Faculty Profile

Andrew Brouwer is mathematical epidemiologist and modeler. He is currently an Assistant Research Scientist in the Department of Epidemiology at the University of Michigan. He received his BA in mathematics and chemistry and MA in mathematics from the SUNY College at Potsdam (2009) and his MS in environmental science and engineering from Clarkson University (2011). Andrew also earned his MS in applied and interdisciplinary mathematics (2013), MA in statistics (2015), and PhD in applied and interdisciplinary mathematics (2015) at the University of Michigan. He was a postdoctoral research fellow in the Department of Epidemiology at the University of Michigan (2015-16) prior to joining the faculty as a research faculty member.

• PhD, Applied and Interdisciplinary Mathematics, University of Michigan, 2015
• M.A., Statistics, University of Michigan, 2015 
• M.S., Applied and Interdisciplinary Mathematics, University of Michigan, 2013
• M.S., Environmental Science and Engineering, Clarkson University, 2011
• M.A., Mathematics, SUNY College at Potsdam, 2009
• B.A., Mathematics, Chemistry, SUNY College at Potsdam, 2009

Andrew uses mathematical and statistical modeling to address public health problems. As a mathematical epidemiologist, he works on a wide range of topics (mostly related to infectious diseases and cancer prevention and survival) using an array of computational and statistical tools. Past work has addressed transmission of disease through the environment, as well as the epidemiology of the human papillomavirus (HPV) and HPV-related cancers. Some current projects include analyzing the impact of time-varying shedding on environmental pathogen surveillance, determining the impact of vaccination campaigns on Michigan’s hepatitis A outbreak, understanding the burden of HPV in transmasculine people, and characterizing patterns of transition between the use of cigarettes and e-cigarettes. Rigorous consideration of parameter identifiability, parameter estimation, and uncertainty quantification are underlying themes in Andrew’s work.

Infectious disease

• Brouwer AF, Zelner JL, Eisenberg MC, Kimmins L, Ladisky M, Eisenberg JNSE. (2020). The impact of vaccination efforts on the spatiotemporal patterns of the hepatitis A outbreak in Michigan, 2016–18. Epidemiology.
• Brouwer AF, Eisenberg JNS, Pomeroy CD, Shulman LM, Hindiyeh M, Manor Y, Grotto I, Koopman JS, Eisenberg MC. (2018). Epidemiology of the silent polio outbreak in Rahat, Israel based on modeling of environmental surveillance data. PNAS.
• Brouwer AF, Masters NB, Eisenberg JNS. (2018). Quantitative microbial risk assessment and infectious disease transmission modeling of waterborne enteric pathogens. Current Environmental Health Reports.
• Brouwer AF, Weir MH, Meza R, Eisenberg MC, Eisenberg JNS. (2017). Dose-response relationships for environmentally mediated transmission models. PLOS Computational Biology.
• Brouwer AF, Eisenberg MC, Remais JV, Meza R, Collender PA, Eisenberg JNS. (2017). Modeling biphasic environmental decay of pathogens and implications for risk analysis. Environmental Science & Technology.

HPV and HPV-associated cancer

• Brouwer AF, Meza R, Eisenberg MC. (2019). Integrating measures of viral prevalence and seroprevalence: a mechanistic modeling approach to explaining cohort patterns of HPV in women in the U.S. Journal of the Royal Society: Philisophical Transactions B.
• Brouwer AF, Eisenberg MC, Carey TE, Meza R. (2019). Multisite HPV infections in the United States (NHANES 2003–2014): an overview and synthesis. Preventive Medicine.
• Brouwer AF*, Delinger RL*, Eisenberg MC, Campredon LP, Walline HM, Carey TE, Meza R. (2019). HPV vaccination has not increased sexual activity or accelerated sexual debut in a college-aged cohort of men and women. BMC Public Health. *co-first author
• Brouwer AF, Eisenberg MC, Meza R. (2018). Case studies of gastric, lung, and oral cancer connect etiologic agent prevalence to cancer incidence. Cancer Research.
• Brouwer AF, Meza R, Eisenberg MC. (2017). Parameter estimation for multistage clonal expansion models from cancer incidence data: a practical identifiability analysis. PLOS Computational Biology.

Society of Mathematical Biology
Society for Industrial and Applied Mathematics
Rogel Cancer Center: Cancer Epidemiology & Prevention