Florida: Zika Virus: Only a Few Small Outbreaks Likely to Occur in Continental U.S.

    Dr. Natalie Exner Dean, a postdoctoral associate in the department of biostatistics at the University of Florida College of Public Health and Health Professions and the College of […]

9th Annual Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID)

  The Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID) is designed to introduce infectious disease researchers to modern methods of statistical analysis and mathematical modeling and to […]

Household Transmission of Vibrio cholerae in Bangladesh Data

On November 2014, some members of the CSQUID team published a study on cholera transmission in Bangladesh in the PLoS Neglected Tropical Diseases journal. Participating researchers included Jonathan Sugimoto, Eben […]

Read More

Paper points to most effective vaccine trials for epidemics, including Ebola

GAINESVILLE, Fla. — Implementing a vaccine trial during an epidemic can be difficult, particularly in countries with poor transportation, limited vaccine supplies and difficulty predicting how widespread a disease may […]

Fighting Ebola with numbers and statistics

Ira Longini, Jr., Ph.D., fights infectious diseases with numbers and statistics. Longini is one of the UF Emerging Pathogens Institute’s biostatistician. He uses mathematical and statistical models to research the […]

Read More
Prev Next

About the Center for Statistics and Quantitative Infectious Diseases

The Center for Statistics and Quantitative Infectious Diseases is program that is part of the MIDAS network. Our main interest is in quantitative methodologic developments related to scientific and public health aspects of infectious diseases, including epidemiology, evaluating interventions, immunology, and vaccinology. Our research focuses on prevention and intervention in infectious diseases of global health importance, as well as emerging infectious diseases, such as pandemic influenza. The quantitative methods include statistical, epidemiologic, mathematical modeling, computational biology, and bioinformatic methods. As part of the MIDAS network, our group is partially supported by the National Institute of General Medical Sciences at NIH.