Welcome to CeCERA

The Computational Epidemiology Research Laboratory (CERL) was established in 2004 to conduct and promote research in computational epidemiology. Following federal funding from HRSA, the Center for Computational Epidemiology and Response Analysis (CeCERA) was founded in 2008.

CeCERA is a multidisciplinary research center focused on activities related to population health. Projects include outbreak modeling, visualization of complex data, geospatial analysis, and response plan design.

Different laboratories have been established as part of CeCERA in the Department of Computer Science and Engineering, the Institute of Applied Science, and the Department of Geography. CERL has continued as an integral component of the interdisciplinary CeCERA.

As opposed to mathematical and statistical epidemiology, computational epidemiology is in its infancy. Despite this, computational epidemiology is a great complement to other methodologies in epidemiology that have been developed during the last century. Our primary focus is the application of computational concepts and resources to problems in the domain of public health, and thereby providing tools for these epidemiologists and scientists. These tools will aid in the prediction and analysis of disease manifestation and spread in a given population through modeling, simulation, and visualization, thus enabling epidemiologists to conduct focused what-if-analyses that facilitate the allocation of public health resources.

For information regarding CeCERA/CERL, research projects, and collaboration, please contact: cecera@unt.edu

CeCERA

News

  • 07/24/2012 - 13:26
    ECCS '12 Satellite meeting: Data-driven modeling of contagion processes presentation accepted

    Title: Studying Disease Dynamics under Diverse Population Structures and Contagion Scenarios
    Author: Iris Gomez-Lopez, Olivia Loza, Armin R. Mikler

  • 07/24/2012 - 13:26
    ECCS '12 Satellite meeting: Data-driven modeling of contagion processes presentation accepted

    Title: Stochastic Computational, Thermal, and Vertical Transmission Models to Simulate Dengue Persistence in Vector and Human Populations

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