SOURCES SOUGHT
R -- Systems Dynamics Model of Social Determinants of Local Obesity Dynamics
- Notice Date
- 5/10/2012
- Notice Type
- Sources Sought
- NAICS
- 541720
— Research and Development in the Social Sciences and Humanities
- Contracting Office
- Department of Health and Human Services, National Institutes of Health, National Library of Medicine, 6707 Democracy Blvd., Suite 105, Bethesda, Maryland, 20894, United States
- ZIP Code
- 20894
- Solicitation Number
- NIHLM2012376-SRE
- Archive Date
- 6/8/2012
- Point of Contact
- Sheila R. Edmonds, Phone: 3014966546
- E-Mail Address
-
sheila.edmonds@nih.gov
(sheila.edmonds@nih.gov)
- Small Business Set-Aside
- N/A
- Description
- This Sources Sought Notice is for informational and planning purposes only and shall not be construed as a solicitation or as an obligation or commitment by the Government. This notice is intended strictly for Market Research. This is a Small Business Sources Sought Notice. This is NOT a solicitation for proposals, proposal abstracts, or quotations. The purpose of this notice is to obtain information regarding: (1) the availability and capability of qualified small business sources; (2) whether they are small businesses; HUBZone small businesses; service- disabled, veteran-owned small businesses; 8(a) small businesses; veteran-owned small businesses; woman-owned small businesses; or small disadvantaged businesses; and (3) their size classification relative to the North American Industry Classification System (NAICS) code for the proposed acquisition. The North American Industry Classification System (NAICS) Code is 541720-Research and Development in the Social Sciences and Humanities with a small business size standard of $7.0 million. The National Institutes of Health (NIH), Office of Behavioral and Social Sciences Research (OBSSR) is conducting a Market Survey to help determine the availability and technical capability of qualified small businesses, veteran-owned small businesses, service-disabled veteran-owned small businesses and/or HUBZone small businesses capable of serving the needs identified below: Background: The Office of Behavioral and Social Sciences Research (OBSSR) furthers the mission of the National Institutes of Health (NIH) by emphasizing the critical role that behavior and social factors play in health, health care, well-being. OBSSR's vision is to bring together the biomedical, behavioral, and social science communities to work more collaboratively to solve pressing health challenges facing our nation. OBSSR's plan includes facilitating: a) the next generation of basic behavioral and social sciences research: b) transdisciplinary "team science" that brings together the biomedical, behavioral, and social-ecological perspectives; c) research that integrates the systems and multiple levels of analysis; d) the translation, implementation, dissemination, and maintenance of best practices to strengthen the sciences of dissemination, put what is known into widespread practice, reduce the burden of chronic disease and help eliminate inequities in health and health care. In 2007, the Office of Behavioral and Social Sciences Research (OBSSR) at the National Institutes of Health (NIH) in collaboration with the Robert Woods Johnson Foundation (RWJF) funded the Collaborative Obesity Modeling Network (COMNet). COMNet was designed to convene modeling groups from around the world (United States, Canada, United Kingdom and Australia) who were already developing statistical and computational models for obesity. The purpose of these meetings was for the groups learn about one another's models. Although many valuable lessons were learned through these meetings and a series of high impact publications did result (Lancet August 2011), the initial COMNet contract did not provide funds for modeling work per se; rather funding was limited to convening meetings. The COMNet meetings were successful in identifying a need for further modeling to aid policy decisions about how to reverse the obesity epidemic. "Comparative modeling" exercises were identified as a promising approach for this endeavor. Comparative modeling involves using a variety of different modeling approaches to address common questions, and in some cases may involve some common model assumptions or datasets. Comparative modeling can be used to show how differences in approaches can affect projected outcomes and to help determine which approaches are best suited for which research questions. Results from comparative modeling studies lend credibility to model results by providing a form of sensitivity analysis on the model assumptions and structure adopted by independent working groups. As a follow up to COMNet, OBSSR, RWJF, the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD), and the National Heart Lung and Blood Institute (NHLBI) jointly sponsored a comparative modeling network to address overweight and obesity-related public policy. Each sponsor funded one or more teams in the Envision network, with each team focusing on a different aspect of the obesity problem or methodological approach. As part of the Envision network, OBSSR funded two teams, led by Virginia Polytechnic Institute and State University (Virginia Tech) and Washington University, St. Louis, each bringing a system dynamics modeling approach. The teams differ in their focus, with the Washington University team focused at the local level and Virginia Tech focused at the national level. This work was funded with the contract mechanism and began in 2009 (Washington University) and 2010 (Virginia Tech). Under the prior contract, Washington University began modeling and simulation work to understand obesity, with a focus on social determinants. The rapid increase in obesity prevalence in the U.S. poses a major threat to the nation's health, now and in the future. The drivers of obesity are predominantly behavioral and social in nature. To future address this problem, the OBSSR requires the continuity of modeling and simulation work to: 1) help understand the etiology of the epidemic 2) help devise appropriate and sustainable solutions, 3) anticipate the potential impact of interventions and their unintended effects over time, and 4) determine the best investment of limited resources across a variety of intervention options and combinations. Purpose/Objective: The purpose of this requirement is to refine a preliminary system dynamics (SD) computer simulation model for childhood obesity trends at the community level with a focus on social determinants. OBSSR wishes to build on the Washington University's previous work on modeling a particular community in the West End neighborhood of St. Louis, Missouri. The Washington University developed a preliminary SD model that included input from the local West End community. What is now needed, is1) to collect data on the model parameters for the