Georgia State University Research Foundation, Inc.
Grant: $190,334 - Department of Health and Human Services - May. 21, 2009
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Award Description: A basic network hypothesis?that networks exert an independent influence on HIV/STD transmission?is well supported by both empirical and theoretical work. The exact (that is, quantitative) relationship, however, between specific aspects of network structure and the occurrence of STIs and HIV remains elusive. The problems are manifold. On the empirical side, missing ties and the underlying sampling approach can engender important distortions. On the theoretical side, simple approaches are removed from reality, but complex approaches are undermined by their detail. Capturing reality may not be the goal, but some cogent semblance of it is needed to make the connection between the propagation of disease and the factors that influence such propagation. We propose that a useful approach will be a blend of the empirical and the theoretical: using observed networks as the starting point for dynamic models that observe disease transmission over time. We will combine eight previous studies and an ongoing project R01 DA019393 (NIDA) , all of which used the same basic questionnaire, to delineate comparative network and behavioral features; to use observed configurations as a starting point for simulation; and to provide a theoretical and empirical basis for evaluating the relationship of network factors to disease transmission. a.1 Aims 1.0 Create parallel information sets from eight completed network studies on STD/HIV transmission. 1.1 Identify variables in these data sets that are comparable, or can be made so by transformation. 1.2 Develop a uniform data set that includes all the studies. 1.3 Perform comparative descriptive analyses of the available data to define the range of characteristics of the populations, risk environments, and network properties. 2.0 Analyze the impacts of network and other demographic, behavioral, and social factors on disease outcomes using standard multivariable statistical tools 3.0 Develop simulation and mathematical methods for exploring network transmission dynamics. 3.1 Evaluate the effect of study design on outcomes for each of the eight studies 3.2 Use simulation to test the hypotheses generated by multivariable analysis (Aim 2) 3.3 Use modeling and simulation to evaluate the transmission of different pathogens in the same populations. a.2 Hypotheses Though exploratory and developmental, this project is nonetheless founded on several hypotheses. H1.0 Approximately 80% of the variables will be compatible across studies, and the eight studies will demonstrate similar general structure (right?skewed degree distribution; large connected components; and small world characteristics). H2.0 Network factors such as concurrency, transitivity, and assortativity will have a larger effect on disease outcomes than do demographic and behavioral factors. H3.0 The proposed theoretical approach and simulations will be validated by their fit with empirically observed outcomes and their power to test hypotheses generated from the data..
Project Description: Extensive empirical research has shown that the transmission of HIV and STIs is profoundly influenced by contact network structure and behavioral risks. Yet the diverse insights gleaned from these studies have not yet been integrated into a general framework for understanding the endemic and epidemic spread of STIs through heterogeneous populations. There are a number of mathematical approaches to modeling disease transmission through contact networks but most make simplifying assumptions that are inconsistent with empirical observations. In particular, many models assume that contact and behavioral patterns remain constant for the duration of an outbreak. In this exploratory project, we propose (1) to develop broad hypotheses linking population structure and behavioral risk to STI transmission dynamics through extensive statistical analyses of data from eight empirical network studies, and (2) to test these hypotheses using powerful new mathematical models that explicitly consider the epidemiological impact of network fluidity. Our empirical data derive from eight completed network studies (six in Atlanta GA and one each in Colorado Springs CO and Flagstaff AZ), and one ongoing study in Atlanta, all of which used the same basic questionnaire. We will assemble and amalgamate these studies, and we estimate that 80% of the variables in each of these studies will be congruent. We will conduct multivariable analyses to determine which behavioral and population factors most strongly influence the transmission of HIV/STIs. Then, using mathematical models that incorporate the network structures, behavioral risks, and prevalence patterns calculated from our eight studies, we will quantitatively explore the implications of these influential factors, the efficacy of various empirical network study designs, and the differential transmission of diverse pathogens in the same network.
Jobs Summary: N/A (Total jobs reported: 0)
Project Status: Less Than 50% Completed
This award's data was last updated on May. 21, 2009. Help expand these official descriptions using the wiki below.
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