Laura B. Balzer, PhD - UMass Amherst · Laura B. Balzer, PhD DepartmentofBiostatistics&Epidemiology SchoolofPublicHealth&HealthSciences UniversityofMassachusetts-Amherst...

Laura B. Balzer, PhD

Department of Biostatistics & EpidemiologySchool of Public Health & Health Sciences

University of Massachusetts - Amherst427 Arnold House, 715 North Pleasant St.

Amherst, MA 01003-9304T 1-413-545-9464

B [email protected]: LauraBBalzer

https://www.balzerlab.com/

INTERESTS• Causal inference and machine learning• Development, evaluation, and implementation of data-driven solutions in Public Health and Medicine• Design and analysis of cluster randomized and pragmatic trials• Analyses with complex measurement, missingness, and dependence• Applications: global health, infectious diseases, community health, epigenetics, behavioral medicine

APPOINTMENT2017–Present Assistant Professor of Biostatistics, University of Massachusetts, Amherst.

Department of Biostatistics and EpidemiologySchool of Public Health and Health Sciences

EDUCATION2010–2015 PhD in Biostatistics, University of California, Berkeley.

• Design and analysis of cluster randomized trials with application to HIV prevention and treatment• Advisors: Drs. Maya Petersen and Mark van der Laan• Berkeley Fellowship: “Awarded to outstanding applicants to doctoral programs in all fields”

2008–2009 MPhil in Computational Biology, University of Cambridge, UK.• Director’s Award for outstanding performance• Graduated 1st in the class

2004–2008 BS in Applied Mathematics, University of Vermont.• Barry M. Goldwater Scholarship Award: “The most prestigious undergraduate scholarship in thenatural sciences, mathematics and engineering in America”

POST-DOCTORAL TRAINING2015–2017 Post-Doctoral Fellow in Biostatistics, Harvard School of Public Health.

• Advisor: Dr. Victor DeGruttola• Harnessing social network information to target interventions and to improve study designs forprogram and policy evaluation

mailto:[email protected]://www.balzerlab.com/

Laura B. Balzer, PhD - Curriculum Vitae - Dec 2019 2/21

HONORS & AWARDS2019 The Distinguished Young Alumna Award, Westover School.2017 Postdoctoral Association 2017 Spring Travel Award, Harvard.2015 Chin Long Chiang Biostatistics Student of the Year, UC Berkeley.

“For her innovative research in HIV prevention and treatment and her many contributions to theBiostatistics Program”

2015 Travel Award: Infectious Disease Research Conference, NIAID/NIH.2014 Gertrude M. Cox Scholarship, ASA.

“For outstanding academic achievement in the University of California, Berkeley biostatistics program,significant contributions to methodological development of causal inference for group-randomizedstudies, inter-departmental cooperation as demonstrated by effective collaborations with epidemiologystudents and faculty, and exceptional commitment to ambitious, engaging, creative and superhero-studded teaching”

2014 Causality in Statistics Education Award, ASA.Jointly with Dr. Maya Petersen to the “individual or team that does the most to enhance the teachingand learning of causal inference in introductory statistics courses”

2014 Travel Award: Joint Statistical Meetings, ASA - San Francisco Bay Area Chpt.2014 Russel M. Grossman Endowment Award, UC Berkeley.2013 3rd place poster, Society for Epidemiologic Research.2012 Outstanding Graduate Student Instructor, UC Berkeley.2012 2nd place at School of Public Health Research Symposium, UC Berkeley.2012 Lois Rifkin Scholarship, UC Berkeley.

2012–2014 Division of Biostatistics stipend for scholastic achievements, UC Berkeley.2010–2012 Berkeley Fellowship, UC Berkeley.

“Awarded to outstanding applicants to doctoral programs in all fields”

2009 Director’s Award for outstanding performance, Cambridge, UK.Equivalent to Distinction; Graduated 1st in the class

2008 Summa Cum Laude, University of Vermont.Graduated 1st in the class

2008 Honors College Scholar, University of Vermont.2008 Mathematics Senior Award, University of Vermont.2008 Statistics Departmental Senior Award, University of Vermont.2007 Sang Kil Nam Scholarship in Mathematics, University of Vermont.

“In recognition of the value of education as a path toward the betterment of mankind”

2007 Barry M. Goldwater Scholarship Award.“The most prestigious undergraduate scholarship in the natural sciences, mathematics and engineeringin America”

2006 Chemistry Rubber Company Award for excellence in Chemistry, University ofVermont.

2004–2008 Presidential Scholarship for academic excellence, University of Vermont.


RESEARCH SUPPORTONGOING

2019–2020 Strategic antiretroviral therapy & HIV testing for youth in rural Africa (SAT-URN)• Funding: NIH-NICHD UG3HD096915 (PI: Havlir)• Role: Sub-Award Principal Investigator

2018–2023 Paternal preconception phthalates and reproductive health - potential media-tion through sperm DNA methylation• Funding: NIH-NIEHS R01ES028298 (PI: Pilsner)• Role: Co-Investigator

2017–2021 Simplified Isoniazid Preventive Therapy Strategy to Reduce TB Burden(SPIRIT)• Funding: NIH-NIAID R01AI125000 (PI: Havlir)• Role: Sub-Award Principal Investigator

2017–2020 Leadership & Operations Center (LOC), AIDS Clinical Trials Group (ACTG);Sustainable East Africa Research in Community Health (SEARCH)• Funding: NIH-NIAID UM1AI068636 (PI: Currier; Havlir)• Role: Sub-Award Principal Investigator

COMPLETED2015–2017 Methods to Advance the HIV Prevention Research Agenda

• Funding: NIH-NIAID R37AI051164 (PI: Degruttola)• Role: Post-Doctoral Scholar

2012–2017 Reducing Failure-to-Initiate ART: Streamlined ART Start Strategy (START)• Funding: NIH-NIAID U01AI099959 (PI: Havlir)• Role: Co-Investigator

2010–2015 Causal Inference Methods for Implementation Science• Funding: NIH-NIAID R01AI074345 (PI: van der Laan)• Role: Graduate student researcher

PROFESSIONAL EXPERIENCE2015-2017 Consultant, SEARCH Collaboration, Makerere University - UC San Francisco.2012–2014 Graduate Student Instructor, UC Berkeley, Berkeley, CA.2010–2015 Graduate Student Researcher, UC Berkeley, Berkeley, CA.2009–2010 Biostatistician, UC Irvine, Irvine, CA.

2009 Computational Biologist, Human Epidemiology Nutrition Growth Ecology (HENGE),University of Cambridge, UK.

2006–2008 Undergraduate Researcher, Interdisciplinary Training in Mathematics and Biology Pro-gram, University of Vermont.


PUBLICATIONS- On Google Scholar∗denotes mentee; ∗∗denotes equal contributions

PEER-REVIEWED PUBLICATIONS[1] L.B. Brown, L.B. Balzer, J. Kabami, D. Kwarisiima, N. Sang, et al. The influence of social networkson antiretroviral therapy initiation among HIV-infected antiretroviral therapy-naïve youth in rural Kenyaand Uganda. J Acquir Immune Defic Syndr, 83:9–15, 2020.

