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Evaluating the Effectiveness of Targeted Public Health Control Strategies for Chlamydia Transmission in Omaha, Nebraska: A Mathematical Modeling Approach

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DOI: 10.4236/aid.2014.43021    3,484 Downloads   3,919 Views  

ABSTRACT

Objectives: Sexually Transmitted Infections (STIs) have a great public health impact globally. STIs are one of the most critical health problems in the United States of America (USA). Here, we present a mathematical model for testing several interventions that are designed for various communities in order to control the Chlamydia epidemic. Study Design: Based on a community sexual behavior survey, we constructed and parameterized a mathematical disease transmission model to estimate the spread dynamics of Chlamydia in young adults in the northern part of Omaha, Nebraska. Methods: A differential equations based continuous time simulation model is run for various scenarios. The model considers only one age group i.e., 19 - 25 ages, which is considered as the highest risk group for this sexually transmitted disease. Our model assumes homogeneous mixing within this age group and use published estimates to model mixing rates between individuals. Results: The presented model quantified the potential value of screening and treatment programs for Chlamydia in reducing the burden of disease in this specific community. By increasing the screening and treatment rates from 35% to 85%, great public health benefit can be achieved in two years, i.e., total cases reduction around 9% just in this considered age group. Conclusions: Computational results show that behavioral change based interventions on prevention have some effect on reducing the prevalence in the targeted age group; however, more benefit can be obtained with frequent screening and treatment programs.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Islam, K. and Araz, O. (2014) Evaluating the Effectiveness of Targeted Public Health Control Strategies for Chlamydia Transmission in Omaha, Nebraska: A Mathematical Modeling Approach. Advances in Infectious Diseases, 4, 142-151. doi: 10.4236/aid.2014.43021.

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