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COVID-19 pandemic, the foodservice industry has had to modify the way it offers its services. The aim of this paper is to examine the drivers of intention to use and recommendation of online food delivery (OFD) using the SOR model, to analyze the perceived risk of COVID-19 and its relationship with the perceived risk for online purchase of OFD as well as to analyze the cultural effect between Spain and India. For this purpose, an online questionnaire was developed by obtaining a sample of 422 users and structural equation modeling (PLS-SEM) was used to determine which variables had a significant influence on the adoption of the OFD. The results confirm that attitude is the main antecedent of intention to use and recommendation, in contrast to the subjective norm relationships, where it was only confirmed by recommendation. This finding demonstrates how individuals' attitude toward intention and recommendation is more favorable than influence of third parties on decisions. [ABSTRACT FROM AUTHOR]

Aims: To assess the effects of COVID‐19 pandemic on clinical variables as part of the routine clinical monitoring of patients with chronic diseases in primary care. Design: A prospective longitudinal study was conducted in primary care centres of the Andalusian Health Service. Methods: Data were recorded before the pandemic (T1), during the declaration of the state of emergency (T2) and in the transition phase (T3). The Barthel index and the Short Portable Mental Status Questionnaire (SPMSQ) were used to analyse functional and cognitive changes at the three time points. HbA1c, systolic and diastolic blood pressure, heart rate, BMI and lipid levels were assessed as clinical variables. Descriptive statistics and non‐parametric chi‐square test were used for analysis. STROBE checklist was used for the preparation of this paper. Results: A total fo148 patients with chronic conditions were included in the analysis. Data analysis revealed in T2 only significant reductions in BMI, total levels of cholesterol and HDL during the onset of the pandemic. Barthel Index, SPMSQ, blood pressure and triglycerides and LDL levels worsened in T2, and the negative effects were maintained in T3. Compared to pre‐pandemic values, HbA1c levels improved in T3, but HDL levels worsened. Conclusions: COVID‐19 has drastically disrupted several functional, cognitive and biological variables. These results may be useful in identifying clinical parameters that deserve closer attention in the case of a new health crisis. Further studies are needed to assess the potential impacts of each specific chronic condition. Impact: Cognitive and functional status, blood pressure and triglycerides and LDL levels worsen in short term, maintaining the negative effects in medium‐term. [ABSTRACT FROM AUTHOR]

This paper offers some reflections on the effectiveness of the insolvency law measures adopted in Spain during the Covid crisis and on the provision of public funding during this crisis and the repayment of the corresponding claims. The analysis shows that the insolvency measures were inherently ill-suited for achieving the policy goal of preserving businesses, and that there was a good case for the provision of public funding. However, in the Spanish case this funding came too late, and there are now significant challenges associated with restructuring these funds where they were extended by way of loan or guarantee rather than as grant. With regard to the recovery of these funds, the paper concludes that there are no good reasons to insulate the State from the restructuring of debtors' liabilities in the context of a crisis with the characteristics of the pandemic crisis. On the contrary, credit risk should also be transferred to the State—as to other creditors—, and the State will then have to assume the role of loss absorber of last resort. [ABSTRACT FROM AUTHOR]

Background: This paper describes the experience of conducting a co‐researched project with people with learning disabilities in Madrid, Spain, during the COVID pandemic and lockdown. I discuss the advantages and limitations of working online and challenges encountered while coordinating and facilitating the research. Methods: Our research project was on the impact of COVID on the lives of people with learning disabilities, which the eight co‐researchers chose. As part of my PhD, I offered my services as researcher to work together with persons with learning disabilities. Eight people took up my offer. We worked together from January 2021 to March 2022 virtually and I recorded this experience. I have written the paper, but as part of my co‐researcher agreement, I have shared my reflections and work with my co‐researchers, and we have co‐written a section to share our findings. Findings: In this paper, I discuss the advantages and limitations of working online, challenges I encountered while coordinating and facilitating the research and the work together. Remote work enabled the group to work on a biweekly basis and with members from different parts of Madrid. It saved people time and effort getting around town, yet we had to introduce express times and spaces to socialise and create a working relationship that is less natural than during in‐person interactions and breaks. During our fieldwork, we found that the pandemic had spurred the access to digital devices and programmes, but people may still be reliant on their environment, carers or supporters to facilitate it. I included a section written with my co‐researchers, in which we reflect together on the experience of working online and how we reached out to their peers during our fieldwork. We identified limitations due to our online research methodology such as lack of owning a digital device, the difficulties having access to a private space from which to connect online and the joy of meeting other people to exchange experiences. Conclusion: Human rights based participatory research can be done online. There are different ways of overcoming barriers to participation. However, there are people with no access to the internet or without digital skills that are being excluded and we must ensure that we reach out to them as well. Accessible summary: I did an online participatory research project with 8 people with learning disabilities from Spain using Zoom. Participatory research means taking part and being involved in the decisions on how the research is done.I discuss online way to make decisions, share power and control over the research, have some social connection in the group, and give information.I show that people with learning disabilities can work remotely but need more opportunities to learn digital skills. Digital skills are the skills to use technological devices, e.g., a smartphone, a tablet or a computer.Digital skills were very important during the pandemic and the lockdown, for example knowing how to find and use information and stay safe online and how to communicate with others over the internet.Participatory research projects need to support co‐researchers to learn new skills and apply them. The researchers need to be creative to make the online work engaging. [ABSTRACT FROM AUTHOR]

