Modelling the impact of household size distribution on the transmission dynamics of COVID-19

Under the implementation of non-pharmaceutical interventions such as social distancing and lockdowns, household transmission has been shown to be significant for COVID-19, posing challenges for reducing incidence in settings where people are asked to self-isolate at home and to spend increasing amounts of time at home due to distancing measures. Accordingly, characteristics of households in a region have been shown to relate to transmission heterogeneity of the virus. We introduce a discrete-time stochastic epidemiological model to examine the impact of the household size distribution in a region on the transmission dynamics. We choose parameters to reflect incidence in two health regions of the Greater Vancouver area in British Columbia and simulate the impact of distancing measures on transmission, with household size distribution the only different parameter between simulations for the two regions. Our result suggests that the dissimilarity in household size distribution alone can cause significant differences in incidence of the two regions, and the distributions drive distinct dynamics that match reported cases. Furthermore, our model suggests that offering individuals a place to isolate outside their household can speed the decline in cases, and does so more effectively where there are more larger households.     

Automated actuation of nasal spray products: effect of hand-related variability on the in vitro performance of Flonase nasal spray

Objective: To determine if patient-related variability for adults and children recorded during hand spraying of Flonase with an instrumented nasal spray results in significant differences in spray weight, droplet size or spray pattern.

Methods: Settings derived from adult and pediatric participants hand-spraying nasal sprays were implemented into force and velocity-controlled automated actuators. Spray weight, droplet size distribution and spray pattern tests were performed using iterations of actuation force (AF) and force rise, hold and fall times. Travel, actuation velocity and release velocity settings were also investigated.

Results: The variability measured in adult-derived actuator settings did not result in any differences in spray weight, but pediatric participants spraying with low AF and/or compression velocity (CV) were predicted to receive a partial dose or no dose at all under some circumstances. Droplet size characteristics were sensitive to the hand-based variability, with actuation force, force rise time and CV hand-related settings all resulting in significant differences in the droplet size.

Conclusions: This study demonstrated how variability in hand spraying by adults and pediatric patients could result in differences in nasal spray characteristics, thus demonstrating the importance of monitoring how the prospective patient groups are likely to use a nasal spray.     

The changes in the effects of social media use of Cypriots due to COVID-19 pandemic

Social media is the leading medium which is used for communication during the COVID-19 pandemic. The research conducted aims to fill the gap of literature related to social media use during the COVID-19 pandemic. This research aims at uncovering the influences of social media use in several dimensions during lockdown(s). The study aims to answer the research question of: Are the influences of social media use different from normal times? The online questionnaire has been completed by six hundred and sixty-eight users within the period of lockdown. The author prepared the questionnaire, which is composed of 22 positive statements in order to evaluate the effects of social media use during the COVID-19 pandemic. A 5 point Likert scale was used, where reliability and validity were calculated by the Cronbach's alpha value, which was 0.751. Findings highlight that users have more information about COVID-19, and they follow recent information via social media, which shows the shift towards digital medium. Findings also indicate that users are aware of fake news, and they follow official sources. Social media is powerful to affect decision-makers, and respondents' social media use did not create any panic or anxiety amongst them. This research indicates that respondents' social media use during COVID-19 is different from normal times as a common purpose triggers this, survival. Before the COVID-19 pandemic, most of social media shares were like a dream or a strong desire that may cause anxiety in others. During the pandemic, people are in lockdown and share similar feelings and follow similar behavioural patterns. As there is a common purpose and struggle via users, psychological well-being is not affected negatively.     