[2] L. Balzer, D. Havlir, M. Kamya, G. Chamie, E. Charlebois, T. Clark, et al. Machine learning toidentify persons at high-risk of HIV acquisition in rural Kenya and Uganda. Clinical Infectious Diseases,In Press, 2019.

[3] S. Puryear, L. Balzer, J. Ayieko, D. Kwarisiima, J.A. Hahn, E. Charlebois, T. Clark, et al. Associationsbetween alcohol use and HIV care cascade outcomes among adults undergoing population-based HIVtesting in East Africa. AIDS, In Press, 2019.

[4] M.P. Fox, J.K. Edwards, R. Platt, and L. Balzer. The critical importance of asking good questions:The role of epidemiology doctoral training programs. Am J Epidemiol, In Press, 2019.

[5] D.J. Heller, L.B. Balzer, D. Kazi, E. Charlebois, D. Kwarisiima, F. Mwangwe, et al. Hypertensiontesting and treatment in Uganda and Kenya through the SEARCH study: an implementation fidelity andoutcome evaluation. PloS ONE, In Press, 2019.

[6] K Potter, J.E. Teng, B. Masteller, C. Rajala, and L.B. Balzer. Examining how dog ‘acquisition’affects physical activity and psychosocial well-being: Findings from the BuddyStudy pilot trial. Animals,9(666), 2019.

[7] D.V. Havlir, L.B. Balzer, E. Charlebois, T.D. Clark, D. Kwarisiima, J. Ayieko, J Kabami, N. Sang,et al. Trial of HIV test and treat via a community health model in rural Africa. New England Journal ofMedicine, 381:219–229, 2019.

[8] H. Saddiki∗ and L.B. Balzer. A primer on causality in Data Science. Journal de la Société Françaisede Statistique, In press, 2019.

[9] V.A. Shetty, L.B. Balzer, K.H. Geissler, and D.L. Chin. Association between specialist office visitsand health expenditures in accountable care organizations. JAMA Netw Open, 2(7):e196796, 2019.

[10] D. Kwarisiima, M. Atukunda, A. Owaraganise, G. Chamie, T. Clark, J. Kabami, V. Jain, D. By-onanebye, F. Mwangwa, L.B. Balzer, et al. Hypertension control in integrated HIV and chronic diseaseclinics in Uganda in the SEARCH study. BMC Public Health, 19(511), 2019.

[11] J. Ayieko, G. Chamie, L. Balzer, D. Kwarisiima, J. Kabami, N. Sang, et al. Mobile, population-wide,hybrid HIV testing strategy increases number of children tested in rural Kenya and Uganda. PediatricInfectious Disease Journal, 37(12):1279–1281, 2018.

[12] S.B. Shade, T. Osmand, A. Luo, R. Aine, E. Assurah, B. Mwebaza, D. Mwai, A. Owaraganise,F. Mwangwa, J. Ayieko, D. Black, L.B. Brown, T.D. Clark, D. Kwarisiima, H. Thirumurthy, C.R. Cohen,E.A. Bukusi, E.D. Charlebois, L. Balzer, et al. Costs of streamlined HIV care delivery in rural Ugandanand Kenyan clinics in the SEARCH study. AIDS, 32(15):2179, 2018.

[13] L.B. Balzer, W. Zheng, M.J. van der Laan, M.L. Petersen, and the SEARCH Collaboration. A newapproach to hierarchical data analysis: Targeted maximum likelihood estimation for the causal effect of acluster-level exposure. Statistical Methods in Medical Research, 28(6):1761–1780, 2018.

https://scholar.google.com/citations?hl=en&user=dSU9MtYAAAAJ


[14] A. Jakubowski, K. Snyman, D. Kwarisiima, N. Sang, R. Burger, L. Balzer, et al. High CD4 countsassociated with better economic outcomes for HIV-positive adults and their HIV-negative householdmembers in the SEARCH trial. PloS ONE, 13(6):e0198912, 2018.

[15] A.I. Naimi and L.B. Balzer. Stacked generalization: An introduction to Super Learning. EuropeanJournal of Epidemiology, 33(5):459–464, 2018.

[16] J.A. Labrecque, J.K. Kaufman, L.B. Balzer, R.F. Maclehose, E. Strumpf, A. Matijasevich, I.S.Santos, and A.J.D. Barros. Effect of a conditional cash transfer program on length-for-age and weight-for-age in Brazilian infants at 24 months using doubly-robust, targeted estimation. Social Science &Medicine, 2011:9–15, 2018.

[17] J. Ayieko, M.L. Petersen, E. Wafula, A. Van Rie, W. Opudo, T.D. Clark, M.R. Kamya, L.B. Balzer,et al. Effect of a patient-centered phone call by a clinical officer at time of HIV testing or re-contact onlinkage to care in rural Kenya. Open Forum of Infectious diseases, 5(1):ofy126, 2018.

[18] C.A. Koss, J. Ayieko, F. Mwangwa, A. Owaraganise, D. Kwarisiima, L.B. Balzer, et al. Earlyadopters of HIV preexposure prophylaxis in a population-based combination prevention study in ruralKenya and Uganda. Clinical Infectious Diseases, 67(15):1853–1860, 2018.

[19] D. Perriat, L. Balzer, R. Hayes, S. Lockman, F. Walsh, et al. Comparative assessment of five large-scale studies of universal HIV testing and treatment in Sub-Saharan Africa. Journal of the InternationalAIDS Society, 21(1), 2018.

[20] W. Zheng, L. Balzer, M. van der Laan, M. Petersen, and the SEARCH Collaboration. Constrainedbinary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.Statistics in Medicine, 37(2):261–279, 2018.

[21] L.B. Balzer. “All generalizations are dangerous, even this one.” - Alexandre Dumas [Commentary].Epidemiology, 28(4):562–566, 2017.

[22] M. Petersen, L. Balzer, D. Kwarsiima, N. Sang, et al. Association of implementation of a universaltesting and treatment intervention with HIV diagnosis, receipt of antiretroviral therapy, and viralsuppression among adults in East Africa. JAMA, 317(21):2196–2206, 2017.

[23] L. Balzer, P. Staples, J. Onnela, and V. DeGruttola. Using network-based simulations to evaluatethe effect of adding targeted PrEP to an ongoing treatment-as-prevention trial. Clinical Trials, Jan:1–10,2017.

[24] L. Balzer, M. van der Laan, M. Petersen, and the SEARCH Collaboration. Adaptive pre-specificationin randomized trials with and without pair-matching. Statistics in Medicine, 35(25):4528–4545, 2016.

[25] M.A. Gianfrancesco, L. Balzer, K.E. Taylor, L. Trupin, et al. Genetic risk and longitudinal diseaseactivity in systemic lupus erythematosus using targeted maximum likelihood estimation. Genes andImmunity, 17:358–362, 2016.

[26] L. Balzer, M. Petersen, M.J. van der Laan, and the SEARCH Collaboration. Targeted estimationand inference of the sample average treatment effect in trials with and without pair-matching. Statisticsin Medicine, 35(21):3717–3732, 2016.

[27] L. Balzer, J. Ahern, S. Galea, and M.J. van der Laan. Estimating effects with rare outcomes andhigh dimensional covariates: Knowledge is power. Epidemiologic Methods, 5(1):1–18, 2016.


