About Our People, Mission, and Vision

The objective that guides Dr. Paltiel's scholarly activities is to promote a reasoned approach to decision making and resource allocation in public health and medicine. Trained in the field of Operations Research, Dr. Paltiel designs and implements policy models and cost-effectiveness analyses. He has a special interest and expertise in HIV/AIDS and has published broadly on the cost-effectiveness of testing, prevention, treatment, and care, both in the United States and around the world.

Forrest Crawford's work focuses on mathematical and statistical problems related to discrete structures and stochastic processes in epidemiology, public health, biomedicine, and evolutionary science.

Dr. Chen received his Ph.D. in Environmental Science and Engineering in 2016 from Nanjing University in China. During 2014-2015, he served as a Visiting Scholar at the Columbia University Mailman School of Public Health. Prior to joining the Yale School of Public Health faculty in July 2019, he was an Alexander von Humboldt Postdoc Fellow at Helmholtz Zentrum München-German Center for Environmental Health.Dr. Chen’s research focuses on the intersection of climate change, air pollution, and human health. His work involves applying multidisciplinary approaches in climate and air pollution sciences, exposure assessment, and environmental epidemiology to investigate how climate change may impact human health. Much of this work has been done in China, Europe, and the U.S.

Dr. Cohen is an infectious disease epidemiologist whose primary research focus is tuberculosis. He is particularly interested in understanding how TB drug-resistance and medical comorbidities such as HIV frustrate current efforts to control epidemics, with an ultimate goal of developing more effective approaches to limit the morbidity caused by this pathogen. Dr. Cohen's training is in epidemiology and clinical medicine, and his work includes mathematical modeling, fieldwork, and analysis of programmatic data. His research program is currently funded by NIH and US CDCAwards.

Laura Forastiere is an Assistant Professor in the Department of Biostatistics at Yale School of Public Health. Her methodological research is focused on methods for assessing causal inference for evidence-based research, exploring the mechanisms underlying the effect of an intervention including causal pathways through intermediate variables or mechanisms of peer influence and spillover between connected units. Her research explores modeling, inferential, and other methodological issues that often arise in applied problems with complex clustered and network data, and standard statistical theory and methods are no longer adequate to support the goals of the analysis. Laura is eager to apply advanced statistical methodology to provide evidence on effective strategies to improve the health and wellbeing of vulnerable populations. She is particularly interested in exploring behavioral interventions that, relying on theories of behavioral economics and social phycology, exploit social interactions and peer influence among individuals. She is involved in many program evaluations and research studies in low- and middle-income countries on malaria, HIV and other STDs, maternal and child health, nutrition, cognitive development, health insurance and microcredit. Dr. Forastiere received her Ph.D. in statistics from the University of Florence (Italy) and postdoc training in statistics and biostatistics at Harvard University. Prior to joining the Department of Biostatistics at Yale School of Public Health, she was a Postdoctoral Associate in the Yale Institute for Network Science.

Gregg Gonsalves is an expert in policy modeling on infectious disease and substance use, as well as the intersection of public policy and health equity. His research focuses on the use of quantitative models for improving the response to epidemic diseases. For more than 30 years, he worked on HIV/AIDS and other global health issues with several organizations, including the AIDS Coalition to Unleash Power, the Treatment Action Group, Gay Men’s Health Crisis, and the AIDS and Rights Alliance for Southern Africa. He is a 2011 graduate of Yale College and received his PhD from Yale Graduate School of Arts and Sciences/School of Public Health in 2017. He is currently the public health correspondent for The Nation. He is a 2018 MacArthur Fellow.