Socio-economic determinants of mobility responses during the first wave of COVID-19 in Italy: from provinces to neighbourhoods

After more than 1 year into the COVID-19 pandemic, governments worldwide still face the challenge of adopting non-pharmaceutical interventions to mitigate the risks posed by the emergence of new SARS-CoV-2 variants and the lack of a worldwide equitable vaccine allocation. Thus, it becomes crucial to identify the drivers of mobility responses to mitigation efforts during different restriction regimes, for planning interventions that are both economically and socially sustainable while effective in controlling an outbreak. Here, using anonymous and privacy-enhanced cell phone data from Italy, we investigate the determinants of spatial variations of reductions in mobility and co-location in response to the adoption and the lift of restrictions, considering both provinces and city neighbourhoods. In large urban areas, our analysis uncovers the desertification of historic city centres, which persisted after the end of the lockdown. Such centre-periphery gradient was mainly associated with differences in educational attainment. At the province level, the local structure of the labour market mainly explained the variations in mobility responses, together with other demographic factors, such as the population’s age and sex composition. In the future, targeted interventions should take into account how the ability to comply with restrictions varies across geographical areas and socio-demographic groups.     

Vibrations of the beam due to a load moving with stochastic velocity

The aim of this work is to give an approach for obtaining the probabilistic characteristics of the beam response due to a load moving with stochastic velocity. It is assumed that the load is modelled by a set of point forces of random amplitudes, the inter-arrival times are random variables that constitute the Poisson stochastic process and the forces are moving along the beam with velocities that are also stochastic. The effective solution in such a case can be obtained by applying the Ito integral and the Ito differentiation rule. In this paper, the theoretical basis for such an approach is given. Analytical expressions for calculating the probabilistic characteristics of the beam response and numerical results are shown.     

Automated contact tracing: a game of big numbers in the time of COVID-19

One of the more widely advocated solutions for slowing down the spread of COVID-19 has been automated contact tracing. Since proximity data can be collected by personal mobile devices, the natural proposal has been to use this for automated contact tracing providing a major gain over a manual implementation. In this work, we study the characteristics of voluntary and automated contact tracing and its effectiveness for mapping the spread of a pandemic due to the spread of SARS-CoV-2. We highlight the infrastructure and social structures required for automated contact tracing to work. We display the vulnerabilities of the strategy to inadequate sampling of the population, which results in the inability to sufficiently determine significant contact with infected individuals. Of crucial importance will be the participation of a significant fraction of the population for which we derive a minimum threshold. We conclude that relying largely on automated contact tracing without population-wide participation to contain the spread of the SARS-CoV-2 pandemic can be counterproductive and allow the pandemic to spread unchecked. The simultaneous implementation of various mitigation methods along with automated contact tracing is necessary for reaching an optimal solution to contain the pandemic.     

Time variation in the probability of failing to detect a case of polymerase chain reaction testing for SARS-CoV-2 as estimated from a viral dynamics model

Viral tests including polymerase chain reaction (PCR) tests are recommended to diagnose COVID-19 infection during the acute phase of infection. A test should have high sensitivity; however, the sensitivity of the PCR test is highly influenced by viral load, which changes over time. Because it is difficult to collect data before the onset of symptoms, the current literature on the sensitivity of the PCR test before symptom onset is limited. In this study, we used a viral dynamics model to track the probability of failing to detect a case of PCR testing over time, including the presymptomatic period. The model was parametrized by using longitudinal viral load data collected from 30 hospitalized patients. The probability of failing to detect a case decreased toward symptom onset, and the lowest probability was observed 2 days after symptom onset and increased afterwards. The probability on the day of symptom onset was 1.0% (95% CI: 0.5 to 1.9) and that 2 days before symptom onset was 60.2% (95% CI: 57.1 to 63.2). Our study suggests that the diagnosis of COVID-19 by PCR testing should be done carefully, especially when the test is performed before or way after symptom onset. Further study is needed of patient groups with potentially different viral dynamics, such as asymptomatic cases.     

Asian tigers and the Chinese dragon: Competition and collaboration between sentinels of pandemics from SARS to COVID-19

This article compares the management of COVID-19 in different Asian states—China, Hong Kong, Singapore, Taiwan, South Korea, Japan, and Vietnam—after their reactions to the SARS crisis in 2003. It uses animal metaphors and the concept of sentinel territory to describe the way these states have prepared for the next pandemic crisis in a mix of competition and collaboration that produces solidarity.     

