Steven E. Bellan

Epidemiology & Biostatistics, Global Health Institute, Health Informatics Institute
Assistant Professor

Curriculum Vitae

Professional Website

Epidemiology & Biostatistics, Global Health Institute, Health Informatics Institute

  • Education

    PhD, Environmental Science, Policy & Management, University of California-Berkeley, 2012

    MPH, Epidemiology, University of California-Berkeley, 2008

    AB, Ecology and Evolutionary Biology, Princeton University, 2006

  • Areas of Expertise

    Research: mathematical modeling, infectious diseases, HIV, Ebola, data-driven modeling, epidemiological study design, disease ecology

    Teaching: scientific computation, biostatistics, R programming, data visualization, quantitative epidemiology

  • Affiliations

    Program Director, International Clinics on Infectious Disease Dynamics and Data

  • Course Instruction

    EPID 7500 – Introduction to Coding in R, Data Science and Simulation for Public Health and the Life Sciences

    Dr. Bellan teaches a variety of quantitative approaches in infectious disease epidemiology with a focus on data-driven mechanistic modeling. HIs teaching approach emphasizes intuitive understanding of statistical and dynamical modeling using interactive lectures, computer labs/tutorials, and realistic examples of data analysis. Dr. Bellan is particularly interested in training researchers to use simulation modeling to plan and interpret empirical studies. He is also the Program Director of the International Clinics on Infectious Disease Dynamics and Data (ici3d.org), which organizes two annual training workshops in Florida and Cape Town.

  • Research Interests

    Dr. Bellan’s lab takes a broad quantitative perspective to address applied questions in infectious disease epidemiology. His research spans multiple pathogen systems (HIV, Ebola, anthrax, rabies) but is united by an overarching theme: the integration of mathematical and statistical models with empirical data to understand infectious disease processes and how to control them. By building simulation models of how diseases spread at the population level, he helps to interpret available data and to plan rigorous empirical studies. Dr. Bellan’s research particularly focuses on this intersection between epidemiological study design and transmission dynamics–that is, he aims to improve study design and interpretation by understanding the dynamical transmission processes underlying an epidemic and how they might bias studies.

  • Selected Publications

    Bellan, SE, JRC Pulliam, CAB Pearson, DChampredon, SJ Fox, L Skrip, AP Galvani, M Gambhir, BA Lopman, TC Porco, LA Meyers, J Dushoff (2015). The statistical power and validity of Ebola vaccine trials in Sierra Leone: A simulation study of trial design and analysis. Lancet Infectious Diseases.

    Bellan, SE, J Dushoff, AP Galvani, LA Meyers (2015). Re-assessment of HIV-1 acute phase infectivity: adjusting for biases with simulated cohorts. PLOS Medicine.

    Bellan, SE, KJ Fiorella, DY Melesse, WM Getz, BG Williams, J Dushoff (2013). Extra-couple HIV transmission in sub-Saharan Africa: a mathematical modelling study of survey data. Lancet.

    Bellan, SE, O Gimenez, R Choquet, WM Getz (2013). Hierarchical Distance Sampling Approach to Estimating Mortality Rates from Opportunistic Carcass Surveillance Data. Methods in Ecology and Evolution.

    Bellan, SE, JRC Pulliam, JC Scott, J Dushoff and the MMED Organizing Committee (2012). How to make epidemiological training infectious. PLOS Biology.

  • News/Media