[28] M. Pearl, L. Balzer, and J. Ahern. Targeted estimation of marginal absolute and relative associationsin case-control data: An application in social epidemiology. Epidemiology, 27:512–517, 2016.

[29] D. Kwarisiima, L. Balzer, D. Heller, P. Kotwani, et al. Population-based assessment of hypertensionepidemiology and risk factors among HIV-positive and general populations in rural Uganda. PLoS ONE,11(5):e0156309, 2016.

[30] G. Chamie, T.D. Clark, J. Kabami, K. Kadede, E. Ssemmondo, R. Steinfeld, G. Lavoy, D. Kwarisiima,N. Sang, V. Jain, H. Thirumurthy, T. Liegler, L. Balzer, et al. A hybrid mobile HIV testing approachfor population-wide HIV testing in rural East Africa. Lancet HIV, January, 2016.

[31] J. Ahern, L. Balzer, and S. Galea. The role of outlet density and norms in alcohol use disorder.Drug and Alcohol Dependence, 151:144–150, 2015.

[32] L.B. Balzer, M.L. Petersen, M.J. van der Laan, and the SEARCH Consortium. Adaptive pair-matching in randomized trials with unbiased and efficient effect estimation. Statistics in Medicine,34(6):999–1011, 2015.

[33] P. Kotwani, L. Balzer, D. Kwarisiima, T.D. Clark, et al. Evaluating linkage to care for hypertensionafter community-based screening in rural Uganda. Tropical Medicine & International Health, 19(4):459–468, 2014.

[34] G. Chamie, D. Kwarisiima, T.D. Clark, J. Kabami, V. Jain, E. Geng, L.B. Balzer, et al. Uptakeof community-based HIV testing during a multi-disease health campaign in rural Uganda. PloS ONE,9(1):e84317, 2014.

[35] V. Jain, D.M. Byonanebye, T. Liegler, D. Kwarisiima, G. Chamie, J. Kabami, M.L. Petersen, L.B.Balzer, et al. Changes in Population HIV RNA Levels in Mbarara, Uganda During Scale-Up of HIVAntiretroviral Therapy Access. JAIDS, 65(3):327–332, 2014.

[36] M. van der Laan, L. Balzer, and M. Petersen. Adaptive Matching in Randomized Trials andObservational Studies. Journal of Statistical Research, 46(2):113–156, 2012.

BOOK CHAPTERS[37] L.B. Balzer, M.L. Petersen, and M.J. van der Laan. The sample average treatment effect. In M.J.van der Laan and S. Rose, editors, Targeted Learning in Data Science. Springer, 2018.

[38] L.B. Balzer, M.J. van der Laan, and M.L. Petersen. Data-adaptive estimation in cluster randomizedtrials. In M.J. van der Laan and S. Rose, editors, Targeted Learning in Data Science. Springer, 2018.

[39] L. Balzer, M. Petersen, and M.J. van der Laan. Tutorial for causal inference. In P. Buhlmann,P. Drineas, M. Kane, and M. van der Laan, editors, Handbook of Big Data. Chapman & Hall/CRC, 2016.

MANUSCRIPTS UNDER PEER-REVIEW OR REVISION[40] J.L Marcus, W. Sewell, L.B. Balzer∗∗, and D.S. Krakower∗∗. Artificial intelligence and machinelearning for HIV prevention: Emerging approaches to ending the epidemic. 2019.

[41] J. Kabami∗, L.B. Balzer, H. Saddiki∗, J. Ayieko, D. Kwarisiima, et al. Population-level viralsuppression among pregnant and post-partum women in the SEARCH universal test and treat trial. 2019.


[42] L.B. Balzer, J. Ayieko, D. Kwarisiima, G. Chamie, E.D. Charlebois, et al.Far from MCAR: obtaining population-level estimates of HIV viral suppression.https://www.medrxiv.org/content/10.1101/19012781v1, 2019.

[43] C. Marquez, M. Atukunda, L.B. Balzer, G. Chamie, J. Kironde, et al. The age-specific burdenand household and school-based predictors of child and adolescent tuberculosis infection in rural uganda.2019.

[44] C.A. Koss, E.D. Charlebois, J. Ayieko, D. Kwarisiima, J. Kabami, M. Atukunda, L.B. Balzer, et al.Uptake, engagement, and adherence to pre-exposure prophylaxis offered after population-level HIV testingin rural Kenya and Uganda: An observational study. 2019.

[45] S.A. Lauer∗, N.G. Reich, and L.B. Balzer. The covariate-adjusted residual estimator and its use inboth randomized trials and observational settings. https://arxiv.org/abs/1910.11397, 2019.

[46] K. Potter, R.T Marcotte, G.J. Petrucci, C. Rajala, C. Saleeba, D.E. Linder, and L.B. Balzer.Examining the contribution of dog walking to total daily physical activity among dogs and their owners.2019.

[47] A.N. Muiru, E. Charlebois, L.B. Balzer, D. Kwarisiima, A. Elly, D. Black, et al. The epidemiologyof chronic kidney disease (CKD) in rural East Africa: a population-based study. 2019.

[48] K. Potter, B. Masteller, and L. Balzer. Findings from a stealth physical activity interventiontargeting dog owners. 2018.

[49] Y. Chen, W. Zheng, L.B. Brown, G. Chamie, D. Kwarisiima, J. Kabami, T.D. Clark, N. Sang,J. Ayieko, E.D. Charlebois, V. Jain, L. Balzer, et al. Semi-supervised record linkage for construction oflarge-scale sociocentric networks in resource-limited settings: An application to the SEARCH study inrural Uganda and Kenya. 2018.

SELECTED TECHNICAL REPORTS[50] L.B. Balzer, D.V. Havlir, J. Schwab, M.J. van der Laan, M.L. Petersen, and the SEARCH Collabo-ration. Statistical analysis plan for SEARCH Phase I: Health outcomes among adults. Technical report,SEARCH Study Team, 2018: https://arxiv.org/abs/1808.03231.

[51] L.B. Balzer, J. Schwab, M.J. van der Laan, and M.L. Petersen. Evaluation of progress towardsthe UNAIDS 90-90-90 HIV care cascade. Technical Report 357, UC Berkeley, 2017: http://biostats.bepress.com/ucbbiostat/paper357/.

