Rafael Meza, Ph.D.

Rafael Meza

Assistant Professor, Epidemiology

M5533 SPH II      Vcard icon
1415 Washington Heights
Ann Arbor, Michigan 48109-2029

Office: 734-763-1946; Fax: 734-936-2084

E-mail: rmeza@umich.edu

Curriculum Vitae (PDF)

Professional Summary

Dr. Meza is assistant professor in the Department of Epidemiology at the University of Michigan. He received his BSc in applied mathematics from the Instituto Tecnologico Autonomo de Mexico (ITAM), and his PhD in applied mathematics from the University of Washington. After receiving his PhD, Dr. Meza completed a two-year postdoctoral fellowship at the Fred Hutchinson Cancer Research Center - and a three-year fellowship at the University of British Columbia Centre for Disease Control.

Dr. Meza's research interests lie at the interface of epidemiology, biostatistics and biomathematics. In particular, he is interested in cancer risk assessment and the analysis of cancer epidemiology data using mechanistic models of carcinogenesis. He is also interested in the mathematical modeling of chronic and infectious disease dynamics and its applications in public health policy design. Dr. Meza is Coordinating Principal Investigator of the Cancer Intervention and Surveillance Modeling Network (CISNET) lung group, core member of the Cancer Prevention and Control Program at the University of Michigan Comprehensive Cancer Center (UMCCC), and member of the UM Tobacco Research Network (UMTRN). He is also Honorary Professor at the Mexico National Institute of Public Health (INSP). 

Currently, Dr. Meza is developing models to evaluate the impact of screening and smoking cessation on lung cancer risk. Additional projects include the development of methodologies to investigate the effects of infectious disease dynamics on the risk of cancers with infectious disease etiology, modeling the impact of policies on cigarette and smokeless tobacco use, and modeling the impact of diabetes prevention strategies in Mexico.

Courses Taught

EPID636: Cancer Risk and Epidemiology Modeling
EPID637: Systems Modeling of Behavior, Social Processes and Chronic Disease


Ph.D., Applied Mathematics, University of Washington, 2006
B.Sc., Applied Mathematics, ITAM, 2000

Research Interests & Projects

Cancer risk assessment, analysis of cancer epidemiology data using mathematical models of carcinogenesis, smoking and lung cancer risk, colon cancer epidemiology, public health policy modeling, mathematical modeling of infectious disease dynamics, contact network epidemiology, cancers with infectious disease etiology. Stochastic processes, applied probability, statistical inference and dynamical systems.

Comparative Modeling of Lung Cancer Control Policies
Principal Investigator: Rafael Meza, Joey Kong, Ted Holford, Harry de Koning, David Levy, Suresh Moolgavkar, Silvya Plevritis
Sponsor: NIH/NCI (U01CA152956)

Sophisticated modeling techniques can be powerful tools for decision makers seeking to understand the effects of cancer control interventions on population trends in cancer incidence and mortality. Yet the proven value of such models in health policy is limited by legitimate concerns over lack of transparency of complex models and variability in published results from different groups. NCI's Cancer Intervention and Surveillance Modeling Network (CISNET) was created to promote collaboration between independent modeling groups investigating similar questions. By using the same sources of data for inputs and agreeing on uniform outcome measures, the variability in results reflects uncertainty in the effects of cancer control interventions rather than differences in design of the analysis. Further, by working together, the modeling groups can coherently explain the causes of variation. This proposal furthers the goals of CISNET by using comparative modeling approach to estimate the contributions of tobacco control and screening to reducing deaths from lung cancer.


Lung cancer screening in the US
Principal Investigator: Pamela McMahon, Rafael Meza, Sylvia Plevritis, Harry de Koning
Sponsor: NIH/NCI

We are deriving lung cancer natural history models based on the National Lung Cancer Screening Trial (NLST) and the Prostate, Lung, Colon and Ovarian Cancer Screening Trial (PLCO) to evaluate the impact of lung cancer screening strategies in the US. We are collaborating with NLST, PLCO investigators and with the US Preventative Services Task Force to determine optimal lung cancer screening recommendations.

Using an Ocean of Data, Researchers Model Real-Life Benefits of Cancer Screening

After Landmark Study, Exploring Questions about Lung Cancer Screening


Modeling the Policy Impact on Cigarette and Smokeless Use and on US Mortality
Principal Investigator: David T Levy; Rafael Meza, Joey Kong (co-Is)
Sponsor: NIH/NIDA (R01DA036497)

We are conducting statistical analyses of the transitions to and from cigarette and smokeless tobacco use. The statistical analyses will consider the effect of tobacco control policies on the initiation, cessation, multiple product use and quantity smoked. We will apply the statistical analyses to three existing models, the SimSmoke tobacco control policy model and two natural history of disease models, the Michigan Lung Cancer Model and the Massachusetts General Hospital Lung Cancer Policy Model (LCPM) models. These models were developed as part of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET). A key advance in CISNET has been the collaborative use of multiple models to address a common question using shared inputs, an approach cited for best modeling practices.

The models will project smokeless tobacco and cigarette use in the US, incorporating multiple product use and the initiation, cessation, and switching between products. We will compare the US population impact of regulations such as: health warnings, retail point-of-sale restrictions and the regulation of product content. The models will consider the impact of  regulations on population smokeless tobacco and cigarette prevalence (in total and by age and gender) and on tobacco- attributable deaths.


