Dr. Michael Haber joined the faculty of the Emory Biostatistics Department in 1983. Since then, his research has been mainly devoted to developing stochastic models and statistical methods related to the analysis of infectious diseases data. Over the past 20+ years, his research has focused on estimating parameters related to the direct, indirect and overall effects of vaccines and vaccination programs. These methods have been applied to data from observational studies and clinical trials on influenza, pneumococcal, rotavirus and other infectious diseases.
Dr. Haber was the Principle Investigator on four NIH R01 grants and on numerous other grants and contracts. He published over 130 peer-reviewed papers and a few book chapters.
Dr. Haber taught courses in probability theory, statistical inference, and on analysis of categorical, survival and infectious diseases data. He directed numerous PhD dissertations and Master theses.
Areas of Interest
- Infectious Disease
- Statistical Modeling
- Infectious Disease Dynamics
- Data Science
- Survival Analysis
- PhD 1976, Hebrew University, Jerusalem
- BIOS 524: Analytic Meth/Infect Disease
Affiliations & Activities
Dr. Haber's main research area involves application of stochastic models and statistical methods related to infectious diseases. He currently works on study designs and statistical methods for esimating vaccine effectiveness
- Haber, M., Brown, M. B., 1986, Maximum likelihood methods for log-linear models when expected frequencies are subject to linear constraints, Journal of the American Statistical Association, 81, 477-482
- Haber, M. and Barnhart, H.X. , 2006, Coefficients of agreement for fixed observers., Statistical Methods in Medical Research, 15, 255-271
- Haber, M., 1999, Estimation of the direct and indirect effects of vaccination., Statistics in Medicine, 18, 2101-2109
- Salmon, D.A., Haber, M., Gangarosa, E.J., Phillips, L., Smith, N. and Chen, R.T., 1999, Health consequences of religious and philosophical exemptions from immunization laws: Individual and social risk of measles., Journal of American Medical Association , 282, 47-53
- Haber, M., Orenstein, W.A., Halloran, M.E., Longini, I.M. , 1995, The effect of disease prior to an outbreak on estimation of vaccine efficacy following the outbreak, American Journal of Epidemiology, 141, 980-990
- Ainslie, K.E.C*., Shi, M*., Haber, M., and Orenstein W.A. , 2019, A dynamic model for evaluation of the bias of influenza vaccine effectiveness estimates from observational studies. , American Journal of Epidemiology, 188, 451-460
- Ainslie, K.E.C*., Haber, M., and Orenstein W.A, 2019, Bias of influenza vaccine effectiveness estimates from test-negative studies conducted during an influenza pandemic. , Vaccine, 37, 1987-1993
- Ainslie, K.E.C*., Haber, M., and Orenstein W.A. , 2019, Challenges in estimating influenza vaccine effectiveness, Expert Reviews of Vaccines, ,
- Ainslie, K.E.C*., Haber, M., Malosh, R.E., Petrie, J.G., and Monto, A.S. , 2018, Maximum likelihood estimation of influenza vaccine effectiveness against transmission from the household and from the community, Statistics in Medicine, ,
- Shi, M*., An, Q*., Ainslie, K.E.C*., Haber, M., and Orenstein, W.A, 2017, A comparison of the test-negative and the traditional case-control study designs for estimation of influenza vaccine effectiveness under non-random vaccination., BMC Infectious Diseases, ,
- Foppa, I.M., Haber, M., Ferdinands, J.M. and Shay, D.K. , 2013, The case test-negative design for studies of the effectiveness of the influenza vaccine. , Vaccine, ,