A global disaster, such as the recent Covid-19 pandemic, affects every aspect of our lives and there is a need to investigate these highly complex phenomena if one aims to diminish their impact in the health of the population, as well as their socio-economic stability. In this paper we present an attempt to understand the role of the governmental authorities and the response of the rest of the population facing such emergencies. We present a mathematical model that takes into account the epidemiological features of the pandemic and also the actions of people responding to it, focusing only on three aspects of the system, namely, the fear of catching this serious disease, the impact on the economic activities and the compliance of the people to the mitigating measures adopted by the authorities. We apply the model to the specific case of Spain, since there are accurate data available about these three features. We focused on tourism as an example of the economic activity, since this sector of economy is one of the most likely to be affected by the restrictions imposed by the authorities, and because it represents an important part of Spanish economy. The results of numerical calculations agree with the empirical data in such a way that we can acquire a better insight of the different processes at play in such a complex situation, and also in other different circumstances. [ABSTRACT FROM AUTHOR]

Aims and Objectives: This paper aims to examine the satisfaction and depressed mood experienced by nursing home workers during the COVID‐19 pandemic and associated variables. Specifically, to analyse the factors that may contribute to nursing home workers developing adaptive behaviours that promote satisfaction or, on the contrary, show characteristics associated with a negative mood. Background: Nursing homes have faced unprecedented pressures to provide appropriately skills to meet the demands of the coronavirus outbreak. Design: A cross‐sectional survey design using the STROBE checklist. Methods: Professionals working in nursing homes (n = 165) completed an online survey measuring sociodemographic and professional characteristics, burnout, resilience, experiential avoidance, satisfaction with life and depression. Data were collected online from April to July 2021, the time in which Spain was experiencing its fifth wave of COVID‐19. Two multiple linear regression models were performed to identify salient variables associated with depressive mood and satisfaction. Results: Resilience, personal accomplishment and satisfaction had a significant and negative relationship with depression and emotional exhaustion, depersonalisation and experiential avoidance had a positive relationship with depression. However, emotional exhaustion, depersonalisation and experiential avoidance had a negative and significant relationship with satisfaction and personal accomplishment, and resilience had a positive and significant relationship with satisfaction. In addition, it was found that accepting thoughts and emotions when they occur is beneficial for developing positive outcomes such as satisfaction. Conclusions: Experiential avoidance was an important predictor of the effects that the COVID‐19 pandemic can have on nursing home workers. Relevance to Clinical Practice: Interventions focusing on resources that represent personal strengths, such as acceptance, resilience and personal accomplishment, should be developed. No Patient or Public Contribution: The complex and unpredictable circumstances of COVID's strict confinement in the nursing home prohibited access to the centres for external personnel and family members. Contact with the professionals involved could not be made in person but exclusively through online systems. However, professionals related to the work environment have subsequently valued this research positively as it analyses 'How they felt during this complicated process'. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak was a major event that greatly impacted the economy and the health systems around the world. Understanding the behavior of the virus and being able to perform long-term and short-term future predictions of the daily new cases is a working field for machine learning methods and mathematical models. This paper compares Verhulst's, Gompertz´s, and SIR models from the point of view of their efficiency to describe the behavior of COVID-19 in Spain. These mathematical models are used to predict the future of the pandemic by first solving the corresponding inverse problems to identify the model parameters in each wave separately, using as observed data the daily cases in the past. The posterior distributions of the model parameters are then inferred via the Metropolis–Hastings algorithm, comparing the robustness of each prediction model and making different representations to visualize the results obtained concerning the posterior distribution of the model parameters and their predictions. The knowledge acquired is used to perform predictions about the evolution of both the daily number of infected cases and the total number of cases during each wave. As a main conclusion, predictive models are incomplete without a corresponding uncertainty analysis of the corresponding inverse problem. The invariance of the output (posterior prediction) with respect to the forward predictive model that is used shows that the methodology shown in this paper can be used to adopt decisions in real practice (public health). [ABSTRACT FROM AUTHOR]

The COVID-19 health crisis brought changes to people´s lives that affected them both physically and psychologically. The aim of this paper is to identify the key socio-psychological factors involved in the main changes to the mental health of the Spanish population, and to determine whether they had the same impact across genders. The survey data from the Spanish Centre for Sociological Research entitled "CIS Survey 3324 Effects and Consequences of Coronavirus IV" (specifically, question 14) were used to this end. Question variables were recoded into dummy variables for analysis of variance (ANOVA) and Exploratory Factor Analysis (EFA). The study found five key factors that have changed the mental health of the Spanish population: "being more empathic", "enjoying leisure more", "discovering new leisure activities", "being more religious or spiritual" and "being more interested in the future". All of these affected women more than men. [ABSTRACT FROM AUTHOR]

Respiratory viruses, such as COVID-19, are spread over time and space based on human-to-human interactions. Human mobility plays a key role in the propagation of the virus. Different types of sensors in smart cities are able to continuously monitor traffic-related human mobility, showing the impact of COVID-19 on traffic volumes and patterns. In a similar way, traffic volumes measured by smart traffic sensors provide a proxy variable to capture human mobility, which is expected to have an impact on new COVID-19 infections. Adding traffic data from smart city sensors to machine learning models designed to estimate upcoming COVID-19 incidence values should provide optimized results compared to models based on COVID-19 data alone. This paper proposes a novel model to extract spatio-temporal patterns in the spread of the COVID-19 virus for short-term predictions by organizing COVID-19 incidence and traffic data as interrelated temporal sequences of spatial images. The model is trained and validated with real data from the city of Madrid in Spain for 84 weeks, combining information from 4372 traffic measuring points and 143 COVID-19 PCR test centers. The results are compared with a baseline model designed for the extraction of spatio-temporal patterns from COVID-19-only sequences of images, showing that using traffic information enhances the results when forecasting a new wave of infections (MSE values are reduced by a 70% factor). The information that traffic data has on the spread of the COVID-19 virus is also analyzed, showing that traffic data alone is not sufficient for accurate COVID-19 forecasting. [ABSTRACT FROM AUTHOR]