Nathan Grubaugh joined the faculty at Yale School of Public Health in 2018. Before going to graduate school, he spent ~7 years working in the biotech industry developing early phase vaccine candidates. He earned his MS in biotechnology from Johns Hopkins University (2011) while conducting research at the NIH and the US Army Research Institute of Infectious Diseases (focus on mosquito-borne virus surveillance). Dr. Grubaugh earned his PhD in microbiology from Colorado State University in 2016 (focus on West Nile virus evolution), and went on to be a postdoctoral fellow at The Scripps Research Institute to study the 2015-2017 Zika virus epidemic. Now at Yale, the Grubaugh Lab uses genomics and phylogenetics to uncover the epidemiological, ecological, and evolutionary determinants of virus outbreaks. They primarily focus on mosquito- and tick-borne viruses, like dengue, West Nile, and Powassan, that are increasingly spreading into new areas and have high outbreak potential. The Grubaugh Lab is diverse and multidisciplinary, including expertise in molecular biology, phylogenetics, statistics, and mathematical modeling. His lab was critical during the COVID-19 response, from designing and evaluating diagnostics (such as SalivaDirect) to establishing the Yale SARS-CoV-2 Genomic Surveillance Initiative to track emerging variants. Expanding on this work, the lab is an academic partner for the Pathogen Genomics Centers of Excellence to foster and improve innovation and technical capacity in pathogen genomics, molecular epidemiology, and bioinformatics to better prevent, control, and respond to microbial threats of public health importance. Read more about their team and work at grubaughlab.com.

Professor Manshadi’s research interests include real-time decision-making and dynamic optimization under uncertainty with various applications, such as online markets, health-care operations, and maritime port logistics, as well as matching markets and social networks.

Edward H. Kaplan obtained his BA from McGill University with First Class Honors in Economic and Urban Geography, and proceeded to graduate study at the Massachusetts Institute of Technology where he completed three masters’ degrees (in Operations Research, City Planning, and Mathematics) in addition to his doctorate in Urban Studies. He currently serves as the William N. and Marie A. Beach Professor of Management Sciences at the Yale School of Management, Professor of Public Health at the Yale School of Medicine, and Professor of Engineering in the Yale School of Engineering and Applied Sciences. An elected member of both the National Academy of Engineering (2003) and the Institute of Medicine (2004), Kaplan is an expert in operations research, mathematical modeling and statistics who studies problems in public policy and management. His recent research has focused on counterterror topics such as the tactical prevention of suicide bombings, bioterror preparedness, and response logistics in the event of a smallpox or anthrax attack. His work on smallpox was awarded the 2003 Koopman Prize of the Institute for Operations Research and the Management Sciences (INFORMS) Military Applications Society, while his models evaluating suicide-bomber-detector schemes received the same award in 2005. Kaplan serves on the National Academy of Sciences panel on basic research to improve intelligence analysis, and co-directs the Daniel Rose Technion-Yale Initiative in Homeland Security and Counter Terror Operations Research. Kaplan has also conducted award-winning research that evaluates the effectiveness of HIV prevention programs while developing new mathematical models for the study of HIV transmission, prevention, and resource allocation. His empirical and modeling research demonstrating the effectiveness of New Haven’s needle exchange program remains among the most creative and important examples of HIV prevention program evaluation to date. Honors for his HIV-related research include induction into the Omega Rho operations research honor society in 2000, the 2002 INFORMS President’s Award recognizing work that advances the welfare of society, the 1997 Ira Hiscock Award of the Connecticut Public Health Association, the 1994 Lanchester Prize for the best publications in the operations research literature, the 1992 Franz Edelman Award for management science achievement, the 1991 State of Connecticut Health Department’s AIDS Leadership Award, the 2009 Charles C. Shepard Science Award from the Centers for Disease Control, and the INFORMS Philip Morse Lectureship for 2010-11. Kaplan served twice as the Lady Davis Visiting Professor at the Hebrew University of Jerusalem—in the School of Public Health and Community Medicine in 1994, and in the Department of Statistics in 1997 -- and is also an elected member of the Board of Governors of the Technion-Israel Institute of Technology. For all of his contributions to the operations research profession, Kaplan was designated an INFORMS Fellow in November 2005.

C. Brandon Ogbunu is an Assistant Professor in the Department of Ecology and Evolutionary Biology at Yale University. He is a computational biologist whose research investigates complex problems in epidemiology, evolutionary & population genetics, and evolution. His work utilizes a range of methods, from experimental evolution, to biochemistry, applied mathematics, and evolutionary computation.

