To narrow the gap between science and policy, MIDAS researchers need not only to produce sound results but also to implement sound strategies to assure utility of and access to those results: that is, to support the translation of research to policy. This Policy Studies Component proposes to advance the translation of modeling results and tools to policy making for infectious disease mitigation. We define translation as the use of new knowledge in practice, including policy making. Translation in science is analogous to innovation in management, and diffusion-of-innovation studies suggest an evidence-based foundation for policy translation. Diffusion theory points to the importance of the """"""""weak network"""""""": one that features a few nodes whose connections channel an information-exchange between two separate networks. In this Policy Studies Component, we take advantage of existing and new researcher-policy maker collaborations. They connect through weak networks across which the leaders in each exchange information (dissemination) and then serve as implementers within each (diffusion). We propose that the translation of modeling results and tools to public health policy depends on the weak network between modelers and policy makers who use dissemination and diffusion to channel information and feedback.
Two Specific Aims will explore whether this proposition is a feasible and revealing framework for the study of policy translation: (1) Engage policy makers in identifying and addressing public health needs for modeling results and tools. This focus is on exploring the problems appropriate for applications of modeling, the optimal construction of models to address users'questions, and the appropriate circumstances for the use of modeling approaches by practitioners and policy makers. (2) Evaluate strategies for translating modeling results and tools into public health policy.
This aim will address questions such as: What strategies effectively translate modeling to policy applications? What organizational factors facilitate the adoption of modeling tools and results by policy makers? What characteristics typify the early adopters and thought leaders who encourage further diffusion of modeling? A synthesis of theory, research, and case examples leads to a conceptual model for Policy Studies. This Push/Pull Model is innovative in its combination of dissemination and diffusion strategies and its evaluation methodology grounded in social science. The Push/Pull Model is embedded in the integrated decision support pathway and captures both diffusion theory and the actual researcher-policy maker collaborations existing in MIDAS.

Public Health Relevance

The Policy Studies Component derives its relevance from achieving the outcomes of successful policy translation. These outcomes include: modeling research addresses topics important and useful for policy making;policy makers responsible for infectious disease mitigation have access to modeling results and tools;and modeling-informed policy making improves resource allocation and population health. Whether these outcomes are served by the selected evaluation strategies will be the focus of evaluation.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
2U54GM088491-06
Application #
8796443
Study Section
Special Emphasis Panel (ZGM1-BBCB-5 (MI))
Project Start
Project End
Budget Start
2014-09-24
Budget End
2015-06-30
Support Year
6
Fiscal Year
2014
Total Cost
$33,894
Indirect Cost
$11,885
Name
University of Pittsburgh
Department
Type
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Lessler, Justin; Cummings, Derek A T (2016) Mechanistic Models of Infectious Disease and Their Impact on Public Health. Am J Epidemiol 183:415-22
Salje, Henrik; Cauchemez, Simon; Alera, Maria Theresa et al. (2016) Reconstruction of 60 Years of Chikungunya Epidemiology in the Philippines Demonstrates Episodic and Focal Transmission. J Infect Dis 213:604-10
Clapham, Hannah E; Rodriguez-Barraquer, Isabel; Azman, Andrew S et al. (2016) Dengue Virus (DENV) Neutralizing Antibody Kinetics in Children After Symptomatic Primary and Postprimary DENV Infection. J Infect Dis 213:1428-35
Chadsuthi, Sudarat; Iamsirithaworn, Sopon; Triampo, Wannapong et al. (2016) The impact of rainfall and temperature on the spatial progression of cases during the chikungunya re-emergence in Thailand in 2008-2009. Trans R Soc Trop Med Hyg 110:125-33
Guclu, Hasan; Read, Jonathan; Vukotich Jr, Charles J et al. (2016) Social Contact Networks and Mixing among Students in K-12 Schools in Pittsburgh, PA. PLoS One 11:e0151139
Grantz, Kyra H; Rane, Madhura S; Salje, Henrik et al. (2016) Disparities in influenza mortality and transmission related to sociodemographic factors within Chicago in the pandemic of 1918. Proc Natl Acad Sci U S A 113:13839-13844
Poon, Leo L M; Song, Timothy; Rosenfeld, Roni et al. (2016) Quantifying influenza virus diversity and transmission in humans. Nat Genet 48:195-200
Dalziel, Benjamin D; Bjørnstad, Ottar N; van Panhuis, Willem G et al. (2016) Persistent Chaos of Measles Epidemics in the Prevaccination United States Caused by a Small Change in Seasonal Transmission Patterns. PLoS Comput Biol 12:e1004655
Nisalak, Ananda; Clapham, Hannah E; Kalayanarooj, Siripen et al. (2016) Forty Years of Dengue Surveillance at a Tertiary Pediatric Hospital in Bangkok, Thailand, 1973-2012. Am J Trop Med Hyg 94:1342-7
Lessler, Justin; Salje, Henrik; Van Kerkhove, Maria D et al. (2016) Estimating the Severity and Subclinical Burden of Middle East Respiratory Syndrome Coronavirus Infection in the Kingdom of Saudi Arabia. Am J Epidemiol 183:657-63

Showing the most recent 10 out of 199 publications