Notice of Special Interest (NOSI): Simulation Modeling and Systems Science to Address Health Disparities
Notice Number:
NOT-MD-20-025

Key Dates

Release Date:

August 13, 2020

First Available Due Date:
October 05, 2020
Expiration Date:
May 08, 2023

Related Announcements

NOT-MD-20-030 - Notice of Correction to Application Submission Information for NOT-MD-20-025

PA-20-185 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)

Issued by

National Institute on Minority Health and Health Disparities (NIMHD)

National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)

National Institute on Drug Abuse (NIDA)

National Institute of Mental Health (NIMH)

National Library of Medicine (NLM)

National Cancer Institute (NCI)

All applications to this funding opportunity announcement should fall within the mission of the Institutes/Centers. The following NIH Offices may co-fund applications assigned to those Institutes/Centers.

Division of Program Coordination, Planning and Strategic Initiatives, Office of Disease Prevention (ODP)

Office of Behavioral and Social Sciences Research (OBSSR)

Purpose

Purpose

The purpose of this Notice of Special Interest is to support investigative and collaborative research focused on developing and evaluating simulation modeling and systems science to understand and address minority health and health disparities.

Background

Although scientific and technological advances have improved the health and well-being of the U.S. population overall, racial and ethnic minorities, socioeconomically disadvantaged, underserved rural and sexual and gender minority populations continue to experience a disproportionate share of many acute or chronic diseases and adverse health outcomes, including the burden related to the recent COVID-19 disease outbreaks caused by the novel coronavirus (SARS-CoV-2) pandemic, and/or other pandemics, epidemics (e.g., dengue fever, zika, chikungunya) or public health emergencies. Several characteristics make addressing health disparities an especially challenging problem. The challenges lie in the interactions of influences at various levels (e.g., individual, interpersonal, family, community, societal), the diversity of the relevant mediators (e.g., exposures, resilience factors), and the multiple interacting mechanisms involved (e.g., biological, behavioral, environmental, sociocultural, and healthcare system). The array of determinants of health across levels and domains are depicted in the NIMHD Research Framework (https://www.nimhd.nih.gov/about/overview/research-framework.html).

Systems science considers different components within complex systems across multiple levels to help understand their interactions and influences. The dynamic relationship that unfolds when considering contextual factors that contribute to health inequities, such as neighborhood segregation, employment insecurity, housing insecurity, food insecurity, neighborhood safety, social networks, and community disempowerment, cannot be fully captured with currently available data and analytic methods that focus on single, independent factors.

Simulation Modeling and Systems Science (SMSS) provides avenues for modeling relevant multiple processes, testing plausible scenarios, understanding the magnitude of intended and unintended consequences of specific interventions, and having the option to adjust and refine simulated intervention designs prior to actual implementation testing in the real world. Although no simulation models can replace real world settings or scenarios, many are becoming indispensable for decision making, such as national or local pandemic planning, and can have a profound impact on health policies relevant to minority health and health disparities. The field of SMSS may help to guide health disparities research, in identifying causal inference and what types of situations will be most amenable to research, policy, and practice interventions and in implicating where leverage may be best applied for any health disparity population.

It is important to advance SMSS using new big data technologies to understand the etiology of health disparities and guide intervention development and implementation. SMSS are also highly relevant to late-stage translation research because they integrate information and evidence from various sources such as epidemiology, clinical guidelines, sociology, behavioral science, psychology, neuroscience, and economics, to formulate complex predictive models. The etiology, pathways, and mechanisms that result in health disparities mimic a complex adaptive system. Models of health disparities seek to illuminate critical elements and intervention points that can tip the system for improved health or provide insights into why health has not improved. Modeling multi-level interventions is important for addressing how the interactions and influences of health determinants function. SMSS offer an opportunity to explore the potentially complex influences on population health at each intervention level. Of importance is the ability to identify unanticipated implementation research strategies that may yield high return. SMSS approaches can answer the critical questions of what works, under what conditions, what strategies and combinations of strategies will yield innovative ways to address disparities. Also, other significant questions include: why something did not work as anticipated, and how could the intervention be modified to be more effective in addressing disparities.