Effectiveness of non-pharmaceutical interventions to contain COVID-19: a case study of the 2020 spring pandemic wave in New York City

As COVID-19 continues to pose significant public health threats, quantifying the effectiveness of different public health interventions is crucial to inform intervention strategies. Using detailed epidemiological and mobility data available for New York City and comprehensive modelling accounting for under-detection, we reconstruct the COVID-19 transmission dynamics therein during the 2020 spring pandemic wave and estimate the effectiveness of two major non-pharmaceutical interventions—lockdown-like measures that reduce contact rates and universal masking. Lockdown-like measures were associated with greater than 50% transmission reduction for all age groups. Universal masking was associated with an approximately 7% transmission reduction overall and up to 20% reduction for 65+ year olds during the first month of implementation. This result suggests that face covering can substantially reduce transmission when lockdown-like measures are lifted but by itself may be insufficient to control SARS-CoV-2 transmission. Overall, findings support the need to implement multiple interventions simultaneously to effectively mitigate COVID-19 spread before the majority of population can be protected through mass-vaccination.     

The effectiveness of an air cleaner in controlling droplet/aerosol particle dispersion emitted from a patient's mouth in the indoor environment of dental clinics

Dental healthcare workers (DHCWs) are at high risk of occupational exposure to droplets and aerosol particles emitted from patients'' mouths during treatment. We evaluated the effectiveness of an air cleaner in reducing droplet and aerosol contamination by positioning the device in four different locations in an actual dental clinic. We applied computational fluid dynamics (CFD) methods to solve the governing equations of airflow, energy and dispersion of different-sized airborne droplets/aerosol particles. In a dental clinic, we measured the supply air velocity and temperature of the ventilation system, the airflow rate and the particle removal efficiency of the air cleaner to determine the boundary conditions for the CFD simulations. Our results indicate that use of an air cleaner in a dental clinic may be an effective method for reducing DHCWs'' exposure to airborne droplets and aerosol particles. Further, we found that the probability of droplet/aerosol particle removal and the direction of airflow from the cleaner are both important control measures for droplet and aerosol contamination in a dental clinic. Thus, the distance between the air cleaner and droplet/aerosol particle source as well as the relative location of the air cleaner to both the source and the DHCW are important considerations for reducing DHCWs'' exposure to droplets/aerosol particles emitted from the patient''s mouth during treatments.     

Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak

An intertwined supply network (ISN) is an entirety of interconnected supply chains (SC) which, in their integrity secure the provision of society and markets with goods and services. The ISNs are open systems with structural dynamics since the firms may exhibit multiple behaviours by changing the buyer-supplier roles in interconnected or even competing SCs. From the positions of resilience, the ISNs as a whole provide services to society (e.g. food service, mobility service or communication service) which are required to ensure a long-term survival. The analysis of survivability at the level of ISN requires a consideration at a large scale as resilience of individual SCs. The recent example of coronavirus COVID-19 outbreak clearly shows the necessity of this new perspective. Our study introduces a new angle in SC resilience research when a resistance to extraordinary disruptions needs to be considered at the scale of viability. We elaborate on the integrity of the ISN and viability. The contribution of our position study lies in a conceptualisation of a novel decision-making environment of ISN viability. We illustrate the viability formation through a dynamic game-theoretic modelling of a biological system that resembles the ISN. We discuss some future research areas.     

Antisense technology as a potential strategy for the treatment of coronaviruses infection: With focus on COVID‐19

After the outbreak of coronavirus disease 2019 (COVID‐19) in December 2019 and the increasing number of SARS‐CoV‐2 infections all over the world, researchers are struggling to investigate effective therapeutic strategies for the treatment of this infection. Targeting viral small molecules that are involved in the process of infection is a promising strategy. Since many host factors are also used by SARS‐CoV‐2 during various stages of infection, down‐regulating or silencing these factors can serve as an effective therapeutic tool. Several nucleic acid‐based technologies including short interfering RNAs, antisense oligonucleotides, aptamers, DNAzymes, and ribozymes have been suggested for the control of SARS‐CoV‐2 as well as other respiratory viruses. The antisense technology also plays an indispensable role in the treatment of many other diseases including cancer, influenza, and acquired immunodeficiency syndrome. In this review, we summarised the potential applications of antisense technology for the treatment of coronaviruses and specifically COVID‐19 infection.     