Professor Pinker’s research in healthcare looks at questions related to patient flow and capacity management within both in-patient and out-patient settings. In the out-patient setting he has studied the division of labor in primary care practices and advanced access appointment scheduling systems. In the in-patient setting he has studied how bed configurations can impact access to care and how congestion in ICUs impacts patient flow. He is currently involved in several projects investigating the use of the Rothman Index as a predictive tool to inform clinical decision making. Outside of healthcare he has done research on service supply chains, the use of flexible workforces, online auctions and responses to terrorist threats among others. He serves on the editorial boards of several leading journals in his field. Pinker has consulted for the United States Postal Service, the financial services industry and the auto industry. His work has been published in leading journals such as Operations Research, Management Science, Manufacturing and Service Operations Management, IIE Transactions, Production and Operations Management, and the Communications of the Association of Computing Machinery.

Virginia Pitzer, joined the Yale School of Public Health as an assistant professor in 2012. She earned her Sc.D. in Epidemiology from the Harvard School of Public Health in 2007, and was a postdoctoral research fellow at Princeton (Department of Ecology and Evolutionary Biology) and a postdoctoral fellow in the Research and Policy for Infectious Disease Dynamics (RAPIDD) program at the Fogarty International Center of the National Institutes of Health prior to coming to Yale.Pitzer’s work focuses on mathematical modeling of the transmission dynamics of imperfectly immunizing infections and how interventions such as vaccination, improved treatment of cases, and improvements in sanitation affect disease transmission at the population level. Her primary research is in rotavirus, (one of the leading causes of severe diarrhea in children in developed and developing countries) for which two new vaccines have been recently introduced. She is also interested in the spatiotemporal dynamics of respiratory syncytial virus and evaluating control options for typhoid fever. Her paper Demographic Variability, Vaccination, and the Spatiotemporal Dynamics of Rotavirus Epidemics appeared in Science magazine in 2009.

Professor Townsend received his Ph.D. in 2002 in organismic and evolutionary biology from Harvard University, under the advisement of Daniel Hartl. His Ph.D. was entitled "Population genetic variation in genome-wide gene expression: modeling, measurement, and analysis", and constituted the first population genetic analysis of genome-wide gene expression variation. After making use of the model budding yeast S. cerevisiae for his Ph.D. research, Dr. Townsend accepted an appointment as a Miller Fellow at the University of California-Berkeley in the Department of Plant and Microbial Biology, where he worked to develop molecular tools, techniques, and analysis methodologies for functional genomics studies with the filamentous fungal model species Neurospora crassa, co-advised by Berkeley fungal evolutionary biologist John Taylor and molecular mycologist Louise Glass. In 2004, he accepted his first appointment as an Assistant Professor in the Department of Molecular and Cell Biology at the University of Connecticut. In 2006 he was appointed as an Assistant Professor the Department of Ecology and Evolutionary Biology at Yale University. In 2013 he began to work on statistical approaches to fit mathematical models of disease spread and emergence, and to work on the somatic evolution of cancer, and was appointed as an Associate Professor of Biostatistics and Ecology & Evolutionary Biology. In 2017 he was named Elihu Associate Professor of Biostatistics and Ecology & Evolutionary Biology, and in 2018 he was appointed Elihu Professor of Biostatistics and Ecology & Evolutionary Biology. In 2019 he was appointed a member of the Connecticut Academy of Science and Engineering, in recognition of the development of innovative approaches to population biology, including the evolution of antimicrobial resistance, disease evolution and transmission, and evolution of tumorigenesis; and research that has enabled curtailment of pathogen evolution, outbreak mitigation, and informed therapeutic approaches to cancer metastasis and evolution of therapeutic resistance in cancer. In 2021 he was selected as the Co-Chair-Elect of the Cancer Evolution Working Group of the American Association for Cancer Research. In 2022 he was appointed Co-Director of the Genetics, Genomics, and Epigenetics Program of the Yale Cancer Center. In 2023 he was elevated to Co-Chair of the Cancer Evolution Working Group of the American Association for Cancer Research.