From Mechanism to Population: Modeling HPV-Related Oropharyngeal Carcinogenesis
Principal Investigator: Rafael Meza, Marisa Eisenberg, Tom Carey
Sponsor: NIH/NCI (U01CA182915) & UM MCubed

While cervical and other genital cancers are primarily caused by Human Papilloma Virus (HPV) infections, recent studies have demonstrated that HPV is also associated with head and neck (HN) cancers. The prevalence of oral HPV infection among men and women aged 14 to 69 years in the US is about 7%, however, 90% of University of Michigan (UM) oropharyngeal squamous cancer (OPSC) patients carry high-risk HPV. Indeed, the incidence of HPV- associated OPSCs is increasing and OPSC has become the most common HPV-related cancer in the US. HPV has been shown to disrupt several key cancer pathways in oropharyngeal squamous cell lines, including p53 and Rb, but many open questions remain regarding oral HPV transmission epidemiology, infection and persistence, the mechanisms of HPV HN carcinogenesis, and the connection between the ongoing oral HPV epidemic and the rising OPSC incidence. The overarching goal of this proposal is to understand the mechanistic effects of HPV infection on the regulatory pathways of oropharyngeal carcinogenesis, and how these effects in turn shape the observed age-specific incidence and mortality of OPSCs. This problem is inherently multi-scale, as population level HPV transmission drives dynamic, ongoing changes to intracellular cancer regulatory pathways, which in turn drives population-level trends in cancer incidence and mortality. Thus, understanding the rising incidence in OPSC necessitates tying together both the population level processes of infectious disease and the population-level cancer incidence through the mechanistic interactions between HPV and carcinogenesis. Toward this goal, we will develop systems biology models of the main proliferation regulatory networks affected by HPV, and assess the consequences of HPV infection, integration and alternate transcripts on the dynamics of HPV-positive tumor cell proliferation. We will integrate these mechanistic infection and cancer models into multistage models of carcinogenesis to gauge the impacts of HPV infection on the population-level age-specific incidence and mortality of OPSC. We will use these integrated multiscale cancer models in combination with population-level oral HPV transmission models to predict the effects of current HPV prevalence trends on future rates of OPSCs and the potential impact of vaccination and other prevention strategies. Our systems models will be based on multiscale inference using mechanistic infection and cancer data.


Selected Publications

Search PubMed for publications by Rafael Meza >>

Meza R, ten Haaf K, Kong CY, Erdogan A, Hazelton WD, Black W, Tammemagi M, Choi S, Jeon J, Han S, Munshi V, van Rosmalen J, Pinsky P, McMahon PM, de Koning H, Feuer EJ, Hazelton WD, Plevritis SK (2014). Comparative analysis of five lung cancer natural history and screening models that reproduce outcomes of the NLST and PLCO trials. Cancer, 120 (11), 1713–1724.

Virani S, Sriplung H, Rozek LS, Meza R (2014). Escalating burden of breast cancer in Southern Thailand: analysis of 1990-2010 incidence and prediction of future trends Cancer Epidemiology, 38 (3), 235–243.

Holford TR, Meza R, Warner KE, Meernik C, Jeon J, Moolgavkar SH, Levy DT (2014). Tobacco Control and the Reduction in Smoking-Related Premature Deaths in the United States, 1964-2012 JAMA, 311(2), 164-171.

de Koning HJ, Meza R, Plevritis SK, Ten Haaf K, Munshi VN, Jeon J, Erdogan SA, Kong CY, Han SS, van Rosmalen J, Choi SE, Pinsky PF, de Gonzalez AB, Berg CD, Black WC, Tammemägi MC, Hazelton WD, Feuer EJ, McMahon PM (2014). Benefits and Harms of Computed Tomography Lung Cancer Screening Strategies: A Comparative Modeling Study for the U.S. Preventive Services Task Force. Ann Intern Med, 160(5), 311-320.

Holford, T.R., Levy, D.T., McKay, L.A., Clarke, L., Racine, B., Meza, R., Land, S., Jeon, J., Feuer, E.J. (2014). Patterns of Birth CohortSpecific Smoking Histories, 19652009. Am J Prev Med, 46(2), e31–e37.

Moolgavkar, S.H., Holford, T.R., Levy, D.T., Kong, C.Y., Foy, M., Clarke, L. Jeon, J., Hazelton, W.D., Meza, R., Schultz, F., McCarthy, W., Boer, R., Gorlova, O., Gazelle, G.S., Kimmel, M., McMahon, PM., de Koning, H.J., Feuer, E.J. (2012). Impact of Reduced Tobacco Smoking on Lung Cancer Mortality in the United States During 1975–2000 JNCI, 104(7), 541-548.

Meza, R., Jeon, J., Renehan, A.G., Luebeck, E.G. (2010). Colorectal cancer incidence trends in the United States and United Kingdom: Evidence of right- to left-sided biological gradients with implications for screening. Cancer Research, 70(13), 5419-5429.

Meza, R., Pourbohloul, B., Brunham, R.C. (2010). Birth cohort patterns suggest that infant survival predicts adult mortality rates. Journal of the Developmental Origins of Health and Disease, 1(03), 174-183.

Meza, R., Jeon, J., Moolgavkar, S.H., Luebeck, E.G. (2008). Age-specific incidence of cancer: Phases, transitions, and biological implications. Proceedings of the National Academy of Sciences (PNAS), 105 (42), 16284-9.

Meza, R., Hazelton, W.D., Colditz, G.A., Moolgavkar, S.H. (2008). Analysis of lung cancer incidence in the nurses' health and the health professionals' follow-up studies using a multistage carcinogenesis model. Cancer Causes and Control, 19(3), 317-28.

Professional Affiliations

Society of Mathematical Biology
Society of Industrial and Applied Mathematics


Nearly 800,000 deaths prevented in the US (1975-2000) due to declines in smoking. Dr. Eric "Rocky" Feuer, CISNET's NCI Scientific Coordinator, discusses the results of a CISNET study that evaluated the impacts of Tobacco Control on lung cancer mortality

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