Discovering the mechanism that enables pre-symptomatic individuals to transmit the SARS-CoV-2 virus has a significant impact on the possibility of controlling COVID-19 pandemic. To this end, we have developed an evidence based quantitative mechanistic mathematical model. The model explicitly tracks the dynamics of contact and airborne transmission between individuals indoors, and was validated against the observed fundamental attributes of the epidemic, the secondary attack rate (SAR) and serial interval distribution. Using the model we identified the dominant driver of pre-symptomatic transmission, which was found to be contact route, while the contribution of the airborne route is negligible. We provide evidence that a combination of rather easy to implement measures of frequent hand washing, cleaning fomites and avoiding physical contact decreases the risk of infection by an order of magnitude, similarly to wearing masks and gloves.

The results of this work provide the formulator with guidelines to select both r(m) and gSTD that guarantee optimal absorption.

The Haifa bay area (HBA), which includes Mount Carmel and the Zevulun valley is the third largest metropolitan area in Israel. It is also a centre of heavy industry and an important transportation hub which serve as sources of local anthropogenic pollution. Such sources are associated with adverse health effects. In order to estimate the possible exposure of the inhabitants in such heterogeneous orographic area, a detailed atmospheric transport and dispersion modelling study is required, which in turn must take into account the local micrometeorology. The aim of this study is to conduct a spatio-temporal analysis of the flow field in the HBA in order to identify the common patterns of the average wind and characterize the statistical parameters of turbulence in this area, essential for detailed pollutants dispersion modelling. This study analyses data collected during four months of summer in a network of 16 weather stations which extend across Mount Carmel and the Zevulun valley. It was found that, during the evening and night time on Mount Carmel, different flow patterns may develop on each side, separated by the watershed line. When such conditions do not develop, as well as during the daytime, the wind field, both on Mount Carmel and the Zevulun valley is approximately homogenous. The analysis of the Monin–Obukhov similarity theory functions for the velocity standard deviations show a distinct difference between Mount Carmel and the Zevulun valley, as well as between strong and weak winds. This difference can be clearly seen also in the diurnal hourly distribution of atmospheric stabilities which exhibit higher proportions of unstable conditions in the Zevulun valley during day time and higher proportion of stable stratifications at the Mount Carmel during night-time.

Understanding the factors that increase the transmissibility of the recently emerging variants of SARS-CoV-2 can aid in mitigating the COVID-19 pandemic. Enhanced transmissibility could result from genetic variations that improve how the virus operates within the host or its environmental survival. Variants with enhanced within-host behavior are either more contagious (leading infected individuals to shed more virus copies) or more infective (requiring fewer virus copies to infect). Variants with improved outside-host processes exhibit higher stability on surfaces and in the air. While previous studies focus on a specific attribute, we investigated the contribution of both within-host and outside-host processes to the overall transmission between two individuals. We used a hybrid deterministic-continuous and stochastic-jump mathematical model. The model accounts for two distinct dynamic regimes: fast-discrete actions of the individuals and slow-continuous environmental virus degradation processes. This model produces a detailed description of the transmission mechanisms, in contrast to most-viral transmission models that deal with large populations and are thus compelled to provide an overly simplified description of person-to-person transmission. We based our analysis on the available data of the Alpha, Epsilon, Delta, and Omicron variants on the household secondary attack rate (hSAR). The increased hSAR associated with the recent SARS-CoV-2 variants can only be attributed to within-host processes. Specifically, the Delta variant is more contagious, while the Alpha, Epsilon, and Omicron variants are more infective. The model also predicts that genetic variations have a minimal effect on the serial interval distribution, the distribution of the period between the symptoms’ onset in an infector–infectee pair.

An open-path spectrometer for fast spatial detection and identification of gaseous plumes in a realistic environmental conditions is presented. Gases are released in a 500 m 3 hall; detection and identification is performed by spectroscopic means-measuring the light spectral absorption (at 8 to 10 μm) by shining an externalcavity quantum cascade laser beam through the inspected volume. Real-time identification is demonstrated for gas plumes of CH 2 FCF 3 (R134a) and CHF 3 at a distance of 30 m round trip with a minimum identification level of 0.2 ppm (response times of 2 to 10 s). The relatively wide spectral coverage allows a high probability of detection (PD) and low probability for a false alarm to be obtained in these realistic conditions. It is also demonstrated that the use of several lines-of-sight improves PD as gas spreading in the hall in these conditions is slow and unpredictable.