3 citations · 6 across the 15 of their papers we have counts for
17 papers
Evaluating the effects of policy interventions subject to early adoption: A case study of prescription drug monitoring programs and opioid dispensing
Sarika Aggarwal, Brent A. Coull, Nima Hejazi +1
Policies that require organizations to use new systems, such as prescription drug monitoring programs (PDMPs), are often implemented in phases, with an initial period of voluntary…
A varying-coefficient model for characterizing duration-driven heterogeneity in flood-related health impacts
Sarika Aggarwal, Phillip B. Nicol, Brent A. Coull +1
Previous work revealed associations between flood exposure and adverse health outcomes during and in the aftermath of flood events. Floods are highly heterogeneous events, largely…
Fair Policy Learning under Bipartite Network Interference: Learning Fair and Cost-Effective Environmental Policies
Raphael C. Kim, Rachel C. Nethery, Kevin L. Chen +1
Numerous studies have shown the harmful effects of airborne pollutants on human health. Vulnerable groups and communities often bear a disproportionately larger health burden due t…
Practical considerations for Gaussian Process modeling for causal inference quasi-experimental studies with panel data
Sofia L. Vega, Rachel C. Nethery
Estimating causal effects in quasi-experiments with spatio-temporal panel data often requires adjusting for unmeasured confounding that varies across space and time. Gaussian Proce…
Towards Optimal Environmental Policies: Policy Learning under Arbitrary Bipartite Network Interference
Raphael C. Kim, Falco J. Bargagli-Stoffi, Kevin L. Chen +1
The substantial effect of air pollution on cardiovascular disease and mortality burdens is well-established. Emissions-reducing interventions on coal-fired power plants -- a major…
Difference-in-Differences under Bipartite Network Interference: A Framework for Quasi-Experimental Assessment of the Effects of Environmental Policies on Health
Kevin L. Chen, Falco J. Bargagli-Stoffi, Raphael C. Kim +2
Pollution from coal-fired power plants has been linked to substantial health and mortality burdens in the US. In recent decades, federal regulatory policies have spurred efforts to…
A Bayesian Spatial Berkson error approach to estimate small area opioid mortality rates accounting for population-at-risk uncertainty
Emily N Peterson, Rachel C. Nethery, Jarvis T. Chen +4
Monitoring small-area geographical population trends in opioid mortality has large scale implications to informing preventative resource allocation. A common approach to obtain sma…
Optimizing Heat Alert Issuance with Reinforcement Learning
Ellen M. Considine, Rachel C. Nethery, Gregory A. Wellenius +2
A key strategy in societal adaptation to climate change is using alert systems to prompt preventative action and reduce the adverse health impacts of extreme heat events. This pape…
Severe flooding and cause-specific hospitalization in the United States
Sarika Aggarwal, Jie K. Hu, Jonathan A. Sullivan +2
Flooding is one of the most disruptive and costliest climate-related disasters and presents an escalating threat to population health due to climate change and urbanization pattern…
Causal exposure-response curve estimation with surrogate confounders: a study of air pollution and children's health in Medicaid claims data
Jenny J. Lee, Xiao Wu, Francesca Dominici +1
In this paper, we undertake a case study to estimate a causal exposure-response function (ERF) for long-term exposure to fine particulate matter (PM) and respiratory hospit…
Spatio-temporal quasi-experimental methods for rare disease outcomes: The impact of reformulated gasoline on childhood hematologic cancer
Sofia L. Vega, Rachel C. Nethery
Although some pollutants emitted in vehicle exhaust, such as benzene, are known to cause leukemia in adults with high exposure levels, less is known about the relationship between…
Environmental Justice Implications of Power Plant Emissions Control Policies: Heterogeneous Causal Effect Estimation under Bipartite Network Interference
Kevin L. Chen, Falco J. Bargagli Stoffi, Raphael C. Kim +1
Emissions generators, such as coal-fired power plants, are key contributors to air pollution and thus environmental policies to reduce their emissions have been proposed. Furthermo…
Impacts of Census Differential Privacy for Small-Area Disease Mapping to Monitor Health Inequities
Yanran Li, Brent A. Coull, Nancy Krieger +4
The US Census Bureau will implement a new privacy-preserving disclosure avoidance system (DAS), which includes application of differential privacy, on the public-release 2020 censu…
A Bayesian hierarchical small-area population model accounting for data source specific methodologies from American Community Survey, Population Estimates Program, and Decennial Census data
Emily N Peterson, Rachel C Nethery, Tullia Padellini +6
Small area estimates of population are necessary for many epidemiological studies, yet their quality and accuracy are often not assessed. In the United States, small area estimates…
Integrated causal-predictive machine learning models for tropical cyclone epidemiology
Rachel C. Nethery, Nina Katz-Christy, Marianthi-Anna Kioumourtzoglou +3
Strategic preparedness has been shown to reduce the adverse health impacts of hurricanes and tropical storms, referred to collectively as tropical cyclones (TCs), but its protectiv…
Causal inference and machine learning approaches for evaluation of the health impacts of large-scale air quality regulations
Rachel C. Nethery, Fabrizia Mealli, Jason D. Sacks +1
We develop a causal inference approach to estimate the number of adverse health events prevented by large-scale air quality regulations via changes in exposure to multiple pollutan…
Estimating Population Average Causal Effects in the Presence of Non-Overlap: The Effect of Natural Gas Compressor Station Exposure on Cancer Mortality
Rachel C. Nethery, Fabrizia Mealli, Francesca Dominici
Most causal inference studies rely on the assumption of overlap to estimate population or sample average causal effects. When data exhibit non-overlap, estimation of these estimand…