Parastu Kasaie, PhD, MS

Titles:

Postdoctoral fellow

Email:

pKasaie@jhu.edu

I am a fellow researcher in the field of infectious disease modeling and epidemiology. With an academic background in Industrial Engineering, Biostatistics and Business Analytics, my research lies at the intersection of mathematical/computational and epidemiological/public-health sciences.

The major focus of my research is development and application of stochastic computer simulation models for understanding and control of infectious disease epidemics. I’m especially interested in application of agent-based simulation technique as a powerful tool for modeling complex epidemiological systems involving human behavior. In my previous research, I have focused on study of Tuberculosis (TB) and HIV infections, and worked on several projects for studying the epidemic dynamics and addressing various policy-making issues for combating the spread of disease.

In choosing the research projects, I tend to focus on problems of special complexity, which cannot be adequately handled through the conventional analytical techniques, and to propose novel approaches for addressing such complexities using a combination of computational, statistical and epidemiological techniques. Examples of my previous research include the estimation of TB transmission patterns from genotyping data, study of spatiotemporal TB diffusion pattern in heterogeneous populations, evaluating the population level impact of various control intervention for control of TB, optimal allocation of limited epidemic-control resources among competing programs.

I’m currently working on a project for studying the HIV transmission and control among Men who have Sex with Men (MSMs) in Baltimore city. In this work, we’re developing a spatially explicit individual-based simulation model of MSMs that can replicate the observed clustering of HIV incidence in Baltimore City according to race, age, and geographical location of each individual. The model is calibrated to demographic and HIV surveillance data from Baltimore City, and will be used to predict the patterns of HIV incidence, prevalence, mortality, linkage and retention in care under various scenarios. The main objective is evaluating the population-level impact of implementing PrEP (as a preventive therapy) and ART, at different levels of coverage and adherence, on future HIV epidemic among Baltimore MSMs.

Categories

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October 2017

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Projects

Modeling the impact of spatially targeted TB...

 We have developed transmission models to understand the impact of TB vaccination strategies that target hotspots of...

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Modeling the impact of novel TB drug regimens...

We are constructing mathematical models of TB epidemics in Southeast Asia, India, and Vietnam to explore the potential...

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Comparative implementation and...

We are conducting a randomized comparative implementation trial across 56 sites in rural South Africa to evaluate three...

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Impact of diabetes on TB treatment outcomes...

This is a study to prospectively enroll and follow TB patients co-infected with diabetes and TB patients without diabetes...

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Modeling the impact of spatially targeted TB...

We have developed transmission models to understand the impact of TB vaccination strategies that target hotspots of...

Read More