7 research outputs found
Effective removal of enteric viruses by Moringa oleifera seed extract functionalized cotton filter
Accessible and low-cost point-of-use technologies have significant potential to mitigate risk to public health, particularly in areas with limited resources and in disaster scenarios. Natural cotton fibers functionalized with water-soluble proteins from Moringa oleifera seeds (MO-cotton filter) are a promising technology at lab-scale with demonstrated feasibility for pathogen removal from water. Here, we showed the performance of MO-cotton filters under practically relevant conditions to remove mammalian virus spiked in groundwater. Specifically, MO-cotton filters achieved > 3.2-log10 reduction at a superficial velocity of 0.7 m/h of two mammalian viruses Tulane virus (TV, Caliciviridae, non-enveloped virus) and Transmissible gastroenteritis virus (TGEV, Coronaviridae, enveloped virus), which are representative of a significant portion of waterborne illnesses. We further evaluated the risk of virus particles detached due to shear forces by testing their infectivity and found that the viruses accumulated on the MO-cotton filters pose a minimal risk of contaminating the drinking water source
Dry Heat as a Decontamination Method for N95 Respirator Reuse
A pandemic such as COVID-19 can cause a sudden depletion in the worldwide supply of respirators, forcing healthcare providers to reuse them. In this study, we systematically evaluated dry heat treatment as a viable option for the safe decontamination of N95 respirators (1860, 3M) before its reuse. We found that the dry heat generated by an electric cooker (100°C, 5% relative humidity, 50 min) effectively inactivated Tulane virus (>5.2-log10 reduction), rotavirus (>6.6-log10 reduction), adenovirus (>4.0-log10 reduction), and transmissible gastroenteritis virus (>4.7-log10 reduction). The respirator integrity (determined based on the particle filtration efficiency and quantitative fit testing) was not compromised after 20 cycles of 50-min dry heat treatment. Based on these results, we propose dry heat decontamination generated by an electric cooker (e.g., rice cookers, instant pots, ovens) to be an effective and accessible decontamination method for the safe reuse of N95 respirators.
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Building Environmental and Sociological Predictive Intelligence to Understand the Seasonal Threat of SARS-CoV-2 in Human Populations
Current modeling practices for environmental and sociological modulated infectious diseases remain inadequate to forecast the risk of outbreak(s) in human populations, partly due to a lack of integration of disciplinary knowledge, limited availability of disease surveillance datasets, and overreliance on compartmental epidemiological modeling methods. Harvesting data knowledge from virus transmission (aerosols) and detection (wastewater) of SARS-CoV-2, a heuristic score-based environmental predictive intelligence system was developed that calculates the risk of COVID-19 in the human population. Seasonal validation of the algorithm was uniquely associated with wastewater surveillance of the virus, providing a lead time of 7–14 days before a county-level outbreak. Using county-scale disease prevalence data from the United States, the algorithm could predict COVID-19 risk with an overall accuracy ranging between 81% and 98%. Similarly, using wastewater surveillance data from Illinois and Maryland, the SARS-CoV-2 detection rate was greater than 80% for 75% of the locations during the same time the risk was predicted to be high. Results suggest the importance of a holistic approach across disciplinary boundaries that can potentially allow anticipatory decision-making policies of saving lives and maximizing the use of available capacity and resources