ABSTRACT
This manuscript describes a new method that enables direct analysis of viral particles in unprocessed samples.Using an electrochemical readout method that requires no external reagents, we detect the SARS-CoV-2 virus in the saliva of infected patients.The approach relies on a molecular sensor tethered to the surface of a gold electrode that contains an antibody, specific to the targetof interest, which here is the SARS-CoV-2 S1 spike protein that is displayed on the viral capsule. The antibody is attached to the electrode using a negatively charged linker that is composed of DNA. When a positive potential is applied to the electrode, the sensor complex is attracted to the electrode surface. The kinetics of transport is measured using chronoamperometry and readout is possible based on the absense or precense of virus and its effect on the complex movevment on electrode surface.
ABSTRACT
This manuscript describes a new method that enables direct analysis of viral particles in unprocessed samples.Using an electrochemical readout method that requires no external reagents, we detect the SARS-CoV-2 virus in the saliva of infected patients.The approach relies on a molecular sensor tethered to the surface of a gold electrode that contains an antibody, specific to the targetof interest, which here is the SARS-CoV-2 S1 spike protein that is displayed on the viral capsule. The antibody is attached to the electrode using a negatively charged linker that is composed of DNA. When a positive potential is applied to the electrode, the sensor complex is attracted to the electrode surface. The kinetics of transport is measured using chronoamperometry and readout is possible based on the absense or precense of virus and its effect on the complex movevment on electrode surface.
Subject(s)
InfectionsABSTRACT
We enrolled 53 consecutive in-patients with COVID-19 at six hospitals in Toronto, Canada, and tested one nasopharyngeal swab/saliva sample pair from each patient for SARS-CoV-2. Overall, sensitivity was 89% for nasopharyngeal swabs and 77% for saliva (p=NS); difference in sensitivity was greatest for sample pairs collected later in illness.
Subject(s)
COVID-19 , Nephrotic SyndromeABSTRACT
Background: A hospital-level pandemic response involves anticipating local surge in healthcare needs. Methods: We developed a mechanistic transmission model to simulate a range of scenarios of COVID-19 spread in the Greater Toronto Area. We estimated healthcare needs against 2019 daily admissions using healthcare administrative data, and applied outputs to hospital-specific data on catchment, capacity, and baseline non-COVID admissions to estimate potential surge by day 90 at two hospitals (St. Michaels Hospital [SMH] and St. Josephs Health Centre [SJHC]). We examined fast/large, default, and slow/small epidemics, wherein the default scenario (R0 2.4) resembled the early trajectory in the GTA. Results: Without further interventions, even a slow/small epidemic exceeded the citys daily ICU capacity for patients without COVID-19. In a pessimistic default scenario, for SMH and SJHC to remain below their non-ICU bed capacity, they would need to reduce non-COVID inpatient care by 70% and 58% respectively. SMH would need to create 86 new ICU beds, while SJHC would need to reduce its ICU beds for non-COVID care by 72%. Uncertainty in local epidemiological features was more influential than uncertainty in clinical severity. If physical distancing reduces contacts by 20%, maximizing the diagnostic capacity or syndromic diagnoses at the community-level could avoid a surge at each hospital. Interpretation: As distribution of the citys surge varies across hospitals over time, efforts are needed to plan and redistribute ICU care to where demand is expected. Hospital-level surge is based on community-level transmission, with community-level strategies key to mitigating each hospitals surge. Keywords: COVID-19, pandemic preparedness, mathematical model, transmission model