Project description:Centers for Disease Control and Prevention (CDC) warns the use of one-way valves or vents in face masks for potential threat of spreading COVID-19 through expelled respiratory droplets. Here, we have developed a nanoceutical cotton fabric duly sensitized with non-toxic zinc oxide nanomaterial for potential use as a membrane filter in the one-way valve for the ease of breathing without the threat of COVID-19 spreading. A detailed computational study revealed that zinc oxide nanoflowers (ZnO NFs) with almost two-dimensional petals trap SARS-CoV-2 spike proteins, responsible to attach to ACE-2 receptors in human lung epithelial cells. The study also confirmed significant denaturation of the spike proteins on the ZnO surface, revealing removal of the virus upon efficient trapping. Following the computational study, we have synthesized ZnO NF on a cotton matrix using a hydrothermal-assisted strategy. Electron-microscopic, steady-state, and picosecond-resolved spectroscopic studies confirm attachment of ZnO NF to the cotton (i.e., cellulose) matrix at the atomic level to develop the nanoceutical fabric. A detailed antimicrobial assay using Pseudomonas aeruginosa bacteria (model SARS-CoV-2 mimic) reveals excellent antimicrobial efficiency of the developed nanoceutical fabric. To our understanding, the nanoceutical fabric used in the one-way valve of a face mask would be the choice to assure breathing comfort along with source control of COVID-19 infection. The developed nanosensitized cloth can also be used as an antibacterial/anti CoV-2 washable dress material in general.
Project description:Coronavirus Disease 2019 (COVID-19) may spread through respiratory droplets released by infected individuals during coughing, sneezing, or speaking. Given the limited supply of professional respirators and face masks, the U.S. Centers for Disease Control and Prevention (CDC) has recommended home-made cloth face coverings for use by the general public. While there have been several studies on aerosol filtration performance of household fabrics, their effectiveness at blocking larger droplets has not been investigated. Here, we ascertained the performance of 11 common household fabrics at blocking large, high-velocity droplets, using a commercial medical mask as a benchmark. We also assessed the breathability (air permeability), texture, fiber composition, and water absorption properties of the fabrics. We found that most fabrics have substantial blocking efficiency (median values >70%). In particular, two layers of highly permeable fabric, such as T-shirt cloth, blocks droplets with an efficiency (>94%) similar to that of medical masks, while being approximately twice as breathable. The first layer allows about 17% of the droplet volume to transmit, but it significantly reduces their velocity. This allows the second layer to trap the transmitted droplets resulting in high blocking efficacy. Overall, our study suggests that cloth face coverings, especially with multiple layers, may help reduce droplet transmission of respiratory infections. Furthermore, face coverings made from materials such as cotton fabrics allow washing and reusing, and can help reduce the adverse environmental effects of widespread use of commercial disposable and non-biodegradable facemasks.
Project description:For 45 African countries/territories already reporting COVID-19 cases before 23 March 2020, we estimate the dates of reporting 1,000 and 10,000 cases. Assuming early epidemic trends without interventions, all 45 were likely to exceed 1,000 confirmed cases by the end of April 2020, with most exceeding 10,000 a few weeks later.
Project description:The COVID-19 pandemic in 2020 caused unprecedented shocks to agricultural food systems, including increased risk to worker health, labor-related input costs, and production uncertainty. Despite employer precautions, there were numerous worksite outbreaks of COVID-19. This paper examines the relationship between month-to-month variation in historical agricultural employment and changes in the incidence of confirmed COVID-19 cases and deaths within U.S. counties from April to August 2020. The results show that employment of 100 additional workers in fruit, vegetable, and horticultural production was associated with 4.5% more COVID-19 cases within counties or an additional 18.65 COVID-19 cases and 0.34 additional COVID-19 deaths per 100,000 individuals in the county workforce.
Project description:Human to human transmissible infectious diseases spread in a population using human interactions as its transmission vector. The early stages of such an outbreak can be modeled by a graph whose edges encode these interactions between individuals, the vertices. This article attempts to account for the case when each individual entails in different kinds of interactions which have therefore different probabilities of transmitting the disease. The majority of these results can be also stated in the language of percolation theory. The main contributions of the article are: (1) Extend to this setting some results which were previously known in the case when each individual has only one kind of interactions. (2) Find an explicit formula for the basic reproduction number [Formula: see text] which depends only on the probabilities of transmitting the disease along the different edges and the first two moments of the degree distributions of the associated graphs. (3) Motivated by the recent Covid-19 pandemic, we use the framework developed to compute the [Formula: see text] of a model disease spreading in populations whose trees and degree distributions are adjusted to several different countries. In this setting, we shall also compute the probability that the outbreak will not lead to an epidemic. In all cases we find such probability to be very low if no interventions are put in place.
Project description:The emergence and global spread of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is critical to understanding how to prevent or control a future viral pandemic. We review the tools used for this retrospective search, their limits, and results obtained from China, France, Italy and the USA. We examine possible scenarios for the emergence of SARS-CoV-2 in the human population. We consider the Chinese city of Wuhan where the first cases of atypical pneumonia were attributed to SARS-CoV-2 and from where the disease spread worldwide. Possible superspreading events include the Wuhan-based 7th Military World Games on October 18-27, 2019 and the Chinese New Year holidays from January 25 to February 2, 2020. Several clues point to an early regional circulation of SARS-CoV-2 in northern Italy (Lombardi) as soon as September/October 2019 and in France in November/December 2019, if not before. With the goal of preventing future pandemics, we call for additional retrospective studies designed to trace the origin of SARS-CoV-2.
Project description:Given that real-world infection-spread scenarios pose many uncertainties, and predictions and simulations may differ from reality, this study explores factors essential for more realistically describing an infection situation. It furnishes three approaches to the argument that human mobility can create an acceleration of the spread of COVID-19 infection and its cyclicality under the simultaneous relationship. First, the study presents a dynamic model comprising the infection-mobility trade-off and mobility demand, where an increase in human mobility can cause infection explosion and where, conversely, an increase in new infections can be made temporary by suppressing mobility. Second, using time-series data for Japan, it presents empirical evidence for a stochastic trend and cycle in new infection cases. Third, it employs macroeconometrics to ascertain the feasibility of our model's predictions. Accordingly, from March 2020 to May 2021, the sources of COVID-19 infection spread in Japan varied significantly over time, and each change in the trend and cycle of new infection cases explained approximately half the respective variation.