Research Objectives

  • Foster trans-disciplinary partnerships and collaborations in understanding the etiology and causal pathways of health disparities using SMSS
  • Use SMSS to identify modifiable barriers and cost-effective factors to reduce and eventually eliminate health disparities
  • Use SMSS to improve patient safety and reduce medical errors for populations affected by health disparities
  • Use SMSS to assess and predict the spread and consequences of pandemics (e.g., SARS-CoV-2) and the effectiveness of interventions in populations affected by health disparities
  • Provide evidence-based simulation or prediction of the impact of effective or ineffective health disparities interventions delivered in real-world settings
  • Promote big data harmonization and novel analytic methods in SMSS to address minority health and health disparities

Research Methodology

Examples of research methods could include but are not limited to:

  • System dynamics modeling
  • Network Analysis
  • Agent-based modeling
  • Dynamic microsimulation modeling
  • Discrete event simulation
  • Markov modeling
  • Hybrid simulation modeling (e.g., sequential design, enrichment design, integration design, and parallel design)

Research Topics

Applications should be relevant to the objectives of the funding opportunity announcement and to at least one of the participating institutes’ and offices' research interests. Researchers are strongly encouraged to review the general research interests of the participating ICs.

National Institute on Minority Health and Health Disparities (NIMHD)

NIMHD is interested in several research priorities that could have significant impact on understanding and addressing minority health and health disparities using simulation modeling and systems science. The research must focus on one or more minority or health disparity populations (African Americans/Blacks, Hispanics/Latinos, American Indians/Alaska Natives, Asians, Native Hawaiians and Other Pacific Islanders, socioeconomically disadvantaged populations, underserved rural populations, and sexual and gender minority populations).

Examples of potential topic areas include but are not limited to:

  • Models to explore mechanisms and pathways of health disparities using multiple socioecological levels
  • Predictive models to improve clinical care coordination and integrate patient-centered health services for minority and health disparity populations
  • Simulation modeling to identify and verify most appropriate population-specific screening or detection strategies on chronic diseases and infectious diseases prevention
  • Simulation modeling to identify and verify most appropriate population-specific evaluation and treatment strategies of chronic and infectious diseases that disproportionately affect disparity populations
  • Models to inform improved multilevel, multi-factorial randomized controlled, comparative effectiveness, or pragmatic intervention designs aimed at addressing health disparities
  • SMSS to improve implementation and dissemination of evidence-based primary care practice in rural and underserved communities
  • Simulation modeling using big data and information technology for national and local disparity surveillance and monitoring
  • Partitioning and decomposition methods that have a high potential in identifying causes of disparities
  • Models that hierarchically connect information at different levels of NIMHD's research framework
  • Models that explore the impact of natural and/or human-made disasters and public health emergencies on health care needs, health care system capacity, health care delivery, and health outcomes in communities affected by health disparities
  • Models that explore the socioeconomic impact of chronic disease care in health disparity populations
  • Models that explore the socioeconomic impact of infectious disease care (e.g. care for COVID-19 patients) in health disparity populations Models to explore the socioeconomic impact of inpatient care in health disparity populations
  • Simulation models for the purpose of improving the safe delivery of health care to populations affected by health disparities
  • Mathematical and/or simulation models that assess or predict the spread and the impact of pandemics such as SARS-CoV-2 and/or other epidemics (e.g., dengue fever, zika, chikungunya) or public health emergencies on health services use and health outcomes among populations affected by health disparities
  • Simulation models that assess and predict the effectiveness of interventions to address the impacts of pandemics such as SARS-CoV-2 and/or other epidemics (e.g., dengue fever, zika, chikungunya) or public health emergencies on health services use and health outcomes of populations affected by health disparities.

