Opportunity Information: Apply for RFA CK 11 006
Apply for RFA CK 11 006
- The Centers for Disease Control and Prevention in the health sector is offering a public funding opportunity titled "Combining Subjective and Objective Methods for Quantifying Contact Rates and Mixing Pattern in School Aged Children" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.283 Centers for Disease Control and PreventionInvestigations and Technical Assistance.
- This funding opportunity was created on Feb 9, 2011 and posted on Dec 21, 2010.
- Applicants must submit their applications by Mar 7, 2011 On time submission requires that electronic applications be error free and made available to CDC for processing from eRA Commons on or before the deadline date. Applications must be submitted to and validated successfully by Grants.gov/eRA Commons no later than 500 PM Eastern Time. Note.HHS/CDC grant submission procedures do not provide a period of time beyond the application due date to correct any error or warning notices of noncompliance with application instructions that are identified by Grants.gov or eRA systems (i.e., error correction window).. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The number of recipients for this funding is limited to 4 candidate(s).
- Eligible applicants include: Unrestricted (i.e., open to any type of entity above), subject to any clarification in text field entitled Additional Information on Eligibility.
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Opportunity Summary:
This CDC funding opportunity (RFA CK 11 006), titled "Combining Subjective and Objective Methods for Quantifying Contact Rates and Mixing Pattern in School Aged Children," was a discretionary cooperative agreement intended to support research that measures how school-aged children interact with other people in the course of everyday life. The central idea is that infectious diseases spread through human contact, and models that predict transmission (and evaluate prevention strategies) depend heavily on how accurately we can estimate real-world contact rates and mixing patterns. By funding studies that capture these patterns more precisely, CDC aimed to strengthen the evidence base used to design and target disease prevention and control strategies, particularly those relevant to schools and other child-centered environments.
The research focus is on quantifying age-specific, individual-level social contacts and "mixing" (who interacts with whom, how often, and in what contexts) as children move within and across multiple community settings. The announcement explicitly highlights settings such as schools, homes, dormitories, and broader community locations. This emphasis reflects the fact that children do not stay in a single environment: their contact networks change over the day and week, and those shifts can meaningfully affect transmission dynamics. The funded work was expected to characterize these movements and interactions in a way that allows modelers to parameterize disease transmission models with more realistic assumptions about contact structure across ages and locations.
A distinctive feature of the opportunity is its push to combine subjective and objective measurement approaches. Subjective methods generally include self-reported or proxy-reported tools such as contact diaries, surveys, interviews, or logs where participants record encounters and contextual details (for example, duration, setting, relationship, or perceived closeness). Objective methods refer to approaches that can capture interaction patterns with less reliance on memory or interpretation, often using instruments or technologies capable of recording proximity or co-location. The goal was not simply to pick one method over another, but to integrate established techniques with newer approaches in order to improve accuracy, address known biases in self-reporting, and capture aspects of contact behavior that are difficult to measure through recall alone. In practical terms, this kind of combined-method design can help reconcile discrepancies between what participants remember and what actually occurs, and can produce richer data sets for model calibration.
Administratively, the program was offered by the Centers for Disease Control and Prevention under CFDA 93.283 (CDC Investigations and Technical Assistance). The funding instrument was a cooperative agreement, which typically signals substantial programmatic involvement by the agency compared with a standard grant. While the specific dollar amounts were not listed in the provided fields (award ceiling and floor both shown as 0), the opportunity anticipated making around four awards. Cost sharing or matching was not required, and eligibility was listed as unrestricted (open to any type of entity), subject to any additional eligibility clarifications in the full text of the announcement.
The timeline indicates the opportunity was posted on December 21, 2010, with an application deadline (original and current closing date) of March 7, 2011, and an archive date of April 6, 2011. Applications had to be submitted electronically through Grants.gov and validated through eRA Commons by 5:00 PM Eastern Time on the due date. The notice also stressed a strict submission policy: applications needed to be error-free and successfully validated by the deadline, with no additional "error correction window" after submission. For technical issues accessing the full announcement, applicants were directed to CDC's Procurement and Grants Office (PGO), Technical Information and Management Section (TIMS), with a phone contact provided.
Overall, the opportunity was designed to improve the empirical foundation of infectious disease transmission modeling by producing higher-quality, age-specific contact data for school-aged children across the environments where they live and interact. By explicitly encouraging the combination of subjective and objective measurement strategies, the program sought more reliable and nuanced estimates of contact rates and mixing patterns, which are critical inputs for evaluating interventions like vaccination strategies, school-based mitigation measures, and community-level disease control planning.