Software: https://github.com/LauraBalzer

• R code for evaluating adult HIV incidence, health, & implementation outcomes for the first phase of theSEARCH Study (Last update: June 22, 2019)

• R code for ISES-ISEE workshop - Introduction to Double Robust Estimation for Causal Inference (Lastupdate: Aug 24, 2018)

• R code to generate simulated data and implement the hierarchical TMLEs (Last update: Mar 12, 2018)

• R code for a paper entitled “Stacked Generalization: An Introduction to SuperLearning” by Naimi andBalzer (Last update: Feb 9, 2018)

https://arxiv.org/abs/1808.03231http://biostats.bepress.com/ucbbiostat/paper357/http://biostats.bepress.com/ucbbiostat/paper357/https://github.com/LauraBalzer


• R code and simulations to illustrate estimation and inference for the sample average treatment effect(SATE) in trials with and without pair-matching. (Last update: Apr 17, 2017)

• R code and simulations to illustrate estimation and inference for the PATE and SATE with the unadjustedestimator, MLE with a priori-specified adjustment set, TMLE with adaptive pre-specification for initialestimation of outcome regression, and C-TMLE including collaborative estimation of the known exposuremechanism. (Last update: Apr 17, 2017)

• R code to implement simulations in the Invited Commentary: ‘All generalizations are dangerous, eventhis one.’- Dumas by Balzer (Last update: Mar 12, 2017)

• R code to evaluate the UNAIDS 90/90/90 Coverage in the SEARCH Study. (Last update: Feb 25, 2017)

ACADEMIC INSTRUCTION• Graduate Course - Introduction to Causal InferenceThis course presents a general framework for causal inference: 1) clear statement of the scientific question,2) definition of the causal model and parameter of interest, 3) assessment of identifiability - that is,linking the causal effect to a parameter estimable from the observed data distribution, 4) choice andimplementation of estimators including parametric and semi-parametric methods, and 5) interpretationof findings. The estimation methods include G-computation, inverse probability of treatment weighting(IPTW), and targeted maximum likelihood estimation (TMLE) with Super Learning.

- ASA’s Causality in Statistics Education Award - “individual or team that does the most to enhancethe teaching and learning of causal inference in introductory statistics courses”

- Course materials available at www.ucbbiostat.com

2019 Instructor - UMass Amherst [3 credits]• Overall course rating: pending

2018 Instructor - UMass Amherst [3 credits]• Overall course rating: 4.6/5.0

2017 Instructor - UMass Amherst [3 credits]• Overall course rating: 4.1/5.0

2013 Graduate student instructor - UC Berkeley [3 credits]• Instructor rating: 6.83/7.00


• Undergraduate Seminar - Data Science to Improve Public HealthEver wonder why Data Scientists have been labeled the “sexiest job of the 21st Century”? Is Big Datareally a revolution or simply hype? Why is it so hard to move from correlation to causation? Drawing onreal examples from Public Health, this course will answer these and other pressing questions. Studentswill be introduced to a formal research framework, including specifying a well-defined scientific question,formally representing background knowledge and uncertainties, and finally answering their question usingmodern methods in machine learning and causal inference.

2018 Instructor - UMass Amherst [1 credit]• Overall course rating: 4.0/4.0

https:/www.ucbbiostat.com


• Graduate Seminar - Hot Topics in Data ScienceThe seminar will be a mixture of guest lectures from leading researchers in academia and industry (e.g.Google) as well as group presentations on top papers in Machine Learning and Causal Inference. We willalso have dedicated time for professional development, including an interactive workshop “Professionaland Multi-disciplinary Communication Strategies” and the discussion of tenure-track job searches.

2018 Instructor - UMass Amherst [1 credit]

• Graduate Course - Causal Inference IIThis course covers more advanced causal topics: longitudinal causal models, identifiability, and estimation;direct and indirect effects; dynamic treatment regimes; stochastic interventions; community-basedinterventions; semi-parametric approaches to hierarchical data; and Collaborative targeted maximumlikelihood estimation.

2014 Instructor - UC Berkeley [2 credits]• Instructor rating: 7.00/7.00


WORKSHOPS & SHORT COURSES

• Introduction to Parametric and Semi-parametric Estimators for Causal InferenceThis workshop introduces the Causal Roadmap approach to scientific questions. The focus is on estima-tion with a simple substitution estimator (parametric G-computation), inverse probability of treatmentweighting, and targeted maximum likelihood estimation with Super Learner. Using an applied example,participants implement these estimators in R.

2020 Instructor - Society for Epidemiologic Research, Boston, MA [Upcoming]2019 Instructor - NICHD, Bethesda, MD2018 Instructor - SERtalks, Boston, MA

Instructor - Society for Epidemiologic Research, Baltimore, MDInstructor - 32nd New England Statistics Symposium, Amherst, MAInstructor - SERtalks, Los Angeles, CA

2017 Instructor - SERtalks, New York, NYInstructor - University of Utah, School of Medicine, Salt Lake City, UT

2016 Instructor - Society for Epidemiologic Research, Miami, FLInstructor - SERtalks, Minneapolis, MNInstructor - University of California, San Francisco, San Francisco, CA

2015 Instructor - Society for Epidemiologic Research, Denver, CO

• Introduction to causal inference for multiple time point (longitudinal) exposuresThis workshop applies the Causal Roadmap to longitudinal data structures, including survival outcomessubject to censoring, and to the joint causal effects of multiple interventions, including cumulativeeffects of treatment over time and controlled direct effects. We will cover longitudinal causal models,identification in the presence of time-dependent confounding, and estimation of joint treatment effectsusing G-computation, inverse probability weighting, and targeted maximum likelihood estimators.


2020 Instructor - Society for Epidemiologic Research, Boston, MA [Upcoming]2019 Instructor - Society for Epidemiologic Research, Minneapolis, MN2017 Instructor - X Congresso Brasileiro de Epidemiologia, Florianópolis, Brazil

• Big data, machine learning techniques to investigate health effects in environmental healthstudiesThis course will present key methodological challenges that arise in environmental health and providerecent methods that can be used to deal with these challenges. The focus is on modern solutions tomultiple testing, model misspecification, and causal inference as applied to environmental health data,with a focus on assessing health effects of chemical mixtures. Participants will gain both a theoreticalunderstanding as well as practical experience with a hands-on session using R software.

2018 Instructor - International Society of Exposure Science & the International Society forEnvironmental Epidemiology (ISES-ISEE), Ottawa, Canada

INVITED SEMINARS & RESEARCH COLLOQUIUM

1. University of Massachusetts, Amherst - Kinesiology Department: “Optimizing the design & analysis ofrandomized trials”, Feb2019

2. University of California, Los Angeles - UCLA Statistics Seminar: “Design & Analysis of Pragmatic,Cluster Randomized Trials”, Feb2019

3. University of California, Berkeley - Berkeley Statistical Methods Seminar: “TMLE for the Analysis ofCluster Randomized Trials with Application to the Primary Analysis in SEARCH”, Sep2018.

4. University of Massachusetts, Amherst - Data Science for Health Lab: “Ensemble & Targeted Learningfor HIV Prevention & Treatment”, Jul2018.

5. University of Massachusetts, Amherst - Statistics & Probability Seminar: “A new approach to hierarchicaldata analysis: Targeted maximum likelihood estimation for the causal effect of a cluster-level exposure”,Apr2018.

6. University of Massachusetts Medical School - Quantitative Methods Core Methods Seminars: “TargetedLearning to evaluate the effects of community-based interventions: the SEARCH trial & HIV preventionin East Africa”, Feb2018.

7. Amherst College Statistics & Data Science Colloquia: “Estimating the Impact of Cluster-Based Interven-tions: the SEARCH trial and HIV prevention in East Africa”, Feb2018.

8. Yale University - Public Health Modeling Concentration Seminar Series: “Causal inference with cluster-level exposures: HIV prevention in East Africa”, Jan2018.

9. University of Massachusetts, Amherst - Computational Social Science Institute: “Estimating the Effectsof Community-based Interventions: SEARCH Trial & HIV prevention in East Africa”, Dec2017.

