[Population Modeling] Introduction

[Cristina Lanzas]

Hi all,

I am Cristina Lanzas. I am faculty at the department of Population Health
and Pathobiology at North Carolina State University. I've recently moved my
lab from the University of Tennessee to NCSU. The following is a brief
intro of my lab work:

Our lab focus on the epidemiology and ecology of infectious diseases in
animal and human populations. We work with  a range of pathogen-host
systems including zoonotic pathogens and health-care associated diseases in
humans. We combine data, epidemiological analysis and mathematical models
to study transmission mechanisms, and to identify and design control
measures to reduce the public health burden associated with infectious
diseases with emphasis on the role that environment plays on transmission
and the dissemination of antimicrobial resistant pathogens (Lanzas and
Chen, 2014). The rational design and assessment of surveillance and control
strategies for environmentally transmitted pathogens require models that
capture more realistic exposure patterns and include spatial features of
the pathogen transmission (Chen et al., 2013). For our current NIH funded
project, we are using the spora-producing *C. difficile* as a case-study to
improve mathematical models used to assess environmental transmission
(Lanzas et al., 2011). We are developing compartmental and agent-based
models that include explicit functional forms for different environmental
exposure pathways, and consider spatial features of pathogen transmission.
In addition to using the models to design and evaluate interventions to
reduce the burden of *C. difficile*, the models are used to investigate the
effect of the characterization of the environmental pathogen distribution
and scale with the generated model dynamics. And in collaboration with
mathematicians, we aim to use the models generated in this project to
address some significant mathematical challenges associated to the analysis
of agent-based models. These challenges include how to reduce spatially
explicit agent-based models to mean-field dynamics, and how to transfer
optimal control strategies from the mean-field models to the agent-based
models.

Ref:


   1. Lanzas, C., and Chen, S. 2014. Complex system modeling for veterinary
   epidemiology. Preventive Veterinary Medicine. DOI:
   10.1016/j.prevetmed.2014.09.012
   2. Chen, S., Sanderson, M., White, B., Amrine, D., Lanzas, C. 2013.
   Temporal-spatial heterogeneity in animal-environment contact: implications
   for the exposure and transmission of pathogens. Nature Scientific
   Reports, 3:3112
   3. Lanzas, C., Dubberke, E.R,, Lu, Z., Reske, K.A., Gröhn, Y.T. 2011.
   Epidemiological model for Clostridium difficile transmission in health care
   settings. Infection Control and Hospital Epidemiology. 32: 553-561
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