Racial and Ethnic (In)equity in Development of Power Through Place-Based Initiatives.

: Place-based initiatives (PBIs) invest in a geographic area and often build community power to improve well-being. However, there can be differences in results for different groups within a community. : In six communities, we measured differences in "power to" by race/ethnicity at two points for the first phase of the PBI Healthy Places North Carolina (HPNC) using five indicators: (1) representation in network of actors collaborating to improve health, (2) leadership attributes, (3) perceived change in attributes due to HPNC, (4) network centrality, and (5) perceived change in network ties due to HPNC.

SEED: A novel web-based data visualization platform to visualize, communicate, and explore social, environmental, and equity drivers of health.

Multisector stakeholders, including, community-based organizations, health systems, researchers, policymakers, and commerce, increasingly seek to address health inequities that persist due to structural racism. They require accessible tools to visualize and quantify the prevalence of social drivers of health (SDOH) and correlate them with health to facilitate dialog and action. We developed and deployed a web-based data visualization platform to make health and SDOH data available to the community.

Routine Hearing Screening for Older Adults in Primary Care: Insights of Patients and Clinic Personnel.

Background And Objectives: Hearing loss frequently goes undiagnosed and untreated, with serious sequelae. Hearing screening facilitates diagnosis and treatment but is not routinely conducted in primary care. This study addresses the attitudes and insights of patients and primary care clinic personnel relative to the routinization of hearing screening in primary care for older adults.

Poincaré and SimBio: a versatile and extensible Python ecosystem for modeling systems.

Motivation: Chemical reaction networks (CRNs) play a pivotal role in diverse fields such as systems biology, biochemistry, chemical engineering, and epidemiology. High-level definitions of CRNs enables to use various simulation approaches, including deterministic and stochastic methods, from the same model. However, existing Python tools for simulation of CRN typically wrap external C/C++ libraries for model definition, translation into equations and/or numerically solving them, limiting their extensibility and integration with the broader Python ecosystem.