10. 5College Stats & Data Science Research Bytes (Amherst, MA): “Machine Learning & Causal Inferencefor HIV Prevention & Treatment, Nov2017.


11. University of Massachusetts, Amherst - Statistics Working Group: “Why Bother with Causal Inference?”,Sept2017.

12. Yale University - Workshop on Quantitative Research Methods: “Targeted Learning in the SEARCHtrial and HIV prevention in East Africa”, Mar2017.

13. Harvard School of Public Health - Quantitative Group for Research on Infectious Diseases: “TargetedLearning in the SEARCH trial and HIV prevention in East Africa”, Sep2016.

14. Université de Montréal - Faculté de Pharmacie: “Estimating the Impact of Community-Based Interven-tions: the SEARCH Trial and HIV Prevention in East Africa”, Oct2016.

15. McGill University - Department of Epidemiology, Biostatistics & Occupational Health: “Estimating theImpact of Community-Based Interventions: the SEARCH Trial and HIV Prevention in East Africa”,Oct2016.

16. Harvard University - The Institute of Quantitative Social Science: “Targeted Learning in the SEARCHtrial and HIV prevention in East Africa”, Mar2016.

17. University of California, Berkeley - School of Social Welfare Research Colloquium: “Introduction toCausal Inference: A roadmap of research in social welfare and public health”, Feb2016.

18. University of Vermont - Statistics Colloquium: “Estimating the Impact of Community-Based Interventions:the SEARCH Trial and HIV Prevention in East Africa”, Oct2014.

GUEST LECTURES1. University of California, Berkeley - Methods in Social Epidemiology (Spr2019): “Introduction to Targeted

Learning”.

2. University of Massachusetts, Amherst - Analysis of Categorical Data in Public Health (Fa2018): “Esti-mating Effects in Cluster Randomized Trials: the SEARCH Trial in Rural Uganda & Kenya”.

3. University of Massachusetts, Amherst - Advanced Epidemiological Methods (Spr2018): “IntegratingCausal Modeling and Statistical Estimation”.

4. University of California, Berkeley - Methods in Social Epidemiology (Spr2018): “Introduction to TargetedLearning”.

5. Mount Holyoke College - Topics in Biostatistics (Spr2018): “Targeted maximum likelihood with SuperLearning to evaluate progress towards HIV care cascade goals: an example from the SEARCH “test andtreat” study”.


7. Harvard School of Public Health - Methods I (Fa2016): “Introduction to Targeted Learning”.


9. Harvard School of Public Health - Statistical Inference I (Spr2016): “Introduction to Targeted Learning”.

10. Harvard School of Public Health - Quantitative Group for Research on Infectious Diseases (Fa2015):“Introduction to Longitudinal Causal Models, Marginal Structural Models and Longitudinal IPTW”.


11. Harvard School of Public Health - Quantitative Group for Research on Infectious Diseases (Fa2015):“Introduction to Targeted Learning”.


13. University of California, Berkeley - Introduction to Causal Inference (Fa2014): “Estimating the Impactof Community-Based Interventions: the SEARCH Trial and HIV Prevention in East Africa”.

14. University of California, Berkeley - Methods in Social Epidemiology (Spr2014): “Introduction to TargetedLearning”, 2014.

15. University of California, Berkeley - Epidemiologic Methods II (Fa2013): “Designing the SEARCH trial:Ph250b in Practice”.

16. University of California, Berkeley - Introduction to Causal Inference (Fa2013): “Adventures in Linkingthe SCM and the Observed Data”.


18. University of California, Berkeley - Causal Consulting (Fa2012): “Do-Si-Do: A Two-Stage Design andTMLE for Estimating Causal Effects of Community-Based Interventions”.

19. University of California, Berkeley - Special Topics in Biostatistics: Adaptive Designs (Fa2012): “PairMatching in Randomized Trials: Fairy Tales & Super Heroes”.


MENTORSHIPCurrent Alejandra Benitez, Doctoral committee member, Biostatistics, External - UC Berkeley.

Joshua Freeman, Doctoral committee member, Epidemiology.Gabriel Reif, Doctoral committee member, Education.Sam Witty, Synthesis project advisor, Computer Science.

Past Emily Peterson, Doctoral committee member, Biostatistics, Dec2019.Post-doctoral fellow at Emory University

Gregory Guranich, Master’s committee member, Biostatistics, Aug2019.Researcher at Alkema Lab

Stephen Lauer, Doctoral Co-Advisor, Biostatistics, Feb2019.Post-doctoral fellow at Johns Hopkins University

Caroline Kusiak, Master’s committee member, Biostatistics, Sept2018.Verily (Google)

Julianne Higgins, William Lee Science Impact Program (Lee-SIP) Scholar & Common-wealth Honors College Honors Research Assistant Fellowship, Mathematics (Undergraduate).

DEPARTMENTAL & UNIVERSITY SERVICE2019-2020 Director, UMass Causality Lab.


Chair, Graduate Affairs Committee.Committee member, Curriculum.Committee member, MS degree development & recruitment.Academic advisor, Two PhD students; one MS student, + co-advising seven MS students.

2018–2019 Founder & Director, UMass Causality Lab.Committee member, Departmental Personnel.Committee member, Curriculum.Academic advisor, One PhD student; two MS students.

2017–2018 Committee member, Admissions.Committee member, Student outreach.Co-organizer, Departmental seminar series.Poster judge, 21st Annual SPHHS Research Day.Abstract judge, Delta Omega Public Health Honorary Society.Academic advisor, Two MS students.

EXTERNAL SERVICE2019–2020 Representative, Universal Test & Treat Trials Consortium (UT3C), Bordeaux-London-

Boston-San Francisco.SER Champion, Society of Epidemiologic Research, International.

2018–2019 Representative, Universal Test & Treat Trials Consortium (UT3C), Bordeaux-London-Boston-San Francisco.Local organizing committee, StatFest 2018, ASA & Amherst College.SER Champion, Society of Epidemiologic Research, International.Invited speaker, Career panel, Stoneleigh-Burnham.Poster judge, Society of Epidemiologic Research Conference, Minneapolis, MN.Abstract review, Society of Epidemiologic Research Conference, Minneapolis, MN.

2017–2018 Representative, Universal Test & Treat Trials Consortium (UT3C), Bordeaux-London-Boston-San Francisco.Board member, Honors College Advisory Board, University of Vermont.Invited session organizer, New England Statistics Symposium, Amherst, MA.Poster judge, New England Statistics Symposium, Amherst, MA.Abstract review, Society of Epidemiologic Research Conference, Baltimore, MD.Poster judge, Society of Epidemiologic Research Conference, Baltimore, MD.

2016–2017 Organizer, Quantitative Group for Research on Infectious Diseases, Harvard T.H. ChanSchool of Public Health.Representative, Universal Test & Treat Trials Consortium (UT3C), Bordeaux-London-Boston-San Francisco.


Board member, Honors College Advisory Board, University of Vermont.Poster judge, Society of Epidemiologic Research Conference, Seattle, WA.

