Efficacy of a student-led community contact tracing program partnered with an academic medical center during the coronavirus disease 2019 pandemic.

PURPOSE: Contact tracing has proven successful at controlling coronavirus 2019 (COVID-19) globally, and the Center for Health Security has recommended that the United States add 100,000 contact tracers to the current workforce. METHODS: To address gaps in local contact tracing, health professional students partnered with their academic institution to conduct contact tracing for all COVID-19 cases diagnosed onsite, which included identifying and reaching their contacts, educating participants, and providing social resources to support effective quarantine and isolation. RESULTS: From March 24 to May 28, 536 laboratory-confirmed COVID-19 cases were contacted and reported an average of 2.6 contacts. Contacts were informed of their exposure, asked to quarantine, and monitored for the onset of symptoms. Callers reached 94% of cases and 84% of contacts. Seventy-four percent of cases reported at least one contact. Household members had higher rates of reporting symptoms (odds ratio, 1.65; 95% confidence interval, 1.19-2.28). The average test turnaround time decreased from 21.8 days for the first patients of this program to 2.3 days on the eleventh week. CONCLUSIONS: This provides evidence for the untapped potential of community contact tracing to respond to regional needs, confront barriers to effective quarantine, and mitigate the spread of COVID-19.

Fluid-structure interaction analysis of cerebrospinal fluid with a comprehensive head model subject to a rapid acceleration and deceleration.

PRIMARY OBJECTIVE: Closed brain injuries are a common danger in contact sports and motorized vehicular collisions. Mild closed brain injuries, such as concussions, are not easily visualized by computed imaging or scans. Having a comprehensive head/brain model and using fluid-structure interaction (FSI) simulations enable us to see the exact movement of the cerebrospinal fluid (CSF) under such conditions and to identify the areas of brain most affected. RESEARCH DESIGN: The presented work is based on the first FSI model capable of simulating the interaction between the CSF flow and brain. METHODS AND PROCEDURES: FSI analysis combining smoothed-particle hydrodynamics and high-order finite-element method is used. MAIN OUTCOMES AND RESULTS: The interaction between the CSF and brain under rapid acceleration and deceleration is demonstrated. The cushioning effect of the fluid and its effect on brain are shown. CONCLUSIONS: The capability to locate areas (down to the exact gyri and sulci) of the brain the most affected under given loading conditions, and therefore assess the possible damage to the brain and consequently predict the symptoms, is shown.