Critical geopolitics conceives of the internal organization of the state as a relevant geopolitical subfield. In this context, this paper aims to develop a geopolitical interpretation of the covid-19 crisis management in Catalonia and Spain from March 2020 to mid-April 2020. The paper begins by providing an overview of internal geopolitics literature by Spanish geographers, focusing on the Catalonia/Spain conflict, followed by a thorough analysis of written and oral materials compiled for that purpose. Three discursive periods are identified: up until the declaration of the State of Alarm in mid-March 2020, the first two weeks with this in force, and the first half of April 2020. The paper evinces that the examined materials support contested visions about the distribution of territorial powers within Spain, while also unearthing some specificities that ultimately relate to the Catalan national question. [ABSTRACT FROM AUTHOR]

In many western countries the Covid crisis has evolved from a public health crisis toward an economic crisis. Spain was no exception. Crises are always key moments in the reconfiguration of the role of the state, as this takes on new domains and functions. Conceiving state's role as a triad helps us understanding its functioning. From the initial stage, state work has been intense in order to mitigate its effects. But the Spanish particularity is the specific articulation of state apparatuses. As in previous crises, Spain has deployed a significant activity to police the public order. The policing of public spaces was tailored to ensure the economic apparatuses remain unchallenged. A new mode of regulation has been established to allow an enhanced regime of capital accumulation through different financial instruments. Despite the frequent neglect of ideological state apparatuses, this paper exposes how relevant they are in moments of impasse to produce a new moral economy reassuring the hegemonic project of the elites. [ABSTRACT FROM AUTHOR]

This paper deals with the analysis of the persistence in the Harmonized Indices of Consumer Prices in France, Germany, Italy, and Spain. The degree of persistence is measured through fractional integration or I (d) techniques, using monthly data from January 2010 to February 2023. We first conducted the analysis with data ending in December 2019, that is, with data prior to the COVID-19 pandemic. Then, we extended the sample, first up to December 2021 and finally to February 2023. Our results show that the findings of our series are highly persistent, with values of the differencing parameter about one or higher than one in the majority of cases. In fact, mean reversion is only observed in the case of Germany with pre-pandemic data. Generally, we observed an increase in the degree of persistence of the series as a consequence of both the COVID-19 pandemic and the Russia–Ukraine war, with the only exception being Spain, where we observe a reduction in the order of integration when including 2022–2023 data. [ABSTRACT FROM AUTHOR]

Hospitals generate huge amounts of nonwoven residues daily. This paper focused on studying the evolution of nonwoven waste generated in the Francesc de Borja Hospital, Spain, over the last few years and its relation to the COVID-19 pandemic. The main objective was to identify the most impacting pieces of nonwoven equipment in the hospital and to analyze possible solutions. The carbon footprint of the nonwoven equipment was studied through a life-cycle assessment. The results showed an apparent increase in the carbon footprint in the hospital from 2020. Additionally, due to the higher annual volume, the simple nonwoven gown used primarily for patients had a higher carbon footprint over a year than the more sophisticated surgical gowns. It can be concluded that developing a local circular economy strategy for medical equipment could be the solution to avoid the enormous waste generation and the carbon footprint of nonwoven production. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic led to higher education institutions adopting alternative teaching models to continue their work while complying with health measures. Specifically, in Spain, once the lockdown period was over, universities adopted the blended learning (BL) model, which allowed for a partial return to the classroom. The BL model meant a completely new approach for students that impacted their learning experience. Using structural equation modelling (SEM), this paper explores in-depth students' experience with BL—social–behavioural, cognitive–affective, sensory and formative—and tests the impact of BL on students' satisfaction and their commitment to learning. Data were collected from a sample of 467 undergraduate students at Complutense University of Madrid (Spain) who filled out a self-administered questionnaire. The model proposed shows fit indices above the recommended thresholds, indicating an adequate model fit. Results suggest a positive influence of the different dimensions of BL experience on satisfaction. In addition, satisfaction with BL had a positive impact on students' affective commitment. Going by these results, the students' experience with BL has been positive, increasing their willingness to study. Finally, the implications of these results for higher educational institutions are discussed and future research lines suggested. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has exacerbated health inequalities worldwide, having a disproportionately harsh impact on unprivileged populations such as migrants and refugees. These populations are often more exposed to the virus, but less protected, while at the same time being at higher risk of suffering from poor living and working conditions, limited access to healthcare, and discrimination by the host society, all of which is challenging to their mental health. Empirical evidence on how the COVID-19 pandemic is affecting migrants and refugees is required to design effective actions aimed at ensuring health equity. Therefore, this paper aims to analyse how the pandemic has impacted the psychological well-being of migrants and refugees living in Spain. This study was carried out within the framework of the ApartTogether study sponsored by the World Health Organization. Data collection was carried out during March-November 2020, through an online survey completed by 241 participants (age: M = 37 years; 129 women). The results indicate that 78.7% of participants had suffered a decrease in their psychological well-being since the onset of the COVID-19 pandemic, with number of difficulties and worries experienced being the best individual predictors of this outcome. Enjoying social connections and perceiving positive treatment from the host society were positively associated with psychological well-being at a relational and community level, respectively. Based on these findings, we outline priority areas of psychosocial interventions aimed at guaranteeing the mental health of migrants and refugees in the face of the pandemic in Spain. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has been recognized as a trigger for redefining supply chains at the global level, and has created an intense debate within the academic community and among policy-makers and practitioners. Among other industries, health care has been dramatically hit by the scarcity of "medical products," specifically for personal protective equipment (PPE-like), due to supply chain disruptions coupled with dramatically increased demand. We aimed to analyze how the scarcity of PPE-like during the COVID-19 pandemic has modified the behavior of decision-makers in the PPE-like supply chain at the hospital level, and to explore what changes could be implemented to cope with future PPE-like shortages.Methods: We used an explorative approach based on semi-structured interviews with key informants in the Spanish health care industry. More specifically, we held interviews to industry experts at three hospitals in three Spanish regions to map the consequences of the COVID-19 pandemic onto the buying decision-making process.Results: Different strategies were developed by decision-makers at hospitals before, during, and after the first wave of the COVID-19 pandemic in Spain. Our paper offers two main findings: a) decision-makers changed their purchasing behavior from a cost main driver to guaranteeing the availability of supplies; b) they supported the idea of giving more "strategic autonomy" to Spain or Europe through back and nearshoring decisions.Conclusions: This paper could be of interest to health care management at the national, regional, and hospital levels, as well as for policy-makers, since it could help to establish and configure policies to support the sourcing of medical products (specifically PPE-like) to anticipate potential supply disruptions. Our paper contributes to the limited existing literature on how purchasing strategies at the decision-maker level and supply vary in the health care industry when a public health crisis appears, and what potential solutions might be for policy-makers and practitioners involved in the health care industry. [ABSTRACT FROM AUTHOR]

