Contact

Phone: 470-578-7414

Email: aazizi@kennesaw.edu

Office Location: D 201

Office Hours:
office hours TBD

Network-Based Model For Chlamydia Sexually Transmitted Infection

Chlamydia trachomatis (Ct) is the most commonly reported  STI in the U.S. with an estimated 1.7 million infections per year.  There is a significant Ct outbreak among  African American people  ages 15-25 in New Orleans, LA. 
In close collaboration with Tulane School of Public Health team, we have developed  Markov Chain Monte Carlo (MCMC) Stochastic Agent-Based  Model for spread  of Ct over dynamic sexual network of individuals in New Orleans to investigated various mitigation  strategies such as  condom use, random screening, partner notification,  and re-screening. 

 

gifct   toolbox ct1

 

Left: Chlamydia epidemic spread over a  sexual network. Larger nodes (person) have more neighbors (sexual partners). The infection status of each person is tracked using the Susceptible (Green) - Infectious (Red) - Susceptible (SIS) framework. Middle: The implemented Ct prevention and interventions via CheckIt! program, Right: Model prediction for the impact of CheckIt! program on the prevalence in women under different intervention coverage. Darker region gives a higher Chlamydia prevalence in women.

Publications:

  •  Azizi, A., Dewar, J., Qu, Z., & Mac Hyman, J. (2021). Using an agent-based sexual-network model to analyze the impact of mitigation efforts for controlling chlamydia. Epidemics, 35, 100456.

  • Qu, Z., Azizi, A., Schmidt, N., Craig-Kuhn, M. C., Stoecker, C., Mac Hyman, J., & Kissinger, P. J. (2021). Effect of screening young men for Chlamydia trachomatis on the rates among women: a network modelling study for high-prevalence communities. BMJ open, 11(1), e040789

  • Azizi, A., Qu, Z., Lewis, B., & Mac Hyman, J. (2021). Generating a heterosexual bipartite network embedded in social network. Applied Network Science, 6(1), 1-16.

  • Boroojeni, A. A., Dewar, J., Wu, T., & Hyman, J. M. (2017). Generating bipartite networks with a prescribed joint degree distribution. Journal of complex networks, 5(6), 839-857 

  • Azizi, A., Xue, L., & Hyman, J. M. (2016). A multi-risk model for understanding the spread of chlamydia. In Mathematical and statistical modeling for emerging and Re-emerging infectious diseases (pp. 249-268). Springer, Cham.

 

Collaborators
James Mac Hyman (Tulane University), Zhuolin Qu (University of Texas San Antanio), Patricia Kissinger (Epidemiology, Tulane), etc.

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