Welcome! Our group conducts research in the field of public health policy and planning. We specifically address questions about how public health programs can better prevent chronic diseases that disproportionately affect low-income communities and are commonly treated in primary care clinics. These questions include: how can changes to nutrition programs reduce population-level disparities in obesity and type 2 diabetes? Which fiscal and regulatory policies affecting food, tobacco and alcohol consumption are most effective in reducing cardiovascular disease rates? Which social and economic policies reduce the risk of disease and disability among low-income families? How can primary healthcare systems better identify and treat chronic conditions before they result in preventable complications? Many of these questions span multiple populations and cross international borders.
Our unique contribution to this field is to address these questions by developing and applying novel mathematical modeling and statistical techniques. We have developed approaches to integrate extremely large-scale data describing social, demographic, economic, and policy changes with health outcomes from diverse populations across the globe. We then analyze these data using novel modeling and statistical strategies that address persistent challenges such as complex time-varying influences on health risks and outcomes; feedback loops between disease risk factors, treatments, and outcomes; and analytical dilemmas unique to extremely large-scale mathematical models. We use models that integrate insights from econometrics, computer science, and operations research to address questions that traditional medical and public health studies cannot directly answer, such as how to optimize the delivery of health programs under limited budgets and rapidly-changing epidemiological conditions. At a theoretical level, this work has helped develop an understanding of 'resilience'--or how health systems can minimize morbidity and mortality despite 'shocks' to the community such as dramatic changes in social conditions (e.g., urbanization, mass migration), economies (e.g., financial crises, rising inequality), and risk exposures (e.g., the industrialization of food systems). Read more...
New post-doctoral fellowship opportunity
An NIH-funded post-doctoral position in epidemiology and biostatistics is available at Stanford University, with an anticipated start date as early as October 2015. The position will be supervised by Dr. Sanjay Basu, with additional mentorship from Drs. David Rehkopf and Mike Baiocchi. The position will entail the following responsibilities: (1) learning and applying novel statistical methods to understand the influence of key 'safety net' programs (such as food security, housing assistance, primary care, and poverty relief initiatives) on long-term cardiovascular disease risk factors (such as hypertension and type 2 diabetes) and associated healthcare utilization and cost disparities; (2) authorship of manuscripts to be submitted for peer-reviewed publication in the epidemiological literature based on analysis of longitudinal cohort data to identify relationships between safety net programs and health and healthcare cost disparities; (3) assistance in enhancing public use datasets that catalogue geographic variations in safety net programs and policies for study by the larger research community; and (4) assistance in the integration of results into microsimulation policy models and their deployment as open-source analytic packages (in R or Julia). Appropriate candidates should have completed a PhD by October 2015 related to epidemiology, statistics, economics, or sociology; expertise in matching methods, instrumental variables analysis and/or experience with common longitudinal cohort/panel datasets (NLSY, PSID, MEPS) is a plus. Salary and benefits, including conference travel and equipment funds, are highly competitive and in excess of the NIH salary scale adjusted for cost of living. The position is available for two years, with the possibility of renewal for a third year. Post-doctoral scholars will receive dedicated mentorship and guidance for transition to an independent academic research position, and will have the opportunity to participate in seminar series, lectures and career development programs. Interested candidates should send a single PDF file including a cover letter, CV including contact information for references, a writing sample (e.g., peer-reviewed publication), and a sample of code (in R, Stata, Julia, MATLAB, C or Python) to Tamica Garner, firstname.lastname@example.org, with subject line “Basu postdoc app”.