2015–2016 Organizer, Conference on Causal Inference with Highly Dependent Data in CommunicableDisease Research, Cambridge, MA.Representative, Universal Test & Treat Trials Consortium (UT3C), Bordeaux-London-Boston-San Francisco.Board member, Honors College Advisory Board, University of Vermont.Invited session organizer, Conference on Causal Inference with Highly Dependent Datain Communicable Disease Research, Cambridge, MA.Mentored poster chats, Society of Epidemiologic Research Conference, Miami, FL.Abstract review, Society of Epidemiologic Research Conference, Miami, FL.

2014–2015 Member, Tenure-track Biostatistics search committee, UC Berkeley.Board member, Honors College Advisory Board, University of Vermont.Member, School of Public Health Graduate Recruitment & Diversity Services, UC Berkeley.Invited session organizer, Atlantic Causal Inference Conference, Philadelphia, PA.Representative, Honors College Alumni Panel, University of Vermont.

2013–2014 Member, School of Public Health Graduate Recruitment & Diversity Services, UC Berkeley.

2012–2013 Member, School of Public Health Graduate Recruitment & Diversity Services, UC Berkeley.

2011–2012 Elected representative, School of Public Health Student Government, UC Berkeley.

REVIEW FOR SCIENTIFIC JOURNALSEditorialBoard:

International Journal of BiostatisticsJournal of Causal Inference

Reviewer: American Journal of EpidemiologyAnnals of EpidemiologyBiometricsBMJ OpenClinical Infectious DiseasesEpidemiologyInternational Journal of EpidemiologyJournal of Causal InferenceJournal of the International AIDS SocietyJournal of RheumatologyPLoS ONESocial Science & Medicine - Population HealthStatistics and Probability LettersStatistics in MedicineStatistical Methods in Medical Research


REVIEW OF SCIENTIFIC GRANTS & REPORTS2018 Netherlands Organisation for Health Research and Development (ZonMw) Health Care

Efficiency Research ProgrammePatient-Centered Outcomes Research Institute

2017 Medical Research Council (UK), Methodology Research PanelPatient-Centered Outcomes Research Institute

MEMBERSHIPS2018–Present New England Statistical Society (NESS)2016–Present International AIDS Society (IAS)2013–Present Society of Epidemiologic Research (SER)2012–Present American Statistical Association

2012–2015 Western North American Region of the International Biometric Society2008 Phi Beta Kappa

SELECTED CONFERENCE & SYMPOSIUM PRESENTATIONS(∗denotes mentee)

1. M.D. Hickey, J. Ayieko, D. Kwarisiima, F.J. Opel, A.Owaraganise, L. Balzer, et al. Improved time incare and viral suppression with streamlined care in the SEARCH Study.

2020[Upcoming]

Conference on Retroviruses and Opportunistic Infections, Boston, MA (Invited Speaker)

2. L. Brown, Y. Chen, L. Balzer, G. Chamie, J. Ayieko, et al. Using social networks to reach individualswith low CD4 at high risk of death.

2020[Upcoming]

Conference on Retroviruses and Opportunistic Infections, Boston, MA (Poster)

3. S.B. Puryear, A. Mucunguzi, L. Balzer, J. Kironde, J.A. Hahn, et al. Alcohol use is associated withincident TB infection in HIV+ and HIV- Ugandan adults.

2020[Upcoming]


4. Y. Chen, G. Chamie, D. Kwarisiima, L. Balzer, J. Kabami, et al. HIV+ persons in rural Uganda withfewer social connections have lower HIV suppression.

2020[Upcoming]


5. C.S. Camlin, E.D. Charlebois, M.L. Petersen, L. Balzer, T.B. Neilands, et al. Metrics of mobility bysex are associated with HIV incidence in rural Kenya & Uganda.

2020[Upcoming]



6. S.B. Puryear, D. Kwarisiima, J. Ayieko, J.A. Hahn, A. Mucunguzi, S. Ogachi, L. Balzer, et al. SEARCHTest & Treat intervention improves viral suppression among hazardous drinkers.

2020[Upcoming]


7. L. Balzer. Far from MCAR: Machine learning to flexibly adjust for missing data.2019 Dean’s Symposium “Statistics and the Life Sciences: Creating a Healthier World”, Boston

University (Invited Speaker)

8. L. Balzer. Machine Learning for Causal Inference.2019 Kidney Week 2019, Washington, D.C. (Invited Speaker)

9. C. Marquez, Y. Chen, M. Atukunda, J. Kironde, C. Chamie, L. Balzer, et al. Social network character-istics are associated with prevalent tuberculosis infection among people living with and without HIV innine communities in rural Uganda.

2019 23nd International AIDS Conference, Mexico City, Mexico (Invited Talk)

10. C. Koss, J. Ayieko, D. Kwarisiima, M. Atukunda, L. Balzer, et al. PrEP uptake, engagement, andadherence following population-wide HIV testing in tural Kenya and Uganda in the SEARCH Study.

2019 23nd International AIDS Conference, Mexico City, Mexico (Poster)

11. S. Puryear, J. Ayieko, D. Kwarisiima, J. Hahn, L. Balzer, et al. Increased levels of current alcohol useare associated with worse HIV care cascade outcomes among HIV-positive adults in rural Kenya andUganda in the SEARCH Trial.

2019 23nd International AIDS Conference, Mexico City, Mexico (Poster)

12. L. Balzer. Biologically or socially transmitted outcomes? Be (un)certain of your uncertainty!2019 Society for Epidemiologic Research, Minneapolis, MN (Invited Speaker)

13. L. Balzer. Super Learning vs. traditional approaches for population-based HIV risk assessment in ruralEast Africa.

2019 Society for Epidemiologic Research, Minneapolis, MN (Invited Speaker)

14. L. Balzer. An overview of Big Data: Promises and potential pitfalls.2019 The Association for Research in Vision and Ophthalmology (ARVO) Conference 2019,

Vancouver, Canada (Invited Speaker)

15. L. Balzer. Data-adaptive estimation to control for missing data, to increase efficiency, and for riskprediction in the SEARCH Study

2019 NIAID Conference: Statistical challenges & opportunities in HIV/AIDS research in the eraof getting-to-zero HIV infections, Philadelphia, PA (Invited Speaker)

16. J. Kabami∗, H. Saddiki∗ , J. Ayieko, D. Kwarisiima, A. Mucunguzi, E. Charlebois, T. Clark, E. Bukusi,C. Cohen, P. Musoke, M. Petersen, D. Havlir, M. Kamya, L. Balzer, G. Chamie. SEARCH interventionincreases viral suppression among pregnant and postpartum women.

2019 Conference on Retroviruses and Opportunistic Infections, Seattle, WA (Poster)


17. G. Chamie, N. Sang, D. Kwarisiima, J. Kabami, K. Kadede, I. Bagala, A. Mucunguzi, T. Clark, L.Balzer, et al. Yield of HIV testing and re-engagement of key populations in Uganda and Kenya.


18. L. Brown, L. Balzer, J. Kabami, D. Kwarisiima, N. Sang, J. Ayieko, et al. Social networks and tiestrength predict outcomes of HIV+ youth in SEARCH trial.


19. H. Thirumurthy A. Jakubowski, Y. He, J. Kabami, D. Kwarisiima, N. Sang L. Balzer, et al. Socioeco-nomic impacts of universal antiretroviral therapy in the SEARCH trial.