Dr. Wang is an Associate Professor at the Yale School of Public Health, faculty member of Cancer Outcomes, Public Policy and Effectiveness Research (COPPER) Center, and faculty member of Public Health Modeling Concentration, Yale School of Public Health. His primary interests focus on outcomes research and decision science. He is interested in combining systematic literature reviews, secondary data analyses, and simulation modeling to examine issues that are critical to clinicians and policy makers’ decision making. He has been working on several breast cancer projects, including an evaluation of preoperative breast MRI, development of an individualized decision aid to help radiotherapy decision-making, and assessment of sentinel lymph node biopsy for patients with ductal carcinoma in situ. He is also evaluating end-of-life care quality. He has served as the primary investigator or co-investigator in several projects (funded by Yale Cancer Center, AHRQ, NCI, ACS, and PCORI).

Joshua Warren is an associate professor in the Department of Biostatistics at the Yale School of Public Health. He received his Ph.D. in statistics from North Carolina State University in 2011. Dr. Warren’s research focuses on statistical methods in public health with an emphasis on environmental health problems. Much of his work involves introducing spatial and spatiotemporal models in the Bayesian setting to learn more about associations between environmental exposures, such as air pollution, and various health outcomes including preterm birth, low birth weight, and congenital anomalies. He also has interest in developing and applying spatiotemporal models in collaborative settings such as epidemiology, geography, nutrition, and glaucoma research. His theoretical and methodological interests include multiple topics in spatial/spatiotemporal modeling and Bayesian nonparameterics.

Dan Weinberger is an Associate Professor in Epidemiology of Microbial Diseases at Yale School of Public Health. His research uses a combination of quantitative analysis, laboratory experiments and field work to understand the epidemiology and biology of respiratory infections. Recent work has focused on developing novel analytical methods for the evaluation of vaccines using time series and spatial data. He collaborates widely with public health agencies and academic organizations around the world on these issues. He earned his PhD in biological sciences from Harvard School of Public Health, with a focus on Infectious Disease Epidemiology, and completed a postdoctoral fellowship in the Division of International Epidemiology and Population Studies in the Fogarty International Center at the NIH.Research: The research in the Weinberger Lab is at the intersection of microbiology and epidemiology. We focus on understanding the biological and epidemiological drivers of respiratory infections, including pneumococcus, RSV, influenza, and Legionella. Major research areas include understanding the biological drivers of the emergence of rare pneumococcal serotypes following vaccine introduction, developing novel statistical approaches to evaluate vaccine impact from observational data, evaluating the importance of interactions among respiratory pathogens, and understanding environmental drivers of Legionellosis. We employ a variety of tools including experimental and quantitative approaches. Our work is funded by grants from the NIH/NIAID, the Bill and Melinda Gates Foundation, and the Emerging Infections Program (a collaboration between the CDC, the Connecticut Department of Public Health, and Yale). You can learn more about our research here. Teaching: I teach the Public Health Surveillance course at YSPH. This class uses a mix of lectures, cases studies, and hands on data analysis exercises. Students learn to perform common surveillance analyses including aberration detection (e.g., CUSUM), time series analysis, and spatial cluster detection (SATSCAN). Students learn to do these analyses in either SAS or R.

Dr. Yaesoubi’s research focuses on medial decision making and model-based evaluation of health policies. His work incorporates mathematical and computer simulation models, machine learning methods, and optimization techniques to guide resource allocation and decision making in public health and health delivery systems. He has applied these methods in estimating the impact of different strategies to reduce the prevalence of alcohol-exposed pregnancies, conducting cost-effectiveness analyses of colorectal cancer screening strategies, estimating societal willingness-to-pay for health, and characterizing performance-based payment systems for preventive care systems. His current work mainly focuses on optimizing public health responses to control the spread of infectious diseases including COVID-19, influenza, meningitis, and drug-resistant tuberculosis and gonorrhea. He is also interested in theoretical and methodological issues in medical decision-making and health care resource allocation.