Colorectal Cancer Stage at Diagnosis Before vs During the COVID-19 Pandemic in Italy

IMPORTANCE Delays in screening programs and the reluctance of patients to seek medical attention because of the outbreak of SARS-CoV-2 could be associated with the risk of more advanced colorectal cancers at diagnosis. OBJECTIVE To evaluate whether the SARS-CoV-2 pandemic was associated with more advanced oncologic stage and change in clinical presentation for patients with colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS This retrospective, multicenter cohort study included all 17 938 adult patients who underwent surgery for colorectal cancer from March 1, 2020, to December 31, 2021 (pandemic period), and from January 1, 2018, to February 29, 2020 (prepandemic period), in 81 participating centers in Italy, including tertiary centers and community hospitals. Follow-up was 30 days from surgery. EXPOSURES Any type of surgical procedure for colorectal cancer, including explorative surgery, palliative procedures, and atypical or segmental resections. MAIN OUTCOMES AND MEASURES The primary outcome was advanced stage of colorectal cancer at diagnosis. Secondary outcomes were distant metastasis, T4 stage, aggressive biology (defined as cancer with at least 1 of the following characteristics: signet ring cells, mucinous tumor, budding, lymphovascular invasion, perineural invasion, and lymphangitis), stenotic lesion, emergency surgery, and palliative surgery. The independent association between the pandemic period and the outcomes was assessed using multivariate random-effects logistic regression, with hospital as the cluster variable. RESULTS A total of 17 938 patients (10 007 men [55.8%]; mean [SD] age, 70.6 [12.2] years) underwent surgery for colorectal cancer: 7796 (43.5%) during the pandemic period and 10 142 (56.5%) during the prepandemic period. Logistic regression indicated that the pandemic period was significantly associated with an increased rate of advanced-stage colorectal cancer (odds ratio [OR], 1.07; 95%CI, 1.01-1.13; P = .03), aggressive biology (OR, 1.32; 95%CI, 1.15-1.53; P < .001), and stenotic lesions (OR, 1.15; 95%CI, 1.01-1.31; P = .03). CONCLUSIONS AND RELEVANCE This cohort study suggests a significant association between the SARS-CoV-2 pandemic and the risk of a more advanced oncologic stage at diagnosis among patients undergoing surgery for colorectal cancer and might indicate a potential reduction of survival for these patients

Dispersion of a Passive Scalar Fluctuating Plume in a Turbulent Boundary Layer. Part III: Stochastic Modelling

International audienceWe analyze the reliability of the Lagrangian stochastic micromixing 8 method in predicting higher-order statistics of the passive scalar concentration in-9 duced by an elevated source (of varying diameter) placed in a turbulent boundary 10 layer. To that purpose we analyze two different modelling approaches by testing 11 their results against the wind-tunnel measurements discussed in Part I (Nironi 12 et al., Boundary-Layer Meteorology, 2015, Vol.156, 415-446). The first is a prob-13 ability density function (PDF) micromixing model that simulates the effects of 14 the molecular diffusivity on the concentration fluctuations by taking into account 15 the background particles. The second is a new model, named VPΓ , conceived in 16 order to minimize the computational costs. This is based on the volumetric par-17 ticle approach providing estimates of the first two concentration moments with 18 no need for the simulation of the background particles. In this second approach, 19 higher-order moments are computed based on the estimates of these two moments 20 and under the assumption that the concentration PDF is a Gamma distribution. 21 The comparisons concern the spatial distribution of the first four moments of the 22 concentration and the evolution of the PDF along the plume centreline. The nov-23 elty of this work is twofold: i) we perform a systematic comparison of the results 24 of micro-mixing Lagrangian models against experiments providing profiles of the 25 first four moments of the concentration within an inhomogeneous and anisotropic 26 turbulent flow, and ii) we show the reliability of the VPΓ model as an operational 27 tool for the prediction of the PDF of the concentration. 2

