This proposal describes a four year career development and training plan for Erik Volz, an Assistant Research Scientist in the Department of Epidemiology at the University of Michigan-Ann Arbor. Training will aid with the development of a career in Epidemiology with a focus on infectious diseases, especially HIV and other sexually transmitted infections. The training program will allow Dr. Volz to acquire skills in areas necessary for expertise in the field of HIV epidemiology while conducting substantial research in areas where he already has established a strong publishing record. Dr. Volz will be mentored by a team of three faculty with experience ranging from complex systems modeling of infectious diseases to the microbiology and pathology of HIV infection and the evolution of viruses. The School of Public Health at the University of Michigan is an excellent venue for junior faculty seeking to develop a career as an independent investigator. A large community of research faculty and postdoctoral fellows are available as potential collaborators and as an audience for work in progress. Research supported by this award will concern the use of novel sources of HIV genetic data for fitting models of the HIV epidemic. The union of mathematical epidemiology, immunology and phylogenetics has been dubbed """"""""phylodynamics"""""""", and Dr. Volz has made recent progress on the theory necessary to unify traditional models of infectious disease epidemics with the evolution of HIV described by phylogenetic trees. The potential of phylodynamic methods was demonstrated recently as the first estimates of the fundamental reproduction number, R0, for pandemic H1N1 came from the analysis of several dozen influenza genetic sequences, not from traditional epidemiological surveillance data. Dr. Volz hopes to refine these methods and develop them into a practical tool for epidemiologists engaging in HIV surveillance. A collaboration will be established with the Michigan Department of Community Health to analyze a database of several thousand HIV sequences collected from newly diagnosed individuals since 2004. By applying phylodynamic models to this large set of sequences, Dr. Volz will attempt to answer longstanding questions about the transmission patterns of HIV. This research will generate novel estimates of R0, the temporal distribution of transmissions post-infection, the fraction of transmissions that happen during acute and early HIV infection, demographic determinants of infection and transmission risk, and behavioral heterogeneity and sexual network structure. Public Health Relevance: Stemming the HIV pandemic requires effective surveillance, frequent testing, and rapid diagnosis of new infections. An under-utilized source of data comes from the virus itself. The genetic sequence of virus bears the fingerprint of epidemiological dynamics, and the objective of this proposal is to characterize the distribution and determinants of HIV transmission using HIV sequences collected for routine drug-resistance testing.
. Stemming the HIV pandemic requires effective surveillance, frequent testing, and rapid diagnosis of new infections. An under-utilized source of data comes from the virus itself. The genetic sequence of virus bears the fingerprint of epidemiological dynamics, and the objective of this proposal is to characterize the distribution and determinants of HIV transmission using HIV sequences collected for routine drug-resistance testing.
|Rasmussen, David A; Volz, Erik M; Koelle, Katia (2014) Phylodynamic inference for structured epidemiological models. PLoS Comput Biol 10:e1003570|
|Romero-Severson, Ethan Obie; Alam, Shah Jamal; Volz, Erik et al. (2013) Acute-stage transmission of HIV: effect of volatile contact rates. Epidemiology 24:516-21|
|Miller, Joel C; Volz, Erik M (2013) Incorporating disease and population structure into models of SIR disease in contact networks. PLoS One 8:e69162|
|Alam, Shah Jamal; Zhang, Xinyu; Romero-Severson, Ethan Obie et al. (2013) Detectable signals of episodic risk effects on acute HIV transmission: strategies for analyzing transmission systems using genetic data. Epidemics 5:44-55|
|Volz, Erik M; Frost, Simon D W (2013) Inferring the source of transmission with phylogenetic data. PLoS Comput Biol 9:e1003397|
|Frost, Simon D W; Volz, Erik M (2013) Modelling tree shape and structure in viral phylodynamics. Philos Trans R Soc Lond B Biol Sci 368:20120208|
|Miller, Joel C; Volz, Erik M (2013) Model hierarchies in edge-based compartmental modeling for infectious disease spread. J Math Biol 67:869-99|
|Volz, Erik M; Ionides, Edward; Romero-Severson, Ethan O et al. (2013) HIV-1 transmission during early infection in men who have sex with men: a phylodynamic analysis. PLoS Med 10:e1001568; discussion e1001568|
|Volz, Erik M; Koelle, Katia; Bedford, Trevor (2013) Viral phylodynamics. PLoS Comput Biol 9:e1002947|
|Volz, Erik M; Koopman, James S; Ward, Melissa J et al. (2012) Simple epidemiological dynamics explain phylogenetic clustering of HIV from patients with recent infection. PLoS Comput Biol 8:e1002552|
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