able to be easily visualized and analyzed in real time, and reports and/or data should be able to be transmitted to appropriate public health authorities.

· A smartphone based clinical support tool to improve antibiotic use in resource-limited settings. Such a tool should be targeted at healthcare providers in multiple settings including acute care hospitals and outpatient settings. This tool should assist with the appropriate choice and administration of initial antibiotic therapy, based on local guidelines and/or antibiograms. The tool should also have the ability to link to laboratory data (e.g., WHONet), if the appropriate tests are ordered and labs are readily available, and suggest any improvements in therapy (e.g., change in therapy, discontinuation, etc.). The tool should also consider an approach to appropriate therapy with many challenges in appropriate diagnosis due to unavailability of tests such as radiography, serology, etc.

2.4 Develop tools to effectively communicate and train healthcare workers on complex infection control topics in resource limited settings.

One of the lessons learned from the Ebola epidemic in West Africa was that healthcare workers had a low level of understanding of basic infection control principles. While some healthcare workers have since been taught the proper procedures for infection prevention and control, including use of personal protective equipment (PPE), the principles of germ theory and the reasons for initiating such precautions have not been emphasized. These lessons are perhaps more important in resource-limited settings because of the intermittent or scarce availability of PPE, necessitating other means of infection control. One of the key needs identified is to teach healthcare workers how pathogens spread, in which settings carry risk of infectious disease transmission (i.e., risk assessment), and how to take steps to mitigate these risks. As such, CDC seeks the development of training and communications tools:

· Develop videos, interactive case-based training, and/ or other innovative tools targeted at healthcare workers in resource limited settings to communicate and reinforce the principles of infection control such as germ theory, risk assessment, and standard and transmission-based precautions.

· Tools should be culturally relevant for West Africa but potentially able to be applied or translated to other resource limited settings. Examples of such tools include animated videos, case-based learning, video games, or individualized eLearning.

Area of Interest #3: Domestic Transmission, Colonization, and Prevention of AR Pathogens and CDI

3.1 Detecting and Preventing Healthcare-Associated Infections (HAIs) and Antibiotic Resistant Organisms in Post-Acute and Long Term Care Facilities.

Over 4 million frail and older adults are admitted to or reside in the ~15,600 nursing homes in the U.S. annually. Older research studies estimate between 1.6 and 3.8 million healthcare-associated infections (HAIs) occur in nursing homes every year, resulting in 388,000 deaths. Limitations in infection surveillance capacity in nursing homes has prevented a reevaluation of the burden of HAIs in this setting but with the rising number of individuals receiving more complex medical care in Skilled Nursing Facilities/Nursing Homes (SNF/NHs), these numbers may underestimate the true magnitude of the problem.

CDC seeks to enhance the ability of U.S. nursing homes to detect and prevent HAIs and antibiotic resistant organisms through stronger infection prevention and surveillance capacity. CDC’s current activities in nursing homes include promotion of infection surveillance reporting capacity within the National Healthcare Safety Network (NHSN) for nursing homes, strengthening infection prevention and antibiotic stewardship infrastructure and program activities in nursing homes, and identifying innovative strategies to implement HAI and AR prevention practices, all to improve the outcomes for patients in the post-acute and long-term care setting.

CDC seeks studies designed to strengthen the capacity for tracking and preventing HAIs and antibiotic-resistance by engaging organizations with infrastructure to:

· Evaluate the acceptability, quality and validity of HAI or AR event reporting, (e.g., urinary tract or C. difficile infections) by nursing homes participating in the National Healthcare Safety Network (NHSN) Long-Term Care Facility reporting component to increase NHSN utilization by nursing home infection prevention and antibiotic stewards programs

· Building on an assessment to determine the barriers and facilitators for multidrug-resistant organisms (MDRO) and C. difficile reporting into the National Healthcare Safety Network (NHSN) by nursing homes (NHs), including facility infrastructure and infection prevention programs, propose an assessment of interventions designed to overcome barriers to reporting, strengthen infection control, and overall reduce these outcomes.

· Determine the barriers and facilitators for implementation of infection prevention practices in high-acuity skilled nursing facilities (e.g., ventilator units) to identify interventions and implementation strategies to reduce transmission of antibiotic-resistant organisms that could be evaluated in effectiveness studies. Upon successful completion of the project and pending funding availability, additional funding years might be available to implement a study to evaluate these interventions.

