Research Network

This Center of Excellence focuses on modeling drug resistance, seasonal infectious diseases and the allocation of interventions. It’s also developing epidemic ‘dashboard’ software to give policymakers visualization tools to help them interpret trends and analyze data in the midst of an emerging epidemic. The center will work closely with health officials around the world to integrate public health knowledge into the models and vice versa.
Web site: http://ccdd.hsph.harvard.edu

This Center of Excellence is studying fundamental questions about the behavioral, environmental and evolutionary factors underlying infectious disease epidemics and using this information to develop real-time models for particular localities, such as cities or states. A key component of the center’s effort is creating outreach and training programs aimed at educating a diverse group of scientists in modeling techniques.

This research group will focus on developing space-time models to detect emerging outbreaks before they spread to most parts of the area under surveillance.  The team will model the natural temporal and geographical variation in different types of electronic health system infectious disease data.

This research group designs, builds and validates models of disease spread and prediction systems based on individuals’ activities in a social network. Using mathematical and computational methods, the group is exploring the effects of human contact patterns in urban areas on disease transmission dynamics and the effectiveness of particular response strategies.

This research group will develop computational models to study the molecular basis of viral evolution.

This research group will develop hierarchical models for the spatio-temporal dynamics of infectious disease.

With substantial expertise on the biology of MRSA, this research group is developing models to understand how patterns of contact and behavior among individuals affect MRSA spread. The researchers will also use the models to test the effectiveness of different interventions, such as public health informational campaigns or enhanced hygiene in institutional settings.

Drawing on expertise in biostatistics and epidemiological field work, this research group is creating simulation models for the transmission of infectious diseases such as flu, cholera, dengue fever and tuberculosis. The models will help assess the effectiveness of different public health interventions and their distribution during an outbreak.

The research group is developing new models of disease spread that integrate individuals’ perceptions and behaviors regarding flu. Using the models, the team will identify intervention strategies that are likely to achieve high levels of adherence and minimize influenza-related disease and mortality. The group also will use the models to optimize intervention strategies.

This informatics group includes researchers at IBM, SAS, Duke University, and Emory University who provide and develop a number of informatics, analytic, and statistical tools in a high performance computational environment. The group also provides programming expertise and data management resources.