Generative design of 3D printed hands-free door handles for reduction of contagion risk in public buildings

During the emergency caused by COVID 19 evidence has been provided about the risk of easily getting the virus by touching contaminated surfaces and then by touching eyes, mouth, or nose with infected hands. In view of the restarting of daily activities in presence, it is paramount to put in place any strategy that, in addition to social distancing, is capable to positively impact on the safety levels in public buildings by reducing such risk. The main aim of this paper is to conceive a design methodology, based on a digital, flawless, and sustainable procedure, for producing human-building interfacing solutions that allow anybody to interact in a safer and more comfortable way. Such solutions are focused on the adaptation of existing buildings features and are thought to be an alternative to sensor based touchless technology when this is not applicable due to economic or time constraints. The process is based on the integration of digital technologies such as 3D Scanning, Generative Design and Additive Manufacturing and is optimised to be intuitive and to be adaptive, hence, to be replicable on different kinds of surfaces. The design concept is finalised to generate automatically different products that meet geometry fitting requirements and therefore adapt to the specific geometries of existing handles. A specific case on Hands Free Door Handles is presented and the results of manufacturing and preliminary validation process are provided and discussed.

Modelling the direct virus exposure risk associated with respiratory events

The outbreak of the COVID-19 pandemic highlighted the importance of accurately modelling the pathogen transmission via droplets and aerosols emitted while speaking, coughing and sneezing. In this work, we present an effective model for assessing the direct contagion risk associated with these pathogen-laden droplets. In particular, using the most recent studies on multi-phase flow physics, we develop an effective yet simple framework capable of predicting the infection risk associated with different respiratory activities in different ambient conditions. We start by describing the mathematical framework and benchmarking the model predictions against well-assessed literature results. Then, we provide a systematic assessment of the effects of physical distancing and face coverings on the direct infection risk. The present results indicate that the risk of infection is vastly impacted by the ambient conditions and the type of respiratory activity, suggesting the non-existence of a universal safe distance. Meanwhile, wearing face masks provides excellent protection, effectively limiting the transmission of pathogens even at short physical distances, i.e. 1 m.

Score estimate of covid-19 risks as per socio-hygienic and behavioral indicators

Epidemiologic situation remains a serious concern all over the world due to the coronavirus infection spread. It is vital to adhere to measure of non-specific COVID-19 prevention. According to literature data, the highest risks of the infection spread occur in public transport, retail outlets where foods and nonfoods are sold, medical organizations, and chemists’ shops. Our research objects were socio-hygienic and behavioral indicators that were risk factors of the coronavirus infection. Our research aim was to substantiate a score estimate of the COVID-19 contagion risk based on socio-hygienic and behavioral indicators. Questioning was applied to determine frequency of visiting public places and adherence to basic measurements of non-specific COVID-19 prevention; overall, 400 respondents took part in it. A questionnaire was developed by experts of the De-partment of General Hygiene at Sechenov University and contained questions aimed at revealing informative signs (risk factors) of the coronavirus infection spread. Cluster analysis was applied to group respondents’ questions and to identify informative signs for further development of a scale showing risk categories. Factor analysis in a form of principal component analysis was applied to questions that had the highest number of statistically significant indicators of Spearman’s correlation coefficient. We developed a procedure for assessing risks of COVID-19 contagion according to socio-hygienic and behavioral in-dicators and substantiated risk categories. The most significant risk factors were indicators related to mandatory mask wearing when visiting specific social objects (risk objects); when taking trips by various means of public transport and duration of such trips; keeping social distance when visiting social objects. We performed score estimate of risk categories regarding COVID-19 contagion.

Fear of infectious diseases and perceived contagion risk count as an occupational health and safety hazard: Accounts from correctional officer recruits in Canada

Prisons are poorly ventilated confined spaces with limited physical distancing opportunities, making an environment conducive to the spread of infectious diseases. Based on empirical research with correctional officer recruits in Canada, we analyze the reasons and sources of fear, and the measures that recruits adopt to counter their fear of contagion. Our study marks an advance in the correctional work literature, which, to date, has tended to view perceived contagion risks as a workplace challenge that can be overcome with occupational skill and experience. In contrast with the existing literature, we present fear and perceived contagion risk as an “operational stress injury” that affects all correctional officers; a structural occupational health and safety problem that needs redressing from the labor policy perspective.

Sustainable Finance and COVID-19: The Reaction of ESG Funds to the 2020 Crisis

We investigated the financial performance of a sample of sustainable investment funds in terms of returns, volatility, and contagion risk during the financial crisis caused by the COVID-19 pandemic. In order to conduct a more reliable analysis, we considered a homogenous sample composed of 30 funds declaring the same benchmark (the MSCI Europe index). The Morningstar Sustainability ESG rating was used to determine the level of sustainability of each fund. Both the GARCH models and the event study suggest that funds with a higher ESG rating were able to outperform other funds during the COVID-19 period. These funds had a greater level of resilience and exhibited a lower level of risk contagion during the pandemic. These instruments appear to assume the role of risk protection and should be considered a means of both promoting sustainable growth and minimizing portfolio risk.

A Dynamic Contagion Risk Model with Recovery Features

We introduce threshold growth in the classical threshold contagion model, or equivalently a network of Cramér-Lundberg processes in which nodes have downward jumps when there is a failure of a neighboring node. Choosing the configuration model as underlying graph, we prove fluid limits for the baseline model, as well as extensions to the directed case, state-dependent interarrival times and the case of growth driven by upward jumps. We obtain explicit ruin probabilities for the nodes according to their characteristics: initial threshold and in- (and out-) degree. We then allow nodes to choose their connectivity by trading off link benefits and contagion risk. We define a rational equilibrium concept in which nodes choose their connectivity according to an expected failure probability of any given link and then impose condition that the expected failure probability coincides with the actual failure probability under the optimal connectivity. We show existence of an asymptotic equilibrium and convergence of the sequence of equilibria on the finite networks. In particular, our results show that systems with higher overall growth may have higher failure probability in equilibrium.

The Role of Economic Contagion in the Inward Investment of Emerging Economies: The Dynamic Conditional Copula Approach

Contagion has been one of the most widely studied and challenging problems in recent economic research. This paper aims at capturing the main impact of contagion risk of the U.S. on foreign direct investment inflows in 18 emerging countries. To quantify the degree of contagion, the time-varying tail dependence copula is employed. Then, the Granger causality test and time series regression analysis are used to investigate the temporal and contemporaneous effects of contagion risk on investment inflows, respectively. Overall, the results confirm the time-varying contagion effects of the U.S. economy on 18 emerging economies. The size of contagion effects gradually increases for all countries, except Thailand, the Philippines, Argentina, and Chile. Furthermore, the results of the Granger causality test and regression reveal that temporal and contemporaneous effects of contagion risk on investment inflows exist in 8 out of 18 countries.