specific community in the West End of St. Louis, (i.e., for standard and non-standardized measures), 2) calibrate the model to local data, once collected, 3) validation exercises (aka confidence building exercises, and 4) comparative modeling exercises in which the results of the model developed under this requirement are compared to results from other models in the Envision network. The reason for selecting this specific community is to leverage Washington University's prior work in this area. In addition, this community has desirable characteristics for study including the existing engagement of the community in the problem and the fact that the community represents an underserved vulnerable population for which such data is badly needed. OBSSR desires to compare Washington University's model to the other models NIH is funding as part of the (Comparative Modeling) CompMod/Envision network. The resulting model should capture the social determinants theorized to contribute to local obesity dynamics. Moreover, it should be based on input from the local community in order to increase model buy-in from local community stakeholders and faith in its outputs. This community model building approach is expected to greatly increase the model's utility in the long run in terms of helping the community understand the obesity problem at the local level, including the factors that contribute to unintended consequences and counterintuitive outcomes, and the trade offs of various policy interventions, and an appreciation for the time dimension of the problem and solution. Scope of Work: OBSSR seeks refinement and expansion to Washington University's existing system dynamics computer simulation model for childhood obesity trends at the community level that can be compared with other existing models in CompMod. In particular, we seek refinement and expansion to a model developed using a participatory group model building approach and which features the West End Neighborhood in St. Louis City, Missouri. The required work extends prior work in the following ways: 1) improves model specification by use of parameter data from the specific community in the West End of St. Louis, (i.e., for standard and non-standardized measures). 2) calibrate the model to local data, once collected. 3) improve model validity with specific validation exercises (aka confidence building exercises; and 4) compare the resulting model to other similar models developed under the Envision network. To accomplish this, the Contractor will need access to the existing model specification developed by Washington University, including the University's computer programming codes to access the data. We are especially in need of formulation, testing, and development of model equations using community specific quantitative data. A key aspect of this requirement involves participation in two face-to-face meetings per year with Envision and CompMod teams (approximately 2 days each). A primary goal of these meetings is to share progress on model development and to work on comparisons with other teams' models. It is expected that the Contractor will engage in relevant presentations and publications regarding the work specified in this requirement. Contractor Tasks The Contractor shall perform the following tasks: Task 1: Measure and calibrate the existing preliminary model developed by Washington University to community specific variables and trends-One of the inherent challenges of working in marginalized communities is the absence of standard data. What is needed to calibrate the model is the systematic collection of primary data and refinement of secondary data including: better demographic trends based on the 2010 Census; geographic information and placement of stores; built environment; height and weight growth curves for a random sample of children in the West End; community perceptions of healthy food access, bullying, crime, and safety; and, norms on food and weight. When possible, multiple measures should be used as a form of data and survey method triangulation, including secondary data and data collected from standardized measures. The specific data collected and analyses performed will be dictated by the existing model. The results should then be used to determine the initial conditions of the model, generate empirical trends for model testing and calibration, and estimate the parameter distributions for subsequent sensitivity analyses. Task 2: Model validation exercises-OBSSR requires model validation exercises to be conducted on the existing preliminary model developed by Washington University using the additional data collected per Task 1. Additional group model building and review sessions will be required in conjunction with data collection to be sure data collected will be appropriate for the existing model. A rigorous set of confidence building tests against data and estimates of effect sizes will then be conducted. Specifically, the confidence building tests should include behavior reproduction of key trends (population dynamics, obesity trends, physical activity, perceptions of safety in the neighborhood, use of corner stores, etc.), comparisons of the individual and joint distributions of simulated variables against the distributions of empirically measured variables, extreme conditions testing to assess the logical consistency of the model, boundary adequacy testing to determine the completeness of the model with respect to the West End community, and sensitivity analysis on all parameters to assess the impact of uncertainty in parameter estimates on the qualitative behavior of the model and policy recommendations. Task 3: Conduct systematic comparisons between the model as it evolves from this work, with other models in CompMod-A fundamental idea in comparative modeling networks is the notion that networks of modeling teams yield better science and more utility to policy makers than individual teams working alone. This notion builds on the general research strategy of triangulation where the use of multiple methods allows one to offset the inherent limitations of one method with the strengths of another method and thereby achieve an overall more rigorous set of results. A project focusing on understanding the role of social determinants at the community level from the community's perspective using participatory methods would provide a set of unique opportunities to explore comparisons with models from other CompMod teams. The findings of such comparisons would be important contributions to the fields of childhood obesity, social determinants of health, and systems science. Specific examples of the types of comparisons sought under this requirement include: • Comparing the simulated growth curves from the model (as it evolves from Task 1 and 2) against the results from another Envision team. The other team has completed extensive work