20. D. Kwarisiima, Y. Mwinike, J. Ayieko, A. Mucunguzi, W. Olilo, L. Balzer, et al. Hypertension controlin integrated HIV/NCD clinics in the SEARCH study.


21. M. Kamya, M.L. Petersen, D. Kwarisiima, J. Ayieko, N. Sang, J. Kabami, T.D. Clark, E.D. Charlebois,L. Balzer, et al. SEARCH intervention reduces mortality at a population-level in men with low CD4count.

2019 Conference on Retroviruses and Opportunistic Infections, Seattle, WA (Invited Talk)

22. L. Balzer. Pragmatic Trials To Bridge Efficacy to Effectiveness.2018 HIV prevention efficacy trials design of the future (HVTN Conference), Seattle, WA

(Invited Speaker)

23. J. Higgins∗, L. Balzer. Towards Generalizability: Recovering from Non-Random Participant Selectionand Measurement

2018 Research Experiences for Undergraduates (REU) Poster Symposium, Amherst, MA (Poster)

24. D. Havlir, E. Charlebois, L. Balzer T. Clark, D. Kwarisiima, J. Ayieko, J. Kabami, N. Sang, et al.SEARCH community cluster randomized study of HIV “test and treat” using multi-disease approach andstreamlined care in rural Uganda and Kenya.

2018 22nd International AIDS Conference, Amsterdam, Netherlands (Late-breaker Oral)

25. B. Jewell, L. Balzer, T. Clark, E. Charlebois, S.R. Maddali, M. Kamya, D.V. Havlir, M.L. Petersen, A.Bershteyn. Modeling Projected HIV Incidence in the SEARCH Study of Treatment as Prevention inEast Africa.

2018 22nd International AIDS Conference, Amsterdam, Netherlands (Poster)

26. S. Lauer∗, L. Balzer, E. Ray, S. Iamsirithaworn, J. Lessler, N. Reich. Building on forecasting modelsto assess the impact of an intervention.

2018 Society for Epidemiologic Research, Baltimore, MD (Poster)2018 New England Statistics Symposium, Amherst, MA (Poster)2018 MIDAS Networking Meeting, Bethesda, MD (Poster)2017 Epidemics 6, Sitges, Spain (Poster)


27. L. Balzer. Introduction to and overview of the distinction between generalizability and transportability.2018 Society for Epidemiologic Research, Baltimore, MD (Invited Talk)

28. L. Balzer. Multilevel Madness.2018 Society for Epidemiologic Research, Baltimore, MD (Poster)

29. L. Balzer. Discussant: Modern Methods for Missingness.2018 New England Statistics Symposium, Amherst, MA (Invited Talk)

30. D. Kwarisiima, J. Kabami, N. Sang, K. Kadede, A. Mucunguzi, K. Snyman, T. Clark, E. Bukusi,T. Liegler, E. Charlebois, L. Balzer, et al. Who remains untested following near-universal (>95%)population HIV testing?

2018 Conference on Retroviruses and Opportunistic Infections, Boston, MA (Invited Talk)

31. C. Marquez, A Mucunguzi, G. Chamie, L. Balzer, et al. Mobility predicts incident TB infection inchildren & adults in rural Uganda

2018 Conference on Retroviruses and Opportunistic Infections, Boston, MA (Poster)

32. J. Ayieko, E. Wafula, W. Opudo, C. Cohen, E. Bukusi, T. Clark, L. Balzer, et al. Phone call fromclinical officer at HIV testing/re-contact improves linkage to care


33. L. Balzer. Causal inference in a big data world - The roadmap2017 X Congresso Brasileiro de Epidemiologia, Florianópolis, Brazil (Invited Talk)

34. L. Balzer. The roadmap - a systematic approach from the causal question through the statisticalanalysis and to impact.

2017 Joint Statistical Meetings, Baltimore, MD (Invited Talk)

35. L. Balzer, W. Zheng, M. van der Laan, M. Petersen. A new approach to hierarchical data analysis:targeted maximum likelihood estimation of cluster-based exposures under interference.

2017 Society for Epidemiologic Research, Seattle, WA (Poster)

36. L. Balzer, M. van der Laan, M. Petersen. Targeted Maximum Likelihood with Super Learning toevaluate progress towards HIV care cascade goals: An example from the SEARCH “test and treat” study.

2017 Society for Epidemiologic Research, Seattle, WA (Contributed Talk)

37. W. Zheng, N. Sang, G. Chamie, L. Balzer, et al. Social networks and HIV prevalence in Kenya in theSEARCH study.

2017 Conference on Retroviruses and Opportunistic Infections, Seattle, WA (Invited Talk)

38. L. Balzer, N. Sang, A. Plenty, T. Liegler, et al. Baseline population HIV cascade and 2-yr outcome ofHIV+ children in the SEARCH trial.



39. C. Marquez, A. Mucunguzi, G. Chamie, D. Kwariisima, T. Ruel, L. Balzer, et al. High TB infectionrate in children & young adults in rural Uganda in the SEARCH trial.


40. M. Petersen, L. Balzer, D. Kwarsiima, N. Sang, et al. SEARCH test and treat study in Uganda andKenya exceeds the UNAIDS 90-90-90 cascade target by achieving 81% population-level viral suppressionafter 2 years.

2016 21st International AIDS Conference, Durban, South Africa (Late-breaker Oral)

41. L. Balzer, W. Zheng, T. Ruel, E.D. Charlebois, et al. Changing social networks and increased HIVprevalence in Kenyan adolescent women.

2016 21st International AIDS Conference, Durban, South Africa (Poster)

42. L. Balzer. Why bother with TMLE (targeted maximum likelihood estimation)?2016 Society for Epidemiologic Research, Miami, FL (Poster)

43. L. Balzer, P. Staples, J. Onnela, V. DeGruttola. Using Network-based Simulations to Evaluate theEffect of Adding Targeted PrEP to an Ongoing Treatment-as-Prevention Trial.

2016 Society for Epidemiologic Research, Miami, FL (Poster)2015 Infectious Disease Research Conference (NIAID/NIH), Bethesda, MD (Invited Talk)

44. W. Zheng, L. Balzer, L. Brown, N. Sang, et al.. Local social network features predict HIV testinguptake in a rural Ugandan community.


45. L. Balzer, M. van der Laan, M. Petersen, the SEARCH Consortium. Adaptive Pre-specification inRandomized Trials With and Without Pair-Matching.

2015 Infectious Disease Research Conference (NIAID/NIH), Bethesda, MD (Poster)Society for Epidemiologic Research, Denver, CO (Poster)Atlantic Causal Inference Conference, Philadelphia, PA (Poster)

46. L. Balzer, M. Petersen, M. van der Laan, the SEARCH Consortium. Estimating the Sample AverageTreatment Effect in the SEARCH trial.

2015 Society for Epidemiologic Research, Denver, CO (Poster)

47. M. van der Laan, L. Balzer, M. Petersen. Estimation and Inference for the Sample Average TreatmentEffect in Cluster Randomized Trials.

