Social network analysis has become increasingly central to the study of HIV/STI transmission dynamics and disparities. For this approach to reach its full potential, the theory and methodology must be empirically grounded. This requires a comprehensive analytic strategy that starts with a feasible plan for sampling networks, and uses a statistical framework to leverage the sample information for understanding of population level network structure and dynamics. In this project, our team seeks to build on an innovative research agenda that has developed the statistical theory, methods and programs needed to establish a principled approach to network epidemiology. We seek to extend the current methodology to support comprehensive modeling for dynamic networks.
Our specific aims are to: 1. develop the statistical theory and methodology for modeling network dynamics a. Refine and extend the current ERGM approach to modeling partnership dynamics. b. Develop extensions of ERGM to handle changing population size and composition. c. Create new network visualization tools designed specifically for epidemiological applications. 2. Integrate the new methods into the stat net software for network analysis and simulation a. Develop robust code for implementing the new methods b. Develop comprehensive help functions, manuals, and tutorials c. Ensure public access by publishing the code on CRAN and exploiting internet-based tools. 3. Develop training resources for researchers from different field's a. Develop a 5 day workshop in network theory, study design, analysis, simulation and visualization. b. Develop a 2 day training workshop on using stat net for network analysis. c. Develop 1 day training workshops for interdisciplinary outreach. Our project team comprises an interdisciplinary group of individuals with a long track record of working together, deep expertise in the application of network methods to STI research and prevention, experience in capacity building, and a commitment to the development of publicly accessible software. Our goal is to advance the science of network analysis, provide innovative research tools for research in epidemiology and public health, and lower the barriers to accessing these new tools.
Social network theory and methods are increasingly important in the study of HIV transmission, and for understanding the large persistent disparities in HIV prevalence both globally and in the United States. This project seeks to extend the capabilities of current methods for empirical network research through a combination of theoretical development, computer package implementation, and training workshops.
|Jenness, Samuel M; Goodreau, Steven M; Morris, Martina (2018) EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks. J Stat Softw 84:|
|Cherng, Sarah T; Shrestha, Sourya; Reynolds, Sue et al. (2018) Tuberculosis Incidence Among Populations at High Risk in California, Florida, New York, and Texas, 2011-2015. Am J Public Health 108:S311-S314|
|Hamilton, Deven T; Goodreau, Steven M; Jenness, Samuel M et al. (2018) Potential Impact of HIV Preexposure Prophylaxis Among Black and White Adolescent Sexual Minority Males. Am J Public Health 108:S284-S291|
|Goodreau, Steven M; Hamilton, Deven T; Jenness, Samuel M et al. (2018) Targeting Human Immunodeficiency Virus Pre-Exposure Prophylaxis to Adolescent Sexual Minority Males in Higher Prevalence Areas of the United States: A Modeling Study. J Adolesc Health 62:311-319|
|Krivitsky, Pavel N; Morris, Martina (2017) INFERENCE FOR SOCIAL NETWORK MODELS FROM EGOCENTRICALLY SAMPLED DATA, WITH APPLICATION TO UNDERSTANDING PERSISTENT RACIAL DISPARITIES IN HIV PREVALENCE IN THE US. Ann Appl Stat 11:427-455|
|Goodreau, Steven M; Rosenberg, Eli S; Jenness, Samuel M et al. (2017) Sources of racial disparities in HIV prevalence in men who have sex with men in Atlanta, GA, USA: a modelling study. Lancet HIV 4:e311-e320|
|Jenness, Samuel M; Goodreau, Steven M; Rosenberg, Eli et al. (2016) Impact of the Centers for Disease Control's HIV Preexposure Prophylaxis Guidelines for Men Who Have Sex With Men in the United States. J Infect Dis 214:1800-1807|
|Butts, Carter T (2016) On the Equivalence of the Edge/Isolate and Edge/Concurrent Tie ERGM Families, and Their Extensions. J Math Sociol 40:1-6|
|Jenness, Samuel M; Goodreau, Steven M; Morris, Martina et al. (2016) Effectiveness of combination packages for HIV-1 prevention in sub-Saharan Africa depends on partnership network structure: a mathematical modelling study. Sex Transm Infect 92:619-624|
|Wang, Cheng; Butts, Carter T; Hipp, John R et al. (2016) Multiple Imputation for Missing Edge Data: A Predictive Evaluation Method with Application to Add Health. Soc Networks 45:89-98|
Showing the most recent 10 out of 48 publications