Duke says testing program prevented campus COVID-19 outbreaks
Duke College’s aggressive pooled surveillance COVID-19 testing program enabled large-scale testing, efficiently lowered transmission, and prevented main outbreaks seen on different faculty campuses, in line with a Morbidity and Mortality Weekly Report (MMWR) research yesterday.
The Duke marketing campaign relied on a mixture of methods, together with a 14-day pre-arrival self-quarantine for all enrolled college students and a code-of-conduct pledge to put on masks, comply with bodily distancing pointers, and bear common COVID-19 testing. Day by day symptom monitoring—carried out through a customized smartphone app—was accompanied by contact tracing and quarantine. On-campus college students had been examined twice every week with self-swab kits collected at strategically situated websites on campus. Off-campus college students had been examined as soon as every week.
The surveillance testing used pooled samples to preserve sources, and the researchers reported constructive outcomes with testing samples in batches of 5 and re-testing particular person samples inside batches that confirmed a constructive outcome. The batch methodology allowed the Duke Human Vaccine Institute to course of 80,000 samples from Aug 2 to Oct 11, together with 68,913 specimens from 10,265 graduate and undergraduate college students—excluding 781 student-athletes who participated in a separate surveillance program.
The Duke surveillance strategy resulted in a decrease common per-capita an infection prevalence amongst college students (0.08%) than within the surrounding group (Durham County, 0.1%), and no massive campus outbreaks. There have been 84 COVID-19 instances amongst college students, with 51% of the instances occurring amongst asymptomatic individuals, highlighting the significance of complete versus symptom-based testing.
“By late summer time there have been nonetheless issues we did not totally perceive about SARS-CoV-2 transmission, so there was some uncertainty going into the autumn semester,” mentioned Steve Haase, PhD, of Duke College College of Medication in a Duke Well being information launch yesterday. “Over the course of the semester we have realized many issues, together with that it is attainable to restrict the unfold of the virus and create a safer atmosphere for our college students to have that invaluable on-campus studying expertise.”
Nov 17 MMWR research
Nov 17 Duke Well being information launch
Smartwatch information may assist establish pre-symptomatic COVID-19
A research in Nature Biomedical Engineering right now exhibits that smartwatches and different wearable gadgets may detect pre-symptomatic COVID-19 an infection and permit for early-stage interventions that cut back transmission.
Amongst contaminated smartwatch customers, 81% confirmed alterations of their coronary heart price, variety of each day steps, or time asleep. Modifications earlier than symptom onset recognized 63% of the COVID-19–constructive people, displaying that client wearable machine information can acknowledge pre-symptomatic an infection.
Stanford College researchers analyzed information from 4,642 smartwatch customers, specializing in 32 COVID-19–constructive individuals with Fitbit information that captured resting coronary heart price (RHR), steps per day, and sleep length.
Of people with a symptom-onset date or a analysis date, 88% (22 out of 25) and 100% (25 out of 25) confirmed a 7-beats-per-minute median elevation in RHR relative to baseline each upfront of and on the time of symptom onset or analysis. Elevated indicators had been detected a number of days forward of symptom onset and analysis—Four days and seven days, respectively—highlighting the potential for early identification of an infection and mitigation of group unfold.
Steps per day considerably decreased and sleep length elevated after the onset of elevated coronary heart price indicators, however no affiliation was discovered between the magnitude of the elevated coronary heart price sign and particular signs, sickness size, or temperature.
The researchers additionally developed a web based detection methodology utilizing smartwatch information to discover the potential detection of early stage COVID-19 sickness upfront of signs, discovering that they had been in a position to detect 63% of identified COVID-19 infections.
“Our findings recommend that exercise monitoring and well being monitoring through client wearable gadgets may be used for the large-scale, real-time detection of respiratory infections, typically pre-symptomatically,” the authors concluded.
Nov 18 Nat Biomed Eng research