A Lagrangian Approach Towards Quantitative Analysis Of Flow-mediated Infection Transmission In Indoor Spaces With Application To SARS-COV-2

The ongoing SARS-CoV-2 (Covid-19) pandemic has ushered an unforeseen level of global health and economic burden. As a respiratory infection, Covid-19 is known to have a dominant airborne transmission modality, wherein fluid flow plays a central role. Quantification of complex non-intuitive dynamics and transport of pathogen laden respiratory particles in indoor flows has been of specific interest. Here we present a Lagrangian computational approach towards quantification of human-to-human exposure quantifiers, and identification of pathways by which flow organizes transmission. We develop a Lagrangian viral exposure index in a parametric form, accounting for key parameters such as building and layout, ventilation, occupancy, biological variables. We also employ a Lagrangian computation of the Finite Time Lyapunov Exponent field to identify hidden patterns of transport. A systematic parametric study comprising a set of 120 simulations, yielding a total of 1,320 different exposure index computations are presented. Results from these simulations enable: (a) understanding the otherwise hidden ways in which air flow organizes the long-range transport of such particles; and (b) translating the micro-particle transport data into a quantifier for understanding infection exposure risks.

Geospatial Assessment of Agricultural Drought Vulnerability Using Integrated Three-Dimensional Model In The Upper Dwarakeshwar River Basin In West Bengal, India

It is essential to measure the degree of agricultural drought vulnerability in an underdeveloped rain-fed agro-based economy at the local, regional, and national level. Agricultural drought has become a major concern in respect to the global food crisis for investigation and development of a sustainable agricultural system that sustains the food security of a country. In this research, delineation of the agricultural drought vulnerability (ADV) status has been carried out by multidimensional mixed-method index approach using remote sensing and geographic information system. An integrated three-dimensional model has been adopted for this study. The three indices of this model are - Exposure Index (EI), Sensitivity Index (SI) and Adaptive Capacity Index (ACI). Exposure Index has been calculated using NDDI, LULC, ADI, DF, ADD and PI. Sensitivity Index has been calculated using satellite-based remote sensing factor VHI, NDWI, EVI, NDVI, VCI, NDWI, LST, and TCI. The ACI has been formed by combining the Environmental Adaptive Capacity (EAC), Social Adaptive Capacity (SAC) and Economical Adaptive Capacity (EcAC) Index. Each index has been computed by assigning the weights based on their relative importance by using the Analytic Hierarchy process (AHP) approach. Final results were classified into five vulnerability zones, e.g., very low, low, moderate, high, and very high covering an area 362.32 km2, 186.68 km2, 568.69 km2, 547.05 km2 and 266.89 km2 respectively. Finally, results have been validated with long term Aman paddy yield data (2004 to 2014) through the Yield Anomaly Index (YAI).

Interstitial Lung Abnormalities Detected by CT in Asbestos-Exposed Subjects Are More Likely Associated to Age

Objective: the aim of this study was to evaluate the association between interstitial lung abnormalities, asbestos exposure and age in a population of retired workers previously occupationally exposed to asbestos. Methods: previously occupationally exposed former workers to asbestos eligible for a survey conducted between 2003 and 2005 in four regions of France, underwent chest CT examinations and pulmonary function testing. Industrial hygienists evaluated asbestos exposure and calculated for each subject a cumulative exposure index (CEI) to asbestos. Smoking status information was also collected in this second round of screening. Expert radiologists performed blinded independent double reading of chest CT-scans and classified interstitial lung abnormalities into: no abnormality, minor interstitial findings, interstitial findings inconsistent with UIP, possible or definite UIP. In addition, emphysema was assessed visually (none, minor: emphysema <25%, moderate: between 25 and 50% and severe: >50% of the lung). Logistic regression models adjusted for age and smoking were used to assess the relationship between interstitial lung abnormalities and occupational asbestos exposure. Results: the study population consisted of 2157 male subjects. Interstitial lung abnormalities were present in 365 (16.7%) and emphysema in 444 (20.4%). Significant positive association was found between definite or possible UIP pattern and age (OR adjusted =1.08 (95% CI: 1.02–1.13)). No association was found between interstitial abnormalities and CEI or the level of asbestos exposure. Conclusion: presence of interstitial abnormalities at HRCT was associated to aging but not to cumulative exposure index in this cohort of former workers previously occupationally exposed to asbestos.