National Institute of Mental Health (NIMH)

NIMH has specific interest in improving the mental health outcomes of underserved populations. NIMH is also participating in modeling approaches that support the National Action Alliance for Suicide Prevention’s efforts to reduce the suicide rate by 20% by 2025. Because many underserved populations often experience greater suicide risk, and less service access and engagement, simulation modeling of potential improvements for underserved populations could identify the most promising pathways to reduce suicide deaths and associated mental health problems. Simulation modeling approaches could include, but are not limited to:

  • Models to improve case identification of individuals with mental illness, suicide risk, treatment response or non-response, and other relevant outcomes in representative populations of diverse racial/ethnic, geographic and socioeconomic groups
  • Modeling to assess the expected benefits and costs of the implementation of efficacious mental health interventions to reduce the burden of mental disorders and suicide across diverse racial ethnic, geographic and socioeconomic groups.
  • Simulation to identify key gaps in existing evidence regarding efficacy, effectiveness, and efficiency of certain mental health interventions among diverse groups, such that research to fill these gaps would have high clinical and public health value, particularly in reducing mental health disparities.

National Institute on Drug Abuse (NIDA)

NIDA is interested in several research priorities that could have significant impact on understanding and addressing minority health and health disparities using simulation modeling and systems science:

  • Studies modeling the effectiveness and cost-effectiveness of dissemination or implementation strategies to reduce health inequities in substance use disorder treatment and improve quality of treatment among rural, minority, and other underserved populations.
  • Studies modeling the implementation of multiple evidence-based practices within community or clinical settings to meet the needs of complex patients and diverse systems of care in addiction.
  • Systems science studies to inform key implementation steps and challenges on decision models that assist states and communities in their efforts to promote effective implementation and dissemination of multi-pronged and coordinated approaches to promote prevention and evidence-based treatment (e.g., Medication Assisted Treatment for opioid use disorders) of addiction.
  • Simulation modeling to identify key determinants for effective evidence-based interventions for addiction (e.g., combination of behavioral treatments with medication assisted treatment) and their impact on morbidity, mortality, and cost of treatment.
  • Studies modeling complex social/environmental factors that influence addiction to identify underlying mechanisms and key leverage points for evidence-based interventions.
  • Studies that model implementation of interventions targeting the same addiction risk behaviors, but that use different strategies (e.g., mass media campaigns vs. policy regulation, etc.) and which predict the critical elements for successful implementation of each intervention approach.
  • Predictive models to improve clinical care coordination and integrate patient-centered addiction services in primary care to reduce disparities.
  • Predictive models to improve care coordination and integrate patient-centered addiction services in settings such as criminal justice and child welfare to reduce disparities.
  • Multi-level models that illuminate interactions between or among distinct systems that contribute to (or attenuate) disparity/inequity outcomes, potentially encompassing influences such as those exerted through education, neighborhood, family, cultural, religious, commercial, media, regulatory, and/or health care systems.

Office of Disease Prevention (ODP)

The ODP is interested in co-funding simulation modeling and systems science research projects to identify combinations of preventive interventions that, if implemented and disseminated broadly, could reduce health disparities for a wide variety of preventable conditions in a state or region, or across the country. The ODP is particularly interested in evaluating multi-level interventions in the context of these simulation modeling and systems science research projects. Of greatest interest would be applications focused on estimating reductions in health disparities for the leading risk factors associated with mortality in the United States: tobacco use, overweight/obesity, poor diet and physical inactivity, alcohol misuse, environmental exposures, infectious disease, injury and violence (includes self-harm), risky sexual behavior, and substance abuse. In addition, The ODP also encourages applications to support projects led by early stage investigators. For more information about ODP strategic priorities, visit: https://prevention.nih.gov/about-odp/strategic-plan-2019-2023.

