Risk of transmission of COVID-19 from healthcare workers returning to work after a 5-day isolation, and kinetics of shedding of viable SARS-CoV-2 variant B.1.1.529 (Omicron)

Background: There have been limited data on the risk of onward transmission from individuals with Omicron variant infections who return to work after a 5-day isolation. Aim: To evaluate the risk of transmission from healthcare workers (HCWs) with Omicron variant who returned to work after a 5-day isolation and the viable-virus shedding kinetics. Methods: This investigation was performed in a tertiary care hospital, Seoul, South Korea. In a secondary transmission study, we retrospectively reviewed the data of HCWs confirmed as COVID-19 from March 14th to April 3rd, 2022 in units with five or more COVID-19-infected HCWs per week. In the viral shedding kinetics study, HCWs with Omicron variant infection who agreed with daily saliva sampling were enrolled between February and March, 2022. Findings: Of the 248 HCWs who were diagnosed with COVID-19 within 5 days of the return of an infected HCW, 18 (7%) had contact with the returned HCW within 1-5 days after their return. Of these, nine (4%) had an epidemiologic link other than with the returning HCW, and nine (4%) had contact with the returning HCW, without any other epidemiologic link. In the study of the kinetics of virus shedding (N = 32), the median time from symptom onset to negative conversion of viable virus was four days (95% confidence interval: 3-5). Conclusion: Our data suggest that the residual risk of virus transmission after 5 days of isolation following diagnosis or symptom onset is low.

Data-informed building energy management (DiBEM) towards ultra-low energy buildings

To support building operations in reaching ultra-low energy targets, this paper proposes a data-informed building energy management (DiBEM) framework to improve energy efficiency systematically and continuously at the operation stage. Specifically, it has two key features including data-informed energy-saving potential identification and data-driven model-based energy savings evaluation. The paper demonstrates the proposed DiBEM with a detailed case study of an office and living laboratory building located in Cambridge, Massachusetts called HouseZero. It focuses on revealing the performance of the energy-efficient interventions from two-years' building performance monitoring data, as well as evaluating energy savings from the interventions based on the data-driven approach. With Year 1 as baseline, several interventions are proposed for Year 2 including improvements to controls and operation settings, encouragement of occupants' behavior for energy savings, and hardware retrofitting. These were deployed to heating/cooling, domestic hot water, lighting, plug and other loads, and photovoltaic (PV) systems. To quantify the impacts of different interventions on energy end uses, several data-driven models are developed. These models utilize linear regression, condition model, and machine learning techniques. Consequently, the heating/cooling energy consumption that was already ultra-low in Year 1 (12.8 kWh/m2) is further reduced to 9.7 kWh/m2 in Year 2, while the indoor thermal environment is well maintained. The domestic hot water energy is reduced from 2.3 kWh/m2 to 1.2 kWh/m2. The lighting energy is only increased from 0.3 kWh/m2 in pandemic operations without occupancy in Year 1 to 0.8 kWh/m2 in partial normal operations in Year 2, while the indoor illuminance level meets occupants' requirements. Combined with other relatively constant loads and the reduction of plug and other loads due to COVID building operation restrictions, the total energy use intensity is thereby reduced from 54.1 kWh/m2 to 42.8 kWh/m2, where 5.4 kWh/m2 of energy reduction for Year 2 is estimated to be contributed by the energy-efficient interventions. PV generation is 36.1 kWh/m2, with an increase of 1.4 kWh/m2 from a new inverter. In summary, this paper demonstrates the use of DiBEM through a detailed case study and long-term monitoring data as evidence to achieve ultra-low energy operations. © 2022 Elsevier B.V.

Collaboration between a tertiary pain centre and community teams during the pandemic.

People with chronic pain faced potential treatment disruption during the COVID-19 pandemic in Singapore, as the focus of healthcare shifted. A model of rapid integration of a pain centre with community healthcare teams was implemented to care for vulnerable older patients with chronic pain and multiple comorbidities. Telemedicine and home visits by community nurses were used, with risk-mitigation measures, ensuring comprehensive assessment and treatment compliance. Medications from pain physicians were delivered at home through a hospital pharmacy. A secure national electronic health records system used by all teams ensured seamless access and documentation. Potential emergency department visits, admissions and delayed discharges were thus avoided. Integration of community teams with chronic pain management services can be recommended to ensure pandemic preparedness.

ISEV and ISCT statement on EVs from MSCs and other cells: considerations for potential therapeutic agents to suppress COVID-19

STATEMENT: The International Society for Cellular and Gene Therapies (ISCT) and the International Society for Extracellular Vesicles (ISEV) recognize the potential of extracellular vesicles (EVs, including exosomes) from mesenchymal stromal cells (MSCs) and possibly other cell sources as treatments for COVID-19. Research and trials in this area are encouraged. However, ISEV and ISCT do not currently endorse the use of EVs or exosomes for any purpose in COVID-19, including but not limited to reducing cytokine storm, exerting regenerative effects or delivering drugs, pending the generation of appropriate manufacturing and quality control provisions, pre-clinical safety and efficacy data, rational clinical trial design and proper regulatory oversight.