The paper seeks to determine the application of Astroturfing strategies on Twitter in Spain during the COVID-19 pandemic in the spring of 2020. Statistical analysis, network analysis and machine learning techniques are used to evaluate approximately 32,527 messages published from the state of alarm decree in Spain (14 March, 2020) until the end of May of the same year, associated with eight tags that address issues related to misleading content identified by two of the main factchecking projects (Maldito Bulo and Newtral). Data allow us to observe the participation of users (not bots) who play the role of influencers despite having an average profile or a profile that is far from being considered a public personality. The application of Astroturfing can be seen as a communication strategy used to position issues on social networks through the distribution, amplification and flooding of disinformation. The scenario allows us to verify the presence of a digital communication scenario that would favour a framework difficult to detect, from strategies such as the one studied, aimed at breaking the echo chamber and filter bubble of social networks, with the aim of positioning issues at the level of public opinion. [ABSTRACT FROM AUTHOR]

The COVID-19 lockdown in Spain caused abrupt changes for students following the Bachelor's Degree in Civil Engineering at the University of Burgos when face-to-face classes switched to online teaching. The recovery of face-to-face teaching after lockdown meant that classes were taught with obligatory social distancing and the use of masks. Teachers were therefore unable to interact with students closely, to perceive their facial expressions during class, or to conduct group work. The changes to civil-engineering teaching linked to the COVID-19 pandemic and the lessons that civil-engineering teachers learnt from the new teaching scenarios are studied in this paper. The reflections of teachers throughout all three stages of the pandemic (pre-pandemic and lockdown, during lockdown, and post-lockdown), and the qualitative and mixed analysis of their responses to a survey of open-ended questions contributed to the identification of six major lessons: (1) asking questions and using real-time quiz tools enliven classes and help to determine which concepts to emphasize for proper student understanding; (2) autonomous student learning can be promoted through the provision of supplementary documentation and the digitalization of solutions to classroom exercises; (3) virtual site visits and real visual examples interspersed with explanations bring concepts closer to their real applications; (4) the delivery of projects in the form of audio-recorded presentations enable their distribution, so that other students can also learn from them as well as the students who created them; (5) online videoconferences, adapted to the concepts that are addressed, facilitate fast and flexible communication with students; and (6) online continuous-assessment exams can promote better student learning patterns and final-exam preparation. Nevertheless, these six lessons were drawn from the experience of teachers at a small Spanish university where the period of solely online teaching during the COVID-19 pandemic lasted only four months. Thus, it would be interesting to analyze the experience of civil-engineering teachers at larger universities and universities that had longer periods of solely online teaching. A study of the level of implementation of the six aspects when the pandemic is declared over might also be worthwhile. [ABSTRACT FROM AUTHOR]

Mathematical models have wide applications in studying COVID-19 epidemic transmission dynamics, however, most mathematical models do not take into account the heterogeneity of susceptible populations and the non-exponential distribution infectious period. This paper attempts to investigate whether non-exponentially distributed infectious period can better characterize the transmission process in heterogeneous susceptible populations and how it impacts the control strategies. For this purpose, we establish two COVID-19 epidemic models with heterogeneous susceptible populations based on different assumptions for infectious period: the first one is an exponential distribution model (EDM), and the other one is a gamma distribution model (GDM); explicit formula of peak time of the EDM is presented via our analytical approach. By data fitting with the COVID-19 (Omicron) epidemic in Spain and Norway, it seems that Spain is more suitable for EDM while Norway is more suitable for GDM. Finally, we use EDM and GDM to evaluate the impaction of control strategies such as reduction of transmission rates, and increase of primary course rate (PCR) and booster dose rate (BDR). [ABSTRACT FROM AUTHOR]