National Institute on Deafness and Other Communication Disorders (NIDCD)

NIDCD is interested in supporting simulation modeling and systems science (SMSS) research projects to advance understanding of hearing impairment and other communication disorders that can lead to disparities and inequities in access and utilization of health care, rehabilitation treatments, and knowledge of preventive measures. Hearing impairment and other communication disorders are not rare in the U.S. population – a conservative estimate is that 46 million Americans experience one or more communication disorders. Since communication disorders make the basic components of communication (sensing, interpreting, and responding to people and things in our environment) challenging, these disorders can not only compromise physical health, but also affect the emotional, social, recreational, educational, and vocational aspects of life. The effects often ripple out to affect families and social networks, including those at work and school. The total economic impact of communication disorders addressed by the NIDCD mission areas of hearing, balance, smell, taste, voice, speech and language with regards to quality of life and unfulfilled potential is substantial. The prevalence of communication disorders is expected to increase as the population ages, survival rates of medically fragile infants improve, and the numbers of children and adults affected by traumatic injuries and diseases increase.

Examples of potential topic areas include but are not limited to:

  • Predictive models to identify strategies and interventions that may be effective in reducing disparities and inequities and to assess the range of effects that may be associated with implementing such strategies and interventions;
  • Multi-level models that illuminate interactions among distinct systems that increase or reduce disparity/inequity outcomes, potentially encompassing influences such as those exerted through education, neighborhood, family, cultural, religious, commercial, media, regulatory, and/or health care systems.
  • Models that identify factors that create or exacerbate disparities and inequities in access to screening, intervention, referral to treatment, treatment for hearing impairment (including tinnitus and hyperacusis), balance/vestibular disorders, smell or taste impairment (including dysgeusia or phantosmia), and disorders of voice, speech and language.
  • Examine existing and develop better aural rehabilitation strategies across the lifespan, including how aural rehabilitation strategies are affected by treating comorbid conditions that influence success, such as co-occurring issues in underserved children and adults from differing socio-cultural backgrounds with regards to hearing impairment, which may also be associated with cognitive decline (e.g., dementia), or chronic illness (e.g., diabetes).
  • Implement practical approaches to screening for chemosensory disorders, i.e., the incidence, prevalence and associated risk factors for taste and smell loss and dysfunction. There is a need to integrate the use of standardized chemosensory measurement into the health care system (particularly for older adults) to facilitate appropriate advice, warnings and precautionary instructions that should be given to patients who suffer from chronic difficulty with odor identification or disturbances in smell perception (e.g., phantosmia) and taste loss or altered perception (e.g., dysgeusia). These problems likely have varying distributions and impact across minority and disadvantaged sectors of the population.

National Cancer Institute (NCI)

NCI is interested in modeling efforts that focus on explaining why disparities exist, how disparities can be alleviated in the future, what combination of cancer control activities (which are considered optimal for the general population) can be more appropriately tailored for the needs in specific populations. Of additional interest is the potential population impact of programs and interventions which have shown promise to reduce disparities in specific studies. While disparities will typically be studied in terms of standard racial/ethnic characterizations, modelers are encouraged to utilize data sources that will enable modeling in terms of other important factors such as income/education, insurance status, and geography (e.g., rural vs. urban). Applications are especially encouraged which link the upstream antecedents of disparities to the long term downstream outcomes. NCI’s interest focuses on modeling in two related domains:

  • The upstream behavioral (including observable behavior, cognition and affective factors), geographic, cultural, political, economic, and organizational antecedents of disparities in smoking rates, obesity, and other risk factors; screening rates, follow-up to abnormal screening, treatment, and quality of care related to healthcare access and delivery; genetic predispositions and gene by environment interactions.
  • The downstream consequences of disparities in cancer incidence, prevalence and mortality resulting from differences in behavioral risk factors, healthcare access and delivery, and genetic predispositions.