on addressing issues related to data imputation and simulating growth curves. Accurate modeling of growth curves is essential to drawing realistic policy forecasts for obesity prevention strategies. This comparison between the model results from the model resulting from this requirement and the existing model from the other Envision team will provide important insights into the nature of missing data with respect to marginalized communities and the extent that effects of missing data in existing data sets can be mitigated through methods such as a participatory modeling. • Comparing the dynamics of the "comfort food" feedback loop in the model (as it evolves from Task 1 and 2) l against the agent-based modeling dynamics of emotional eating from another Envision team. The other Envision team focuses on individual level models and represents individual level psychological mechanisms. For comparison purposes, we are seeking under this requirement, a model that would represent the aggregated effects at the community level. The other Envision team will be able to provide detailed information and simulation results that could be used to compare and validate an aggregate representation of emotional eating developed under this requirement. An aggregate model might be able to provide the other Envision team with an assessment of what the overall importance of these feedback mechanisms might be in driving childhood obesity trends in the community. • Comparing the aggregated dynamics of social networks at the community level from the model (as it evolves from Task 1 and 2) against the disaggregated agent-based modeling of social networks from another Envision team. System dynamics models represent network effects at the aggregate level, but are generally limited in terms of explaining differences that might arise from different types of social network structures. A comparison between the system dynamics model sought under this requirement with an agent based model being developed by another Envision team, could help assess the sensitivity of policy recommendations to assumptions about social network structures. If, for example, it turns out that the structure of the social network changes the dynamics of childhood obesity and this has policy implications, then it will be important for any policy analysis to consider and measure the structure of social networks. On the other hand, if policy recommendations are insensitive to assumptions about social networks, then the aggregate representation of social networks in system dynamics may suffice. • Comparing the weight distributions from the aggregated cohorts of the model (as it evolves from Task 1 and 2) sought under this requirement against the weight distributions from the disaggregated individuals from another Envision team. In contrast to the model sought under this requirement, the other Envision team uses a disaggregated, individual level behavioral model of the energy gap. The system dynamics model sought under this requirement would focus on modeling the growth curves of age-birth weight cohorts. A comparison between them would provide an important check to first see if the results of obesity trends across the models are consistent. It would also provide the most direct comparison within CompMod as to how social determinants might mediate and moderate the effects of prevention strategies for childhood obesity. Deliverables ● The first deliverable is the collection of primary data and the attainment of secondary data, both required to specify the existing preliminary model to the local community (see full description, Task 1 above). • Execution of Tasks 1 and 2 performed on the existing preliminary model will result in an evolved model that will be a product of this requirement. The deliverable is an empirically tested system dynamics computer simulation model of the social determinants of childhood obesity in the West End community. ● The delivered model should be provided in some form that is designed for community member engagement. That is, to help them understand and appreciate how systems science and computational models can be used to identify, prioritize, design, and implement more effective prevention strategies. ● An additional key deliverable will be model comparisons, of the sorts outlined in Task 3, between the work sought and the work of others in the CompMod network. ● A final written progress report will be due within 60 days of completion of the proposed contract. Period of Performance: The anticipated period of performance will be twelve (12) months from the date of award. The proposed acquisition will be procured in accordance with the policies and procedures under FAR 15. All responsible sources may submit a capability statement which will be considered by the National Library of Medicine. This Sources Sought Notice is not a Request for Proposals (RFP), nor is an RFP available. (a) Provide a capability statement demonstrating relevant experience, skills and ability to fulfill the Government's requirements for the above. The capability statement should contain enough sufficient detail for the Government to make an informed decision regarding your capabilities; however, the statement should not exceed ten (10) pages. (b) The capability statement should include references, key personnel, and any teaming arrangements needed to fulfill the requirements. It must identify the responder's small business type and size; DUNS number; NAICS code; and technical and administrative points of contact, including names, titles, addresses, telephone and fax numbers, and e-mail addresses. (c) All capability statements must be submitted electronically no later than 2:00 PM EST on Thursday, May 24, 2012 to Sheila Edmonds at sheila.edmonds@nih.gov. Disclaimer and Important Notes: This notice does not obligate the Government to award a contract or otherwise pay for the information provided in response. The Government reserves the right to use information provided by respondents for any purpose deemed necessary and legally appropriate. Any organization responding to this notice should ensure that its response is complete and sufficiently detailed to allow the Government to determine the organization's qualifications to perform the work. Respondents are advised that the Government is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted. After a review of the responses received, a pre-solicitation synopsis and solicitation may be published in Federal Business Opportunities. However, responses to this notice will not be considered adequate responses to a solicitation. Confidentiality: No proprietary, classified, confidential, or sensitive information should be included in your response. The Government reserves the right to use any non-proprietary technical information in any resultant solicitation(s).
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