Derek Ouyang

Stanford University | SU · Department of Geophysics

Exposure to climate hazards is increasing, and the experiences of frontline communities warrant meaningful and urgent attention towards how to mitigate, manage, and adapt to hazards. We report results from a community-engaged pilot (November 2021 – June 2022) of N=30 participants in four frontline communities of the San Francisco Bay Area, Californ...

COVID-19 exposed and exacerbated health disparities, and a core challenge has been how to adapt pandemic response and public health in light of these disproportionate health burdens. Responding to this challenge, the County of Santa Clara Public Health Department designed a model of "high-touch" contact tracing that integrated social services with...

Neighborhood-level screening algorithms are increasingly being deployed to inform policy decisions. We evaluate one such algorithm, CalEnviroScreen - designed to promote environmental justice and used to guide hundreds of millions of dollars in public funding annually - assessing its potential for allocative harm. We observe high sensitivity to sub...

Background Case investigation and contact tracing (CICT) is an important tool for communicable disease control, both to proactively interrupt chains of transmission and to collect information for situational awareness. We run the first randomized trial of COVID-19 CICT to investigate the utility of manual (i.e., call-based) vs. automated (i.e., sur...

On the basis of an extensive academic–public health partnership around COVID-19 response, we illustrate the challenge of science-policy translation by examining one of the most common nonpharmaceutical interventions: capacity limits. We study the implementation of a 20% capacity limit in retail facilities in the California Bay Area. Through a diffe...

Significance Language discordance has been shown to contribute to social disparities in healthcare. Contact tracing is essential to combating COVID-19, but language differences between contact tracers and patients have hindered its efficacy. We demonstrate a general method for leveraging machine learning and administrative data to maximize the impa...

Importance Overcoming social barriers to COVID-19 testing is an important issue, especially given the demographic disparities in case incidence rates and testing. Delivering culturally appropriate testing resources using data-driven approaches in partnership with community-based health workers is promising, but little data are available on the desi...

Increasing coastal flooding threatens urban centers worldwide. Projections of physical damages to structures and their contents can characterize the monetary scale of risk, but they lack relevant socioeconomic context. The impact of coastal flooding on communities hinges not only on the cost, but on the ability of households to pay for the damages....

Anonymized smartphone-based mobility data has been widely adopted in devising and evaluating COVID-19 response strategies such as the targeting of public health resources. Yet little attention has been paid to measurement validity and demographic bias, due in part to the lack of documentation about which users are represented as well as the challen...

As sea level rises, urban traffic networks in low-lying coastal areas face increasing risks of flood disruptions. Closure of flooded roads causes employee absences and delays, creating cascading impacts to communities. We integrate a traffic model with flood maps that represent potential combinations of storm surges, tides, seasonal cycles, interan...

As sea levels rise, urban traffic networks in low-lying coastal areas face an increasing risk offlood disruption and commute delays. We hypothesize that road network connectivity rather than flood exposure governs commute delays. We integrate an existing traffic model with flood maps to identify inundated roads, simulate traffic patterns, and quant...