Transparency is fundamental for the development of good governance, and even more so in times of crisis. The current crisis caused by the coronavirus has raised questions worldwide as to whether the government is acting transparently. In the case of Spain, the state of alarm decreed has suspended the terms and interrupted the deadlines for processing the procedures of public sector entities, including those affecting the Law on Transparency. This paper analyses how this suspension is affecting the actions carried out in Spain. It shows those practices that we consider to violate citizens' right to public information, and which are therefore not transparent. In Spain, there has been a setback in terms of access to public information and transparency, which has not only been visible in the management of COVID-19 data, but has also affected other areas such as public procurement. [ABSTRACT FROM AUTHOR]

Covid-19 is the first pandemic to be broadcast and photographed as it happens worldwide. However, despite the plethora of images on countless aspects of the pandemic, few media images have covered its more sensitive issues, such as the collapse of the healthcare system, the process of dying alone, or the disruption to funeral rites and mourning. Consequently, the visual narratives of the pandemic are biased. They lack images that show its more dramatic aspects. This affects not only how the public perceives and reacts to Covid-19, but also the visual evidence that will remain for historical memory in the future. With one of the world's highest case rates and most stringent states of emergency, Spain offers an interesting case study to analyse the pandemic's photographic narratives and its missing images during lockdown. This paper focuses on the presence or absence of images dealing with illness, death, dying and grief, as well as their ways of representation. It delves into the framing of particular visual narratives through an analysis of the images that appeared in Spain's leading newspapers, together with semi-structured interviews conducted with renowned photojournalists who worked on the front line to document Covid-19 during lockdown. [ABSTRACT FROM AUTHOR]

The evolution of some epidemics, such as influenza, demonstrates common patterns both in different regions and from year to year. On the contrary, epidemics such as the novel COVID-19 show quite heterogeneous dynamics and are extremely susceptible to the measures taken to mitigate their spread. In this paper, we propose empirical dynamic modeling to predict the evolution of influenza in Spain's regions. It is a non-parametric method that looks into the past for coincidences with the present to make the forecasts. Here, we extend the method to predict the evolution of other epidemics at any other starting territory and we also test this procedure with Spanish COVID-19 data. We finally build influenza and COVID-19 networks to check possible coincidences in the geographical distribution of both diseases. With this, we grasp the uniqueness of the geographical dynamics of COVID-19. [ABSTRACT FROM AUTHOR]

Spain was one of the countries in which more severe lockdown policies were imposed during the second term of 2020 to mitigate the unprecedented health crisis. The measures restricted citizens' mobility, obliging families to stay confined at homes for 99 days since 15 March 2020. The measures created a number of challenges that affect the family climate. This paper aims to empirically analyse how the family climate in Spain has been affected by COVID-19. The family climate assessment was based on an online questionnaire answered by 2034 citizens. A multi-criteria decision-making method rooted in fuzzy logic and TOPSIS, and a fuzzy clustering method, are applied to analyse the effects of the COVID-19 on the family climate. The fuzzy clustering method reveals that there are three different family climate profiles, namely (1) extreme positive, (2) extreme negative, and (3) intermediate. Our results show that some traits affect having a more or less positive family climate. The authors discuss the main contributions and the policy implications that could provide insights into future measures. [ABSTRACT FROM AUTHOR]

At the outbreak of the Covid-19 pandemic, several countries declared “states of exception,” that is, authorized legal devices that, in the face of circumstances deemed catastrophic, permit the implementation of extraordinary measures and the temporary suspension of some rights in order to restore the previous state of affairs as soon as possible. This paper offers a comparative textual analysis of the different states of exception declared in the USA, France, and Spain. I argue that these texts constitute a privileged site to explore how prevalent global political logics and mainstream discourses on illness are interwoven. Regarding the global political logics in play, I hold that these declarations constitute an instantiation of democracy’s autoimmune character; it attacks itself in order to protect itself. Regarding mainstream discourses on illness, I explore how illness is regarded as a threat to one’s self (by something seemingly other) and the notion that therapy must consist of securing the self’s triumph over anything seemingly other. This twofold analysis reveals that an aporetic dialectic between self and other—as regards politics and illness—operates in these declarations, most likely because it is, in fact, one and the same dialectic, upon which Western epistemology rests. Furthermore, I suggest that these texts reflect and promote these dominant logics, contributing to shape human relationships around the globe in a certain dangerous way. [ABSTRACT FROM AUTHOR]

The present paper deals with the numerical solution for a general form of a system of nonlinear Volterra delay integro-differential equations (VDIDEs). The main purpose of this work is to provide a current numerical method based on the use of continuous collocation Taylor polynomials for the numerical solution of nonlinear VDIDEs systems. It is shown that this method is convergent. Numerical results will be presented to prove the validity and effectiveness of this convergent algorithm. We apply models to the COVID-19 epidemic in China, Spain, and Italy and one for the Predator–Prey model in mathematical ecology. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has particularly affected the mental health of children and adolescents. In Spain, numerous studies have been carried out about the emotional impact on this population. The objective of this paper is to examine, through a systematic review, the most immediate psychological effects of the pandemic on Spanish children and adolescents and the related variables. A search was conducted, obtaining 356 articles of which 27 met the inclusion criteria. The studies reviewed address emotional problems, emotion-regulation problems, anxiety, depression, and stress in Spanish children and adolescents. An increase in emotional problems during confinement was observed. Differences were found in emotional problems, being generally more common in girls and older children and adolescents. Related variables of a family nature and referred to the pandemic, coping styles, and other psychological problems were examined. These results are relevant to design interventions that can prevent the impact of other similar situations. [ABSTRACT FROM AUTHOR]

During the recent COVID-19 pandemic, quarantine and testing policies have been of vital importance since the causative agent has been a novel virus and no vaccine was developed at the time. In this work, a new epidemiological deterministic model is proposed, analyzed, and discussed. Such a model includes quarantine periods of people with symptoms that have been tested positive, and it will trigger a trace of their close contact, who will be also tested and put in quarantine if the result is positive. Moreover, how the model parameters affect its stability is analyzed with the basic reproduction number R0. Since the COVID-19 outbreak in Spain (approximately 13/03/2020) until 25/04/2021, different restrictions have been applied. For discussion of a real case study, data have been gathered and used from the Spanish Autonomous Community of Cantabria to estimate the parameters and to see how the restrictions have affected their values. In the parameter estimation process, it has been assumed that the constructed model follows the structure of an ARX model. Finally, by considering that the gathered data are subject to certain errors, the paper discusses how to adequate the model usefulness for its use in fitting and processing data through an estimation mechanism involving the provided daily total and positive performed tests. [ABSTRACT FROM AUTHOR]

European countries struggled to fight against the second and the third waves of the COVID-19 pandemic, as the Test-Trace-Isolate (TTI) strategy widely adopted over the summer and early fall 2020 failed to contain the spread of the disease effectively. This paper sheds light on the effectiveness of such a strategy in two European countries (Spain and Italy) by analysing data from June to December 2020, collected via a large-scale online citizen survey with 95,251 and 43,393 answers in Spain and Italy, respectively. Our analysis describes several weaknesses in each of the three pillars of the TTI strategy: Test, Trace, and Isolate. We find that 40% of respondents had to wait more than 48 hours to obtain coronavirus tests results, while literature has shown that a delay of more than one day might make tracing all cases inefficient. We also identify limitations in the manual contact tracing capabilities in both countries, as only 29% of respondents in close contact with a confirmed infected individual reported having been contact traced. Moreover, our analysis shows that more than 45% of respondents report being unable to self-isolate if needed. We also analyse the mitigation strategies deployed to contain the second wave of coronavirus. We find that these interventions were particularly effective in Italy, where close contacts were reduced by more than 20% in the general population. Finally, we analyse the participants' perceptions about the coronavirus risk associated with different daily activities. We observe that they are often gender- and age-dependent, and not aligned with the actual risk identified by the literature. This finding emphasises the importance of deploying public-health communication campaigns to debunk misconceptions about SARS-CoV-2. Overall, our work illustrates the value of online citizen surveys to quickly and efficiently collect large-scale population data to support and evaluate policy decisions to combat the spread of infectious diseases, such as coronavirus. [ABSTRACT FROM AUTHOR]

The three European countries included in the northwest littoral of the Mediterranean region – Italy, France and Spain – reported their first cases of the SARS-CoV-2 coronavirus early in 2020. The subsequent epidemic strongly impacted these countries, challenging the healthcare systems efficiency, and the capacity and transparency of their public statistics structures. Because public statistics were not fully adapted to such a new health situation, the available official data could not wholly describe the epidemic correctly. This paper developed an indicator derived from the prevalence of SARS-CoV-2 aiming to describe the time and spatial dynamics of the epidemic. Although the analysis was not applied to France due to the lack of data available, the comparative analysis among Spain and Italy highlighted some similarities and certain divergences, partially attributable to the features of each country‘s national demographic patterns and the peculiarities of applied health protocols. Finally, mortality during the first wave of the epidemic has been analysed for the three countries, demonstrating higher mortality index in Spain, although the reported number of SARS-CoV-2 declared deaths does not explain a portion of this mortality excess. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has increased the unemployment issue and accelerated the digital transformation. Real-time data specific to ongoing revolution in applied economic analysis are increasingly demanded to anticipate changes in unemployment to improve decision-making. The aim of this paper is to test whether unemployment rate forecasts based on Google Trends data improve the predictions based only on macroeconomic indicators published with a longer time lag. The research has been carried out at the national level for Spain and Portugal, and the main novelty is the analysis of unemployment rate forecasts at the regional level for Spain using dynamic panel data models to implement the best policies to reduce unemployment. The keywords unemployment and job offers have been used in each language. The results obtained demonstrate the capacity of Google Trends data associated with unemployment to improve the predictions of unemployment rates in Spanish regions. Moreover, predictions based on Google Trends data at national level in Spain and Portugal are significantly more accurate than those based on autoregressive models for both countries. [ABSTRACT FROM AUTHOR]

The Covid-19 pandemic has temporarily emptied museums and drawn attention to an aspect of these cultural institutions that is often seen as secondary and subordinate to their physical presence: the digital dimension. Having been forced to close their doors, museums have sought to boost their online activity through a range of different initiatives. The most notable actions undertaken in terms of frequency are related to social networks. This situation obliges us to ask the question: have museums succeeded in achieving a meaningful online presence in their communities via social media? In terms of marketing and digital communication, content is understood as meaningful when it provides value to the audience. This value arises from the alignment of the objectives of the institution with those of the target audience; this makes it essential to understand the profile of users who comprise the communities of different digital channels. Drawing on a comparative analysis of the profiles of museum visitors and those of social media users, this paper addresses the challenges of connecting on social media with the generation known as Generation Z (a population currently between 14 and 24 years of age). To do so, it attempts to define this generation and determine how it uses social media, taking advantage of the work already carried out by Spanish museums on their social media profiles during lockdown to establish how museum institutions can make themselves more relevant to this demographic segment in Spain and beyond. [ABSTRACT FROM AUTHOR]

This paper describes three linked reactions to the COVID-19 pandemic, a mix of pragmatic change and reflection that can be seen as action research. Our case studies, stories, come from the UK, Spain and Ecuador and describe three different but overlapping actions all focused on making available or using online questionnaires and drawing on counselling, psychology and psychotherapy ideas and practices and technological solutions to help address the COVID-19 crisis and the lockdown. We believe these experiences have implications for our professions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has become a global phenomenon with powerful effects. The deaths and suffering, and the measures taken to mitigate the propagation, are changing the way we relate, work, and enjoy ourselves. The psychological impact on individuals and groups can only be partially known yet, but deserves examination. We focus on the specific place where we live: the city of Bilbao in northern Spain. The response of its people could represent an example of the COVID-19 experience and its effects, and some aspects might be generalized elsewhere. This paper reflects on the influence of the pandemic on some relevant social dimensions: personal and public spaces, affected by estrangement, time, subject to a slower pace, which pushes us into a different contact with our internal world. It also addresses a social vision of the pandemic as a punishment for our errors in the socio-economic and environmental fields, the role of uncertainty that generates strong defensive movements at the group level, and the expressions of personal and group courage throughout the process. The intensity of the pandemic in Bilbao and many parts of the world still prevents reflection on the long-term effects, which will have to be investigated in the future. [ABSTRACT FROM AUTHOR]

COVID-19 pandemic led to significant changes in domestic water use in many cities. One important question is whether and to what extent the pandemic stressed the resilience of the water supply system. Another question examined in the paper is whether changes in water use during confinement differed according to the sociospatial configuration of cities. We examine these questions in the context of a medium size city of Northern Spain characterized by a mix of residential land uses, and internal variations in education, age composition, and income, producing step gradients in water use. First, we select and analyze influencing factors in domestic water consumption. Second, using statistical regression tests, we assess whether or not and to what extent the same factors influenced consumption during the COVID 19 lockdown. Results indicate that COVID-19 related confinement increased work and study from home and reinforced WASH habits, leading to more water consumption. However, this increase was larger in medium and low-income neighborhoods than in high-income neighborhoods, showing the relevance of sociodemographic factors but also of other variables more relevant for outdoor water use such as precipitation. Despite this rise in consumption, the water supply system was able to withstand the shock caused by confinement showing a robust resilience both in physical and in social terms. However, more challenging scenarios such as the coincidence of a pandemic with a severe drought should be taken into account in future resilience development. • Sociodemographic and urban factors played an important role in explaining domestic water consumption patterns during COVID-19 lockdowns. • Households in multifamily buildings or apartment blocks with medium-low incomes and significant presence of young people recorded the largest relative increases of water consumption during these lockdowns. • Weather conditions are key in domestic water consumption during the COVID 19 lockdown especially in areas with a large presence of single houses. • The water supply system was resilient and could withstand the increase in consumption caused by confinement as well as provide for financial assistance to vulnerable households. Policies should take into account the possible coincidence in time of unexpected phenomena such as COVID-19 with droughts already stressing urban resilience. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and lockdown in Spain during Spring 2020 resulted in a ban on most uses of public space, producing a social redefinition of not only public spaces, but also private spaces such as homes. This paper examines the discourses related to balconies that appeared at this time on Twitter (X), an intermediate microspace and hybrid between the public and private. The study uses data from tweets posted in Spain during the strictest phase of the lockdown (from 15 March to 1 May 2020). Based on a descriptive analytical approach – both quantitative and textual – the study applies text content analysis and natural language processing to identify and analyse the main topics of conversation related to the use of balconies. The study brought to light two primary and complementary results. Firstly, the balcony during the pandemic became a revitalized space in an exceptional situation, partially adapting to the most common practices characteristic of public space and thus reaffirming the importance of the existence of public spaces for citizen encounters. Secondly, the various uses of balconies received different types of attention and generated stronger or weaker interactions on social networks, demonstrating the complexity and diversity of relationships with public spaces. • The impossibility of using public spaces multiplied the importance of balconies • Using Twitter data, we studied the use of balconies in Spain in the spring of 2020 • Balconies became a public microspace through their use towards the outside • Technology did not isolate citizens but was key for the promotion of the new uses • We found important differences by use in attachments to the tweets and interactions [ABSTRACT FROM AUTHOR]

Online learning and training continue gaining momentum worldwide resulting in the reduction of the traditional form of face-to-face education with its temporal and spatial limitations. Online education improves access to education and training, as witnessed during the Covid-19 pandemic. This article focuses on online education adoption in Spain. A representative survey on ICT use in households conducted annually by the Spanish National Institute of Statistics is used to construct a panel database for the years 2008–2020. The first objective is to provide an econometric model for adopting online education using this panel data. Next is to measure the effects of relevant observable individual socioeconomic variables on adoption. A Heckman selection model allows for estimating the impact of gender, age, education, digital skills, habitat, and income. The article also measures the effects of Covid-19 in 2020 on different population groups. The drivers and impediments have the expected signs and plausible sizes. The paper concludes with policy recommendations and suggestions for further research. • Adopotion of online education, both before and during the Covid-19 pandemic. • An economic model of online adoption. The main determinants are gender, age, education, digital skills, habitat, and income. • An acceleratio n of nine times in the adoption is apparent after the first wave of Covid-19 compared with the period 200819. • The policy recommendations are related to improving digital skills, which are limited compared with other European countries. [ABSTRACT FROM AUTHOR]

The objective of this paper is to link the literatures on economic complexity, income equality and environmental quality within the context of the Environmental Kuznets Trilemma. Within this framework, it is possible to measure the presence of an impossible trinity of irreconcilable objectives: economic growth, equal distribution of income and environmental sustainability. Our paper revisits this trilemma by focusing on economic complexity (EC) indexes instead of direct measures of economic growth, and applies this analysis to the sub-national level. We link these three cutting-edge topics by means of novel datasets computed for the Spanish economy at the province level (NUTS-3) for a long period (2002–16). Our paper also sheds new light on the spatial patterns of the trilemma's three dimensions and their implications for the future of Spain's more peripheral regions. ⁃ This paper links the literatures on economic complexity, income equality and environmental quality within the context of the Environmental Kuznets Trilemma. ⁃ Our paper focuses on economic complexity indexes instead of direct measures of economic growth, and applies this analysis to the sub-national level, using novel datasets for the Spanish provinces (NUTS-3) for a long period (2002–16). ⁃ Our paper shows a clear tension between economic growth and complexity versus income equality and environmental quality. The econometric analysis verifies the classic trilemma (equality-sustainability-growth), but also of our new version: equality-sustainability-complexity. ⁃ The paper also tests the presence of a quadrilemma, discussing the role to which a province's level of complexity tends to play in the tensions between growth, inequality, and sustainability. The results open new avenues for the smart specialization of regions within countries, something specially relevant in the COVID-19 crisis. [ABSTRACT FROM AUTHOR]

In this paper, we decompose a family of energy poverty indices into incidence, intensity and inequality among the poor. When continuous variables such as income are used, it is well known that any income poverty index should take into account these three poverty terms. Therefore, every energy poverty measure should also take into account these three. We propose to follow an analogous idea to decompose a family of energy poverty indices in these three components. The novelty of this proposal is that the multidimensional family of energy poverty measures is applied to multiple dichotomous variables and not to a single continuous variable, when, to date, no decomposition has been proposed based on these types of variables. We then extend this decomposition to a further decomposition by population subgroups. In this way, we will be able to know more precisely the origins of energy poverty in order to implement more specific anti-poverty policies targeting the incidence, intensity or/and inequality among the energy poor. Finally, we apply the proposed decomposition to Spain in 2020 as regards certain individual and household characteristics, so as to identify the individuals most likely to suffer from energy poverty in the first year of the Covid-19 pandemic. • An decomposable index to measure energy poverty. • Poverty Decomposition in Incidence, Intensity and Inequality. • Sources of energy poverty increase in Spain on 2020. [ABSTRACT FROM AUTHOR]

Many types of research have been carried out with the aim of combating the COVID-19 pandemic since the first outbreak was detected in Wuhan, China. Anticipating the evolution of an outbreak helps to devise suitable economic, social and health care strategies to mitigate the effects of the virus. For this reason, predicting the SARS-CoV-2 transmission rate has become one of the most important and challenging problems of the past months. In this paper, we apply a two-stage mid and long-term forecasting framework to the epidemic situation in eight districts of Andalusia, Spain. First, an analytical procedure is performed iteratively to fit polynomial curves to the cumulative curve of contagions. Then, the extracted information is used for estimating the parameters and structure of an evolutionary artificial neural network with hybrid architectures (i.e., with different basis functions for the hidden nodes) while considering single and simultaneous time horizon estimations. The results obtained demonstrate that including polynomial information extracted during the training stage significantly improves the mid- and long-term estimations in seven of the eight considered districts. The increase in average accuracy (for the joint mid- and long-term horizon forecasts) is 37.61% and 35.53% when considering the single and simultaneous forecast approaches, respectively. • Estimated polynomial model coefficients serve as COVID19 contagion rate descriptors. • EANNs are used to build valid predictors for different pandemic stages. • Considering curve polynomial descriptors significantly improve the model performances. • Simultaneous Multi-Task EANN forecast perform better in Málaga with simpler models. [ABSTRACT FROM AUTHOR]

The Spanish real estate and its 'sea and sun' tourism model, were profoundly disrupted during the Great Recession of 2008–2014 As a result, hedge funds and their speculative operations have favoured an intense process of urban touristification in the largest Spanish cities, especially over the past ten years. The aim of this paper is to examine how the COVID-19 crisis has triggered shifts in the supply of short-term rentals and the type of demand of such rentals. By taking into account such changes, we will address the potential changes that the current pandemic scenario might bring between the 'classical' real estate market and short-term rentals in Spain. • Its high dependence on tourism makes Spain the best case study to analyze pandemic-related impacts on urban tourism • The exhaustion of the "Sun & Beach" tourism model had been replaced by the touristification of consolidated urban areas • Short-term rental and residential markets have redefined their complex relationship in new, uncertain directions • Platforms are the new frontier of capital accumulation in cities, anda powerful new mechanism to extract rents from housing [ABSTRACT FROM AUTHOR]

