Opportunity Information: Apply for PA 15 273

  • The National Institutes of Health in the education health sector is offering a public funding opportunity titled "Harnessing Big Data to Halt HIV (R01)" and is now available to receive applicants.
  • Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.242 Mental Health Research Grants 93.279 Drug Abuse and Addiction Research Programs 93.393 Cancer Cause and Prevention Research 93.394 Cancer Detection and Diagnosis Research 93.395 Cancer Treatment Research 93.396 Cancer Biology Research 93.399 Cancer Control 93.855 Allergy and Infectious Diseases Research 93.856 Microbiology and Infectious Diseases Research.
  • This funding opportunity was created on Jun 5, 2015 and posted on Jun 5, 2015.
  • Applicants must submit their applications by May 7, 2018. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
  • Eligible applicants include: Public and State controlled institutions of higher education Native American tribal governments (Federally recognized) 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 Independent school districts For profit organizations other than small businesses Public housing authorities/Indian housing authorities Small businesses Private institutions of higher education City or township governments Others (see text field entitled Additional Information on Eligibility for clarification) County governments Native American tribal organizations (other than Federally recognized tribal governments) State governments Special district governments.
  • Other Eligible Applicants include the following Alaska Native and Native Hawaiian Serving Institutions Asian American Native American Pacific Islander Serving Institutions (AANAPISISs) Eligible Agencies of the Federal Government Faith based or Community based Organizations Hispanic serving Institutions Historically Black Colleges and Universities (HBCUs) Indian/Native American Tribal Governments (Other than Federally Recognized) Non domestic (non U.S.) Entities (Foreign Organizations) Regional Organizations Tribally Controlled Colleges and Universities (TCCUs) U.S. Territory or Possession.
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Opportunity Summary:

Harnessing Big Data to Halt HIV (R01) (Funding Opportunity Number PA 15-273) was a discretionary National Institutes of Health (NIH) grant opportunity designed to push HIV research forward by using Big Data Science to answer questions that are difficult to tackle with smaller, traditional datasets. The central goal was to fund R01 research projects that could fundamentally improve understanding of three major areas: how HIV is transmitted, how people move through the HIV care continuum (from diagnosis to linkage to care, treatment, viral suppression, and long-term retention), and how HIV interacts with other health conditions and comorbidities. The intent was not just to generate new findings, but to transform how researchers study HIV by leveraging large-scale, complex, and often messy real-world data.

The FOA emphasized end-to-end “big data” work. Applicants were expected to assemble or integrate large data sources (for example, combining clinical, behavioral, social, geographic, laboratory, pharmacy, claims, surveillance, or other high-volume datasets), then apply robust, reproducible analytic approaches that can handle scale and complexity, and finally communicate results in meaningful ways through strong visualization. In practical terms, the announcement signaled NIH’s interest in projects that go beyond standard statistical workflows and instead incorporate modern data science practices such as scalable data management, careful provenance and documentation, reproducible pipelines, and approaches that can be validated and re-used. A clear theme was that results should be credible and repeatable, which typically implies careful handling of bias, missing data, confounding, and data linkage issues, along with transparent analytic methods that others can audit or replicate.

This opportunity used the R01 grant mechanism, meaning it was aimed at full research projects with a defined set of aims, a strong investigative team, and enough scope to produce substantial, publishable advances rather than pilot-only work. It fell under health- and education-related funding activity categories and was connected to multiple CFDA program areas, reflecting how HIV-related big data research can intersect with mental health (93.242), substance use and addiction research (93.279), and a wide range of cancer-related categories (93.393 through 93.399), as well as infectious disease and microbiology research (93.855 and 93.856). That range highlights the reality that HIV research often spans comorbid conditions, coinfections, and long-term health outcomes, including cancer risks and control, mental health conditions, and substance use dynamics that affect transmission and care engagement.

Eligibility was broad and included most common research-performing organizations. Eligible applicants included public and private institutions of higher education, nonprofits with or without 501(c)(3) status, for-profit organizations other than small businesses, small businesses, independent school districts, and a wide set of government entities (city/township, county, state, special district, and public housing authorities/Indian housing authorities). Tribal governments and tribal organizations were eligible, including federally recognized tribal governments as well as other tribal entities. The FOA also explicitly called out additional eligible applicants such as Historically Black Colleges and Universities (HBCUs), Hispanic-serving institutions, Tribally Controlled Colleges and Universities (TCCUs), Alaska Native and Native Hawaiian Serving Institutions, and Asian American Native American Pacific Islander Serving Institutions (AANAPISISs), as well as faith-based or community-based organizations, regional organizations, U.S. territories or possessions, and even non-U.S. entities (foreign organizations). This broad eligibility aligns with the public health nature of HIV research and the need for diverse data sources, community connections, and multidisciplinary expertise.

From an administrative standpoint, there was no cost-sharing or matching requirement, reducing barriers for applicants who might not have institutional resources to provide matching funds. The opportunity was posted and created on June 5, 2015, with an original and final closing date of May 7, 2018, and it was archived on June 7, 2018. NIH was the sponsoring agency, and the full announcement was hosted through the NIH Grants Guide (link provided in the source). For technical issues accessing the announcement, the contact listed was the NIH Office of Extramural Research (OER) Webmaster (FBOWebmaster@OD.NIH.GOV), indicating the standard NIH pathway for help with FOA access and linking problems.

Overall, the grant call can be read as an effort to bring big data methods to real HIV challenges: identifying transmission patterns and risk networks, detecting gaps in testing and treatment, improving retention and viral suppression at the population level, and understanding how HIV interacts with other chronic conditions over time. The emphasis on assembling large datasets, performing rigorous and reproducible analyses, and delivering clear visualizations suggests NIH was looking for projects that not only answer important questions, but also build data-driven infrastructure and analytic approaches that could be re-used by the broader HIV research and public health communities.