· Based upon recent studies of hand contamination with multidrug-resistant organisms (MDRO) and C. difficile in nursing home residents, along with pathways and consequences for said contamination, as well as a literature review for best practices toward achieving patient hand hygiene, propose an intervention study to reduce transmission and resident acquisition of MDROs and C. difficile resulting from hand contamination.

· Building on experience utilizing whole genomic sequencing (WGS) of important antibiotic resistant threat bacteria to understand transmission within and between nursing home residents in a region, propose follow on studies utilizing WGS to either better understand transmission within and between nursing homes and/or the flow of resistance into and out of the nursing home population.

3.2 Validation and Utilization of Measures of Healthcare Facility Connectedness.

Prevention of infections with multidrug-resistant organisms (MDROs) is a CDC priority. Recent studies have described an association between measures of healthcare facility connectedness, via the sharing of patients who may be colonized or infected with MDROs, and incidence of healthcare-associated infections such as Clostridium difficile infections (CDI) and carbapenem-resistant Enterobacteriaceae (CRE), even when controlling for traditional confounders. Mathematical modeling studies highlighted in the CDC’s August 2015 Vital Signs found that regionally coordinated approaches resulted in a cumulative 74% reduction in CRE acquisitions over 5 years in a 10-facility network model and a 55% reduction over 15 years in a 102-facility network model. To validate the use of measures of healthcare facility connectedness and improve accessibility of data for the administration of public health programs which take healthcare facility connectedness into consideration to prevent the spread of MDROs, CDC seeks studies to:

· Calculate measures of healthcare facility connectedness for facilities within varying regions (e.g., hospital referral regions, states, etc.) using valid data source(s) (e.g., administrative claims data) to determine the reproducibility of results.

· Validate the associations between various measures of connectedness (i.e., weighted and unweighted in/out-degree, centrality, cliques, etc.) with incidence and spread across healthcare facilities of MDROs (e.g., clinical infections identified via state or local surveillance systems, infections reported to the Centers for Medicare & Medicaid Services Hospital Compare, ICD-9-CM coded CDI), when controlling for other confounders in order to identify the optimal measures.

· Assess the incremental benefit of analyses and strategies that incorporate healthcare facility connectedness versus network-naïve analyses to identify influential facilities for preventing the regional spread of MDROs and to identify sentinel facilities for early detection of emerging healthcare-associated infections. Develop and implement techniques to incorporate time varying facility-level incidence data into a tool that would allow a ranking of facilities across a region for prioritization by the risk of incident infections for an emerging infectious disease with healthcare-associated transmission (e.g., sentinel surveillance sites) compared to the best available network-naïve methods. Develop recommendations for best practices for implementing prevention strategies based on healthcare facility connectedness.

3.3 Novel Strategies to Address Community Onset Invasive Staphylococcus aureus (SA) Staphylococcus aureus (SA) is among the most common and important causes of infectious disease in humans. Significant progress has been made in recent years in preventing hospital-acquired, invasive SA infections, including infections due to methicillin-resistant SA (MRSA); however, rates of invasive infection due to SA in community settings have not decreased to the same extent. CDC distinguishes epidemiologically between two categories of community-onset invasive SA infections: healthcare-associated community-onset infections, in which patients have a central venous catheter or prior hospitalization, nursing home residence, surgery, dialysis in the prior year; and community-associated infections, in which patients have none of the previously mentioned significant healthcare risk factors. In this area of interest, CDC seeks to develop and implement strategies for preventing invasive SA infections in the community by supporting work in the following areas:

· Use whole genome sequencing and epidemiologic analysis to determine sources of acquisition and routes of transmission of SA in cases of healthcare-associated community-onset infection

· Implement a novel strategy for prevention of invasive community-onset invasive SA infections. This could be limited to a specific subset of community-onset SA infections, e.g., infections after hospital discharge, or community-associated infections only. The strategy can be novel either because it is has never been demonstrated to have efficacy for preventing invasive SA or because it is untested in a specific population.

3.4 Randomized Controlled Trial of Treating Symptomatic Patients for CDI who are NAAT Positive but Toxin A&B Negative.

From the fulfillment of Koch’s postulates using the cell cytotoxin neutralization assay (CCNA) in the late 1970s, to the era of widespread toxin EIA testing for toxins A&B in the 1990s and early 2000s, to the recent uptake of nucleic acid amplification tests (NAAT), the diagnosis of Clostridium difficile infection (CDI) has been fraught with difficulty.