Effectiveness of SplashGuard Caregiver prototype in reducing the risk of aerosol transmission in intensive care unit rooms of SARS-CoV-2 patients: a prospective and simulation study

ABSTRACT: Background The contagiousness of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is known to be linked to the emission of bioaerosols. Thus, aerosol-generating procedures (AGPs) could increase the risk of infection among healthcare workers (HCWs). Aim To investigate the impact of an aerosol protection box, the SplashGuard Caregiver (SGGC) with suction system, by direct analysis of the presence of viral particles after an AGP, and by using the computational fluid dynamics (CFD) simulation method. Methods This prospective observational study investigated HCWs caring for patients with SARS-CoV-2 admitted to an intensive care unit (ICU). Rooms were categorized as: SGCG present and SGCG absent. Virus detection was performed through direct analysis, and using a CFD model to simulate the movement dynamics of airborne particles produced by a patient's respiratory activities. Findings Of the 67 analyses performed, three samples tested positive on quantitative polymerase chain reaction: one of 33 analyses in the SCCG group (3%) and two of 34 analyses in the non-SGCG group (5.9%). CFD simulations showed that: (1) reduction of the gaps of an SGCG could decrease the number of emitted particles remaining airborne within the room by up to 70%; and (2) positioning HCWs facing the opposite direction to the main air flow would reduce their exposure. Conclusions This study documented the presence of SARS-CoV-2 among HCWs in a negative pressure ICU room of an infected patient with or without the use of an SGCG. The simulation will help to improve the design of the SGCG and the positioning of HCWs in the room

Long-term response of rainfed sorghum to diverse growing environments and optimal sowing window at Coimbatore

Rainfed sorghum production is profoundly vulnerable to climate variability. Sowing the crop at an appropriate time could be one of the most crucial climate-resilient options to improve the yield. The well-calibrated and validated CERES-Sorghum model was employed to study the rainfed sorghum response to varied environments over the long term (1983–2021) and to determine the optimum sowing window at Coimbatore, Tamil Nadu. The CERES-Sorghum model was used for automatic-planting with a different minimum threshold of 50,60,70 and 80 percent soil water content at 15 cm soil depth under various sowing windows from 1stSeptember to 13th October at a 7-day interval. The model results of automatic planting event indicated the best performance of 1st September sowing window at 50 percent soil water content over 39 years under semi-arid environment. The temperature rise of 1˚C exhibited no significant influence on sorghum grain yields at all sowing windows and a slight reduction in yield was observed at an elevated 2˚C temperature. A further rise in temperature reduced the yield drastically on September month sowings. Across the sowing window, first week sowing window (1st to 7th September) yield was higher under current climatic conditions. The yield of 1st September sowing window remained higher in the elevated temperature conditions as well as in both deficit and excess rainfall conditions than other sowings. In current and future climatic conditions, 1st September sowing window would be the best sowing time to mitigate climate risk in rainfed sorghum