2015 Atlantic Causal Inference Conference, Philadelphia, PA (Invited Talk)

48. L. Balzer, M. Petersen, M. van der Laan. Pair-Matching & Estimation of the Intervention Effect in theSEARCH trial.

2014 Joint Statistical Meetings, Boston, MA (Contributed Talk)SFASA Student Travel Awards Seminar, Boston, MA (Invited Talk)Atlantic Causal Inference Conference, Providence, RI (Poster)


49. J. Ahern, L. Balzer, M. van der Laan. A rigorous system to determine the health impacts of policiesand programs: Simulations to optimize study design and analysis.

2013 Berkeley Data Science Initiative Symposium, Berkeley, CA (Poster)NIH High Risk-High Reward Research Symposium, Bethesda, MD (Poster)

50. L. Balzer, M. Petersen, M. van der Laan. Pair-Matching - Theory vs. Practice: Adaptive Matching inthe SEARCH trial.

2013 Society for Epidemiologic Research, Boston, MA (Poster)Western North American Region of IBS, Los Angeles, CA (Invited Talk)

2012 School of Public Health Research Symposium, Berkeley, CA (Poster)

51. L. Balzer, M. Pearl, J. Ahern, M. van der Laan. Estimating Effects on Rare Outcomes: Knowledge isPower.

2013 Western North American Region of IBS, Los Angeles, CA (Invited Talk)Atlantic Causal Inference Conference, Boston, MA (Poster)

52. M. Pearl, L. Balzer, J. Ahern. Low-income neighborhoods and very preterm birth: an application ofcase-control-weighted targeted maximum likelihood estimation.

2013 Society for Epidemiologic Research, Boston, MA (Contributed Talk)Society for Pediatric & Perinatal Epidemiologic Research (SPER), Boston, MA (ContributedTalk)

53. L. Balzer, M. Petersen, J. Schwab, M. van der Laan. Estimating the impact of community-levelinterventions: The SEARCH Trial and HIV Prevention in Sub-Saharan Africa.

2012 Western North American Region of IBS, Fort Collins, CO (Invited Talk)

54. L. Balzer, M. Petersen, M. van der Laan. Why Match in Individually and Cluster Randomized Trials?2012 Atlantic Causal Inference Conference, Baltimore, MD (Poster)

55. L. Balzer, D. Bentil. Minimal Mathematical Model for Activated Protein C Regulation of Factor Va2008 Student Research Conference, University of Vermont, Burlington, VT (Invited Talk)

IN THE NEWS & MEDIA• Balzer and International Team Evaluate Community Health Approach to Universal HIV Testing andTreatment in Rural East Africa, Inside UMass, Oct 1, 2019.

• Intensive Anti-H.I.V. Efforts Meet With Mixed Success in Africa, The New York Times, July 18, 2019.

• Balzer Receives Distinguished Young Alumna Award, The SPHHS E-Newsletter, June 13, 2019.

• Balzer Discusses Trial Design at HIV Prevention Symposium, Inside UMass, Nov 19, 2018.

• Balzer to Lead Workshop on Estimators for Causal Inference, The SPHHS E-Newsletter, Sept 20, 2018.

• Balzer, International Team Lead Community-Based HIV Trial in East Africa, Inside UMass, Aug 7, 2018.

https://www.umass.edu/newsoffice/article/balzer-and-international-team-evaluatehttps://www.umass.edu/newsoffice/article/balzer-and-international-team-evaluatehttps://www.nytimes.com/2019/07/17/health/hiv-testing-treatment-africa.htmlhttps://www.umass.edu/sphhs/news-events/balzer-receives-distinguished-young-alumna-awardhttp://www.umass.edu/sphhs/news-events/balzer-discusses-trial-design-hiv-prevention-symposiumhttps://www.umass.edu/sphhs/news-events/balzer-lead-workshop-estimators-causal-inferencehttp://www.umass.edu/newsoffice/article/balzer-international-team-lead-community


• ‘Test and Treat’ Programs Reduce HIV Infections: Multi-disease attack shows benefits across the board,MedPage Today, July 27, 2018.

• Multi-disease health fairs, universal “test and treat” help East African communities achieve HIVbenchmarks, by National Institutes of Health, July 25, 2018.

• Balzer Examines Super Learning Prediction Methodology, The SPHHS E-Newsletter, July 23, 2018.

• African study exceeds U.N. ‘test and treat’ goal for ending HIV pandemic, Reuters, July 20, 2016.

• SEARCH study exceed 90-90-90 targets after 2 years of ‘test and treat’ for HIV in rural East Africa, aidsmap,July 20, 2016.

• How a remote Kenyan island is helping create world-class HIV care, PBS NewsHour, July 15, 2016.

• Strength and Solutions In Numbers, Berkeley Health Magazine, June 2015.

• Biostatistics teaching team receives ASA education award for innovative excellence, UC Berkeley Schoolof Public Health, Aug 2014.

• American Statistical Association Announces Recipients of 25th Annual Gertrude M. CoxScholarships, ASA News, Aug 2014.

• Cal Berkeley Petersen, Balzer To Be Presented 2014 Causality in Statistics Education Award, ASA News,July 2014.

• Top Honors, by Thomas Weaver, Vermont Quarterly, Fall 2007.

• Creating a Global Impact - CEMS Student Wins Highly Competitive Goldwater Scholarship, The Uni-versity of Vermont, April 2007.

https://www.medpagetoday.com/meetingcoverage/iac/74270https://www.nih.gov/news-events/news-releases/multi-disease-health-fairs-universal-test-treat-help-east-african-communities-achieve-hiv-benchmarkshttps://www.nih.gov/news-events/news-releases/multi-disease-health-fairs-universal-test-treat-help-east-african-communities-achieve-hiv-benchmarkshttps://www.umass.edu/sphhs/news-events/balzer-examines-super-learning-prediction-methodologyhttp://uk.reuters.com/article/us-africa-aids-idUKKCN10017Nhttp://www.aidsmap.com/page/3073046https://www.youtube.com/watch?v=KGBRm9MJDwYhttp://berkeleyhealth.berkeley.edu/2015/06/strength-and-solutions-in-numbers/http://sph.berkeley.edu/biostatistics-teaching-team-receives-asa-education-award-innovative-excellencehttp://www.amstat.org/newsroom/pressreleases/2014-25thAnnualCoxScholarships.pdfhttp://www.amstat.org/newsroom/pressreleases/2014-25thAnnualCoxScholarships.pdfhttp://www.amstat.org/newsroom/pressreleases/2014-CausalityinStatEdAward.pdfhttp://alumni.uvm.edu/vq/fall2007/notebook.asphttp://www.uvm.edu/~cems/?Page=alumni/students/lbalzer.php&SM=alumni/_alumnimenu.html

INTERESTSAPPOINTMENTEDUCATIONPOST-DOCTORAL TRAININGHONORS & AWARDSRESEARCH SUPPORTPROFESSIONAL EXPERIENCEPUBLICATIONS- blueOn Google Scholar PEER-REVIEWED PUBLICATIONSBOOK CHAPTERSMANUSCRIPTS UNDER PEER-REVIEW OR REVISIONSELECTED TECHNICAL REPORTS

Laura B. Balzer, PhD - UMass Amherst · Laura B. Balzer, PhD DepartmentofBiostatistics&Epidemiology SchoolofPublicHealth&HealthSciences UniversityofMassachusetts-Amherst...

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