Concentration Fluctuations from Localized Atmospheric Releases

We review the efforts made by the scientific community in more than seventy years to elucidate the behaviour of concentration fluctuations arising from localized atmospheric releases of dynamically passive and non-reactive scalars. Concentration fluctuations are relevant in many fields including the evaluation of toxicity, flammability, and odour nuisance. Characterizing concentration fluctuations requires not just the mean concentration but also at least the variance of the concentration in the location of interest. However, for most purposes the characterization of the concentration fluctuations requires knowledge of the concentration probability density function (PDF) in the point of interest and even the time evolution of the concentration. We firstly review the experimental works made both in the field and in the laboratory, and cover both point sources and line sources. Regarding modelling approaches, we cover analytical, semi-analytical, and numerical methods. For clarity of presentation we subdivide the models in two groups, models linked to a transport equation, which usually require a numerical resolution, and models mainly based on phenomenological aspects of dispersion, often providing analytical or semi-analytical relations. The former group includes: large-eddy simulations, Reynolds-averaged Navier–Stokes methods, two-particle Lagrangian stochastic models, PDF transport equation methods, and heuristic Lagrangian single-particle methods. The latter group includes: fluctuating plume models, semi-empirical models for the concentration moments, analytical models for the concentration PDF, and concentration time-series models. We close the review with a brief discussion highlighting possible useful additions to experiments and improvements to models

Lagrangian Stochastic Modelling of Dispersion in the Convective Boundary Layer with Skewed Turbulence Conditions and a Vertical Density Gradient: Formulation and Implementation in the FLEXPART Model

International audienceA correction for the vertical gradient of air density has been incorporated into a skewed probability density function formulation for turbulence in the convective boundary layer. The related drift term for Lagrangian stochastic dispersion modelling has been derived based on the well-mixed condition. Furthermore, the formulation has been extended to include unsteady turbulence statistics and the related additional component of the drift term obtained. These formulations are an extension of the drift formulation reported by Luhar et al. (1996) following the well-mixed condition proposed by Thomson (1987). Comprehensive tests were carried out to validate the formulations including consistency between forward and backward simulations and preservation of a well-mixed state with unsteady conditions. The stationary state CBL drift term with density correction was incorporated into the FLEXPART and FLEXPART-WRF Lagrangian models, and included the use of an ad hoc transition function that modulates the third moment of the vertical velocity based on stability parameters. Due to the current implementation of the FLEXPART models, only a steady-state horizontally homogeneous drift term could be included. To avoid numerical instability, in the presence of non-stationary and horizontally inhomogeneous conditions, a re-initialization procedure for particle velocity was used. The criteria for re-initialization and resulting errors were assessed for the case of non-stationary conditions by comparing a reference numerical solution in simplified unsteady conditions, obtained using the non-stationary drift term, and a solution based on the steady drift with re-initialization. Two examples of “real-world” numerical simulations were performed under different convective conditions to demonstrate the effect of the vertical gradient in density on the particle dispersion in the CBL

Stochastic Fields Method for Sub-Grid Scale Emission Heterogeneity in Mesoscale Atmospheric Dispersion Models

The stochastic fields method for turbulent reacting flows has been applied to the issue of sub-grid scale emission heterogeneity in a mesoscale model. This method is a solution technique for the probability density function (PDF) transport equation and can be seen as a straightforward extension of currently used mesoscale dispersion models. It has been implemented in an existing mesoscale model and the results are compared with Large-Eddy Simulation (LES) data devised to test specifically the effect of sub-grid scale emission heterogeneity on boundary layer concentration fluctuations. The sub-grid scale emission variability is assimilated in the model as a PDF of the emissions. The stochastic fields method shows excellent agreement with the LES data without adjustment of the constants used in the mesoscale model. The stochastic fields method is a stochastic solution of the transport equations for the concentration PDF of dispersing scalars, therefore it possesses the ability to handle chemistry of any complexity without the need to introduce additional closures for the high order statistics of chemical species. This study shows for the first time the feasibility of applying this method to mesoscale chemical transport models.JRC.F.8-Sustainable Transport (Ispra