National Library of Medicine (NLM)

NLM is interested in research projects that incorporate innovative biomedical informatics and data sciences approaches into simulation modeling and systems science to reduce health disparities across all segments of the U.S. population. NLM is interested in SMSS research projects that are generalizable across multiple biomedical domains. Examples of potential topic areas include but are not limited to:

  • Predictive modeling using EHR data for disparity surveillance and reduction of bias
  • SMSS studies that address improving planning for diverse populations in health and weather emergencies
  • Simulation modeling for public health surveillance in rural, minority, and other underserved populations
  • Simulation modeling of decision factors for health decisions of consumers and patients in rural, minority, and other underserved populations

National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)

The mission of the National Institute of Arthritis and Musculoskeletal and Skin Diseases is to support research into the causes, treatment, and prevention of arthritis and musculoskeletal and skin diseases. Together, musculoskeletal and arthritis disorders are the third leading cause of disability in the United States. A disproportionate share of disability may be experienced by underrepresented and underserved populations, including racial and ethnic minorities, as well as socioeconomically disadvantaged, under-resourced rural, and sexual and gender minority populations. NIAMS has specific interest in simulation modeling and systems sciences research to identify combinations of evidence-based secondary prevention interventions, at multiple levels, that if implemented broadly, could have potential to reduce health disparities and improve outcomes for diseases within the NIAMS mission area.

Application and Submission Information

This notice applies to due dates on or after October 5, 2020 and subsequent receipt dates through May 8, 2023. 

Submit applications for this initiative using one of the following funding opportunity announcements (FOAs) or any reissues of these announcement through the expiration date of this notice.

  • PA-20-185 - NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed)

All instructions in the SF424 (R&R) Application Guide and the funding opportunity announcement used for submission must be followed, with the following additions:

  • For funding consideration, applicants must include “NOT-IC-19-XXX” (without quotation marks) in the Agency Routing Identifier field (box 4B) of the SF424 R&R form. Applications without this information in box 4B will not be considered for this initiative.

Applications nonresponsive to terms of this NOSI will not be considered for the NOSI initiative.

Inquiries

Please direct all inquiries to the contacts in Section VII of the listed funding opportunity announcements with the following additions/substitutions:

Scientific/Research Contact(s)

Rada Dagher, Ph.D., M.P.H.
National Institute on Minority Health and Health Disparities (NIMHD)
Telephone: 301-451-2187
Email: rada.dagher@nih.gov

Denise Juliano-Bult. M.S.W.
National Institute of Mental Health (NIMH)
Telephone: 301-443-1638
Email: djuliano@mail.nih.gov

Keisher Highsmith, Dr.PH.
National Institute on Drug Abuse (NIDA)
Telephone: 301-402-1984
Email: keisher.highsmith@nih.go

Elizabeth Neilson, Ph.D., M.P.H., M.S.N.
Office of Disease Prevention (ODP)
Telephone: 301-827-5578
Email: NeilsonE@mail.nih.gov

Howard J. Hoffman, M.A.
National Institute on Deafness and Other Communication Disorders (NIDCD)
Telephone: 240-506-1974
Email: hoffmanh@nidcd.nih.gov

Eric J. (Rocky) Feuer, Ph.D., M.S.
National Cancer Institute (NCI)
Telephone: 240-276-6772
E-mail: feuerr@mail.nih.gov

Hua-Chuan Sim, M.D.
National Library of Medicine (NLM)
Telephone: 301-594-4882
Email: simh@mail.nih.gov

Stephanie George, Ph.D.
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
Telephone: 301-594-4974
Email: stephanie.george@nih.gov

Michael Spittel, Ph.D.
Office of Behavioral and Social Sciences Research (OBSSR)
Telephone: 301-451-4286
Email: Michael.Spittel@nih.gov

OBSSR does not award grants. Please contact one of the IC program contacts listed below for questions regarding funding interest.

Financial/Grants Management Contact(s)

Priscilla Grant
National Institute on Minority Health and Health Disparities (NIMHD)
Telephone: 301-594-8412
Email: pg38h@nih.gov


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