FAQs: Harnessing Big Data to Halt HIV (R01) (PA 15-273)

What is the "Harnessing Big Data to Halt HIV (R01)" funding opportunity?

It was a discretionary National Institutes of Health (NIH) funding opportunity (Funding Opportunity Number PA 15-273) that supported R01 research projects using Big Data Science to advance HIV research in ways that are hard to achieve with smaller, traditional datasets.

What was the central goal of this FOA?

The central goal was to fund R01 projects that could fundamentally improve understanding of (1) how HIV is transmitted, (2) how people move through the HIV care continuum, and (3) how HIV interacts with other health conditions and comorbidities.

Which parts of the HIV care continuum were specifically called out?

The FOA referenced the continuum from diagnosis to linkage to care, treatment, viral suppression, and long-term retention.

What did NIH mean by "Big Data" in this context?

The FOA emphasized large-scale, complex, real-world datasets that are often messy, and it encouraged approaches that can handle data volume, variety, and complexity while still producing credible and repeatable results.

What kinds of data sources were applicants expected to use or integrate?

Applicants were expected to assemble or integrate large data sources, such as clinical, behavioral, social, geographic, laboratory, pharmacy, claims, surveillance, or other high-volume datasets.

Was the FOA focused only on analysis, or also on data assembly and integration?

It emphasized end-to-end big data work, including assembling or integrating large datasets, applying robust and reproducible analytics, and communicating results meaningfully, including through strong visualization.

What types of analytic expectations were highlighted?

The announcement highlighted robust, reproducible analytic approaches suited to scale and complexity, along with modern data science practices such as scalable data management, clear provenance and documentation, reproducible pipelines, and methods that can be validated and re-used.

Why did the FOA emphasize reproducibility and credibility?

A clear theme was that results should be credible and repeatable, which implies careful handling of bias, missing data, confounding, and data linkage issues, and using transparent analytic methods that others can audit or replicate.

Did the FOA require visualization?

It emphasized communicating results in meaningful ways through strong visualization as part of an end-to-end big data workflow.

What grant mechanism did this opportunity use?

It used the NIH R01 mechanism, intended for full research projects with defined aims, a strong investigative team, and enough scope to produce substantial, publishable advances rather than pilot-only work.

What were the main research areas this FOA aimed to improve?

The FOA focused on improving understanding of HIV transmission, the HIV care continuum, and HIV interactions with other health conditions and comorbidities.

How does this FOA connect HIV research to other health areas?

It noted that HIV-related big data research can intersect with mental health, substance use and addiction research, cancer-related categories, and infectious disease and microbiology research, reflecting HIV comorbidities, coinfections, and long-term outcomes.

Which funding activity categories were associated with this opportunity?

It fell under health- and education-related funding activity categories.

Which CFDA program areas were referenced?

The opportunity was connected to multiple CFDA program areas, including mental health (93.242), substance use and addiction research (93.279), cancer-related categories (93.393 through 93.399), and infectious disease and microbiology research (93.855 and 93.856).

Who was eligible to apply?

Eligibility was broad and included public and private institutions of higher education, nonprofits with or without 501(c)(3) status, for-profit organizations other than small businesses, small businesses, independent school districts, and many government entities (city/township, county, state, special district, and public housing authorities/Indian housing authorities).

Were tribal governments and tribal organizations eligible?

Yes. Federally recognized tribal governments and other tribal entities were eligible, and tribal organizations were also explicitly included.

Were specific types of minority-serving institutions explicitly encouraged or listed as eligible?

Yes. The FOA explicitly listed eligibility for Historically Black Colleges and Universities (HBCUs), Hispanic-serving institutions, Tribally Controlled Colleges and Universities (TCCUs), Alaska Native and Native Hawaiian Serving Institutions, and Asian American Native American Pacific Islander Serving Institutions (AANAPISISs).

Were faith-based or community-based organizations eligible?

Yes. Faith-based or community-based organizations were explicitly included among eligible applicants.

Could organizations outside the United States apply?

Yes. The FOA included non-U.S. entities (foreign organizations) among eligible applicants.

Were U.S. territories or possessions eligible?

Yes. U.S. territories or possessions were explicitly included among eligible applicants.

Was cost-sharing or matching required?

No. There was no cost-sharing or matching requirement.

When was this funding opportunity posted and when did it close?

It was posted and created on June 5, 2015. The original and final closing date was May 7, 2018.

Is this FOA still active?

No. It was archived on June 7, 2018.

Which agency sponsored this opportunity?

The sponsoring agency was the National Institutes of Health (NIH).

Where was the full announcement hosted?

The full announcement was hosted through the NIH Grants Guide (link referenced in the source information).

Who was the contact for technical issues accessing the announcement?

For technical issues accessing the announcement, the contact listed was the NIH Office of Extramural Research (OER) Webmaster at FBOWebmaster@OD.NIH.GOV.

What kinds of outcomes was NIH hoping to enable through this FOA?

The FOA can be read as aiming to enable big-data-driven progress on identifying transmission patterns and risk networks, detecting gaps in testing and treatment, improving retention and viral suppression at the population level, and understanding HIV interactions with other chronic conditions over time.

What was the broader intent beyond generating new findings?

The intent was not only to generate new findings, but to transform how researchers study HIV by leveraging large-scale, complex, real-world data and building approaches that could be validated, re-used, and benefit the broader HIV research and public health communities.

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