Frequently Asked Questions (FAQs)
What is the title of this CDC funding opportunity?
The opportunity is titled "Combining Subjective and Objective Methods for Quantifying Contact Rates and Mixing Pattern in School Aged Children."
What is the opportunity number (RFA) for this announcement?
The CDC announcement is RFA CK 11 006.
What type of funding mechanism is this?
This was a discretionary cooperative agreement. A cooperative agreement typically means CDC expected substantial programmatic involvement compared with a standard grant.
What CDC program or CFDA listing is associated with this funding?
The opportunity was offered under CFDA 93.283, "CDC Investigations and Technical Assistance."
What was the main purpose of the funded research?
The purpose was to support research that measures how school-aged children interact with other people during everyday life, so that infectious disease transmission models can use more accurate estimates of real-world contact rates and mixing patterns.
Why does CDC emphasize contact rates and mixing patterns?
Infectious diseases spread through human contact. Models that predict transmission and evaluate prevention strategies depend heavily on how accurately real-world contact rates and "who mixes with whom" patterns are estimated. Better measurements strengthen the evidence base used to design and target prevention and control strategies.
What population is the focus of the research?
The focus is on school-aged children, with an emphasis on quantifying age-specific, individual-level social contacts and mixing patterns.
What does "mixing patterns" mean in this context?
"Mixing patterns" refers to who interacts with whom, how often interactions occur, and in what contexts or settings those interactions take place.
What kinds of settings were highlighted for measuring contacts?
The announcement highlights multiple community settings where children interact, including schools, homes, dormitories, and broader community locations.
Why does the opportunity stress measuring contacts across multiple settings?
Children do not remain in a single environment. Their contact networks shift across the day and week as they move among school, home, and other community locations, and those shifts can significantly affect transmission dynamics.
What kinds of data were studies expected to generate?
Studies were expected to characterize movements and interactions in ways that allow modelers to parameterize disease transmission models with more realistic assumptions about contact structure across ages and locations.
What is meant by combining "subjective" and "objective" methods?
The opportunity encouraged projects to integrate self-reported (subjective) approaches with instrument- or technology-based (objective) approaches to improve the accuracy and completeness of contact measurement.
What are examples of subjective methods mentioned or implied in the announcement?
Subjective methods include self-reported or proxy-reported tools such as contact diaries, surveys, interviews, or logs where participants record encounters and contextual details (for example, duration, setting, relationship, or perceived closeness).
What are examples of objective methods as described in the announcement?
Objective methods refer to approaches capable of recording proximity or co-location with less reliance on memory or interpretation, often using instruments or technologies that can capture interaction patterns more directly.
Why did CDC want applicants to use both subjective and objective approaches instead of only one?
The intent was to improve accuracy, address known biases in self-reporting, and capture aspects of contact behavior that are difficult to measure through recall alone. Combined-method designs can help reconcile discrepancies between what participants remember and what actually occurs and can produce richer data sets for model calibration.
How many awards were expected under this opportunity?
The opportunity anticipated making around four awards.
How much funding was available per award?
The provided fields showed an award ceiling of 0 and an award floor of 0, so specific dollar amounts were not listed in the information provided.
Was cost sharing or matching required?
No. Cost sharing or matching was not required.
Who was eligible to apply?
Eligibility was listed as unrestricted (open to any type of entity), subject to any additional eligibility clarifications in the full text of the announcement.
When was the opportunity posted?
The opportunity was posted on December 21, 2010.
What was the application deadline?
The application deadline (original and current closing date) was March 7, 2011.
What was the archive date?
The archive date was April 6, 2011.
How were applications required to be submitted?
Applications had to be submitted electronically through Grants.gov and validated through eRA Commons.
What was the submission deadline time on the due date?
Applications needed to be submitted and validated by 5:00 PM Eastern Time on the due date.
What did the announcement say about submission errors and correction time?
The notice emphasized a strict submission policy: applications needed to be error-free and successfully validated by the deadline, with no additional "error correction window" after submission.
What should applicants do if they have trouble accessing the full announcement?
For technical issues accessing the full announcement, applicants were directed to CDC's Procurement and Grants Office (PGO), Technical Information and Management Section (TIMS), with a phone contact provided in the notice.
How was CDC expecting the results to be used?
The results were intended to improve the empirical foundation for infectious disease transmission modeling by producing higher-quality, age-specific contact data for school-aged children across the environments where they live and interact.
What kinds of prevention or control strategies could this research inform?
By improving estimates of contact rates and mixing patterns, the data could support evaluation and targeting of interventions such as vaccination strategies, school-based mitigation measures, and community-level disease control planning.
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