Using Data Linkage to Understand Suicide Attempts, Self-Harm and Unintentional Drowning Deaths (U01) | RFA CE 22 008

Opportunity Information: Apply for RFA CE 22 008

The CDC National Center for Injury Prevention and Control (NCIPC) is offering a cooperative agreement research opportunity called "Using Data Linkage to Understand Suicide Attempts, Self-Harm and Unintentional Drowning Deaths (U01)" (Funding Opportunity Number RFA CE 22 008). The goal is to fund investigator-initiated projects that use modern data science and data linkage methods to build a fuller, real-world picture of what happens before, during, and after serious injury events, with a specific focus on one of two topics: (1) suicide attempts and/or intentional self-harm, or (2) unintentional drowning deaths. The basic premise is that injury events and outcomes are documented across many separate systems that rarely talk to each other, and linking those systems can reveal patterns in risk and protective factors that are hard to see when each dataset is analyzed in isolation.

The opportunity centers on linking existing datasets that capture different stages of an incident and its consequences. For example, EMS and 911-related records may describe what was observed at the scene and the immediate circumstances, police reports may add situational details or contributing factors, hospital and emergency department records capture clinical diagnoses, injury severity, and treatment, and vital statistics can confirm deaths and causes. Other systems, such as behavioral health service utilization or follow-up records, can shed light on what happens after an emergency visit or hospitalization. Because each dataset is collected by different organizations at different times, and stored in separate databases, it is often impossible to track a single event across systems or understand longer-term outcomes and recurrence (such as repeated suicide attempts). This funding call is meant to support projects that overcome those barriers using rigorous linkage approaches.

Applicants are encouraged to use and advance linkage techniques and tools, including deterministic linkage (exact or rules-based matching), probabilistic linkage (statistical matching when identifiers are imperfect), and more advanced approaches such as clustering or neural network-based methods. The intent is not only to connect records but to do it in a way that is defensible, reproducible, and useful for public health decision-making. Strong proposals would make clear how linkage quality will be assessed (for example, match rates, error rates, sensitivity analyses), how missing or inconsistent identifiers will be handled, and how privacy and data security will be maintained while still producing actionable findings.

NCIPC highlights the value of datasets that provide structured, comprehensive information with enough context to identify risk and protective factors and connect them to medical outcomes. Beyond clinical endpoints, the CDC is also interested in analyses that can estimate economic consequences, including non-medical costs like productivity loss and work loss, not just direct medical spending. In other words, projects that can connect circumstances and exposures to both health outcomes and economic impacts are especially aligned with what the program is trying to achieve. The research is expected to help states and communities prioritize prevention strategies by showing which factors are most strongly associated with severe outcomes, repeat events, or death, and where protective factors may be leveraged.

A notable emphasis in the announcement is on inclusivity across populations. NCIPC is particularly interested in research that includes all populations within the linked data environment so that sub-populations with high rates of suicide attempts, subsequent suicide, re-attempts, or unintentional drowning deaths can be identified and compared to groups experiencing lower rates. This signals an expectation that applicants will think carefully about how their linked data will capture demographic, geographic, and social differences, and how analyses will avoid inadvertently excluding groups that are often undercounted or inconsistently recorded across systems. The ultimate payoff is the ability to detect disparities, understand them in context, and better target prevention efforts.

The CDC also explicitly leaves the door open to integrating non-traditional data sources to deepen measurement of potential drivers or protective conditions. Examples mentioned include social media data to explore suicide attempt contagion and community-level information like local swim lesson availability to better understand drowning risk. The broader point is that traditional injury datasets may document the event and clinical outcome well but may not capture upstream context, community conditions, or exposure environments. Thoughtful integration of these additional sources, when feasible and ethical, could strengthen the analytic story and produce more practical prevention insights.

From an administrative standpoint, this is a discretionary funding opportunity using a cooperative agreement mechanism (U01), meaning awardees should expect substantial involvement from CDC staff compared to a standard grant. The program sits under HHS/CDC, CFDA 93.136. The maximum award amount listed is $350,000, and CDC expected to make about 2 awards under this announcement. Eligibility is broad and includes various levels of government, public and private higher education institutions, tribal governments and organizations, nonprofits (including both 501(c)(3) and non-501(c)(3)), for-profit organizations (other than small businesses), and small businesses, with the note that eligibility is essentially open across many entity types subject to any clarifications in the official notice. The announcement was created December 27, 2021, with an original application deadline of March 8, 2022 (applications due by 5:00 pm ET).

Overall, this opportunity is aimed at building stronger evidence for injury prevention by creating linked, multi-source data that can clarify circumstances, severity, outcomes, recurrence, and costs for either suicide attempts/intentional self-harm or unintentional drowning deaths. The expected end product is not just a technical demonstration of linkage, but a set of findings that help public health and community partners decide what to change, where to intervene, and which protective factors to strengthen in order to prevent injuries and save lives.

• The Department of Health and Human Services, Centers for Disease Control and Prevention - ERA in the health sector is offering a public funding opportunity titled "Using Data Linkage to Understand Suicide Attempts, Self-Harm and Unintentional Drowning Deaths (U01)" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.136.
• This funding opportunity was created on Dec 27, 2021.
• Applicants must submit their applications by Mar 08, 2022 Electronically submitted applications must be submitted no later than 500 pm ET on the listed application due date.. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Each selected applicant is eligible to receive up to $350,000.00 in funding.
• The number of recipients for this funding is limited to 2 candidate(s).
• Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For profit organizations other than small businesses, Small businesses, Others (see text field entitled Additional Information on Eligibility for clarification), 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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