Impacts of a delayed and slow-paced vaccination on cases and deaths during the COVID-19 pandemic: a modelling study

In Brazil, vaccination has always cut across party political and ideological lines, which has delayed its start and brought the whole process into disrepute. Such divergences put the immunization of the population in the background and create additional hurdles beyond the pandemic, mistrust and scepticism over vaccines. We conduct a mathematical modelling study to analyse the impacts of late vaccination along with slowly increasing coverage, as well as how harmful it would be if part of the population refused to get vaccinated or missed the second dose. We analyse data from confirmed cases, deaths and vaccination in the state of Rio de Janeiro in the period between 10 March 2020 and 27 October 2021. We estimate that if the start of vaccination had been 30 days earlier, combined with efforts to drive vaccination rates up, about 31 657 deaths could have been avoided. In addition, the slow pace of vaccination and the low demand for the second dose could cause a resurgence of cases as early as 2022. Even when reaching the expected vaccination coverage for the first dose, it is still challenging to increase adherence to the second dose and maintain a high vaccination rate to avoid new outbreaks.     

Status of engineering change management in the engineer-to-order production environment: insights from a multiple case study

Engineering Changes (ECs) are a fact of life for companies in the Engineer-To-Order (ETO) production environment. Various Engineering Change Management (ECM) strategies, practices and tools exist, but no explicit distinction has been made regarding ECM in different production environments. Using a multiple case study method, this article investigates how ETO companies manage ECs and how ETO characteristics influence ECM. A generic ECM framework was developed and used to map ECM in the cases. The study showed that ETO companies use similar practices for handling ECs, while ECM tools are either not used by the companies or used to a very limited extent. It was found that the use of some ECM practices and tools is complicated by specific ETO company characteristics. However, no reasons were found for the lack of computer-based tools, change propagation and impact assessment tools, change reduction and front-loading tools, and design tools. This suggests, firstly, that there is vast room for improvement in ETO companies when it comes to ECM; and secondly, that the applicability of such tools should be further tested in the ETO environment. Based on the findings, some suggestions as to how ECM can be improved in ETO companies are given to practitioners.     

Optimizing Drug Delivery to the Lung: Design of a CFC-Free Corticosteroid Metered-Dose Aerosol System

The mandatory replacement of chlorofluorocarbons (CFCs) with ozone–friendly propellants, such as hydrofluoroalkanes (HFAs), has provided an opportunity to optimize aerosol design and improve drug delivery to pulmonary tissue. Asthma is an inflammatory disorder of the lungs that appears to affect both small and large airways, so ideally, inhaled corticosteroid should reach both central and peripheral sites. This review considers the development of an aerosol system containing beclomethasone dipropionate in hydrofluoroalkane–134a (HFA) propellant (Qvar?, 3M Health Care, Loughborough, UK) designed to target medication delivery throughout the bronchopulmonary tree and to improve the therapeutic ratio (topical efficacy: systemic safety), thereby offering potential clinical benefits to asthma patients.     

A metallurgical study of the contamination zone at the surface of dental Ti castings, due to the phosphate-bonded investment material: the protection efficacy of a ceramic coating

Commercial pure (cp) titanium exhibits remarkable advantages compared to conventional dental alloys, mostly in the fields of biocompatibility and corrosion resistance. Today there exist very optimistic perspectives for the use of titanium as an ideal alternative for the conventional dental alloys. However, titanium casting procedure shows some serious difficulties related mainly with its high melting point and its great chemical reactivity at high temperatures. As a result, an extensive contamination is observed in Ti castings when SiO₂-based investment materials are used (phosphate-bonded or silica-bonded). In the present work, a detailed metallurgical study of the contamination zone of Ti castings due to Si, P and O, was performed. The new phases which formed, were investigated and analyzed using mainly light and scanning electron microscopy, as well as energy dispersion spectrometry. These phases were found to be: -Ti, -Ti and a Ti-Si compound. An attempt was done to prevent the contamination of cast Ti by using a wax pattern coating technique. The protection efficacy of a ZrO₂ coating was proven. Ti castings without contamination were obtained in this way.     

Bayesian meta‐modelling of engineering design simulations: a sequential approach with adaptation to irregularities in the response behaviour

Among current meta‐modelling approaches, Bayesian‐based interpolative methods have received significant attention in the literature. These methods are particularly known for their capability to adapt to the response function behaviour in order to generate good meta‐models with fewer experiments. Current Bayesian adaptation techniques, however, are mainly based on the assumption that some variables are more important (or sensitive) than others. These less sensitive variables are weighted less or ignored to reduce the dimension of the design space. This assumption limits the scope and applicability of these models since in many practical cases none of the variables can be completely ignored or weighted less than others. This paper proposes a pragmatic approach that identifies regions of the design space where more experiments are needed based on the response function behaviour. The proposed approach adaptively utilizes the information obtained from previous experiments, builds interim meta‐models, and identifies ‘irregular’ regions in which more experiments are needed. The behaviour of the interim meta‐model is then quantified as a spatial function and incorporated into the next stage of the design to sequentially improve the accuracy of the obtained meta‐model. The performance of the new approach is demonstrated using a numerical and an engineering example. Copyright © 2005 John Wiley & Sons, Ltd.     

Validation of the photomechanical spalling test in the case of non-linear dynamic response: Application to a granite rock

In this paper, the use of the virtual fields method for the identification of a strongly asymmetric compression–tension response of rock-like materials under dynamic tensile loading is investigated. The photomechanical spalling set-up is used, which induces an indirect tensile load in a non-balanced sample, and the inertial component of the test is directly related to the measured dynamic stress with no previous assumption on the material behaviour. This experimental method provides a direct route to identifying the material asymmetric constitutive response in compression and tension under a uniaxial stress state as well as the material non-linear response after tensile strength is reached. To validate this approach, the entire measurement chain for the case of a post-peak response is investigated through simulated experiments that incorporate a damage model and synthetic grid images. Finally, the method is applied to the case of granite rock, namely, a Bohus granite, as to directly measure the material asymmetric compression–tension and the softening response after peak tensile stress.     

The bayesian approach to the combination of forecasts: Some extensions into a Skewed environment

Where a decision-maker has to rely on expert opinions a need for a normative model to combine these forecasts appears. This can be done using Bayes' formula and by making some assumptions on the prior distribution and the distribution of the expert assessments. We extend the case to skewed distributions of these assessments. By using an Edgeworth expansion of the density function including the skewness parameter, we are able to obtain the formula to combine the forecasts in a Bayesian way.      

Integrating TTF and UTAUT2 theories to investigate the adoption of augmented reality technology in education: Perspective from a developing country

Augmented reality (AR) has gained increased recognition in varying fields, in particular educational contexts. In the wake of the Covid-19 pandemic, home-based learning becomes a reality and is already in place across the globe, and learning via augmented reality technology will help learners comprehend learning content in a more creative frame of mind than ever before. Very little research has examined the adoption behavior of augmented reality in developing country perspectives. Therefore, there is a pressing necessity to understand the dynamics of augmented reality adoption for the benefit of motivating and inspiring students to adopt this highly innovative and impactful type of technology in the learning process. Against this background, the authors proposed and tested a model based on integrating Task-Technology Fit (TTF) and UTUAT2 theories. The results reveal the positive effect of task technology fit, performance expectancy, effort expectancy, social influence, facilitating condition, and hedonic motivation on behavioral intention (BI) in the adoption process of augmented reality in educational settings, where price value is found to exert little influence on behavioral intention. This model explains 49% of the variance in intentional behavior to adopt AR technology in the educational context. The conclusions of this study will add to the literature more informative knowledge leading to increased awareness of the dynamics and behaviors of AR adoption in a developing country perspective. We present and discuss the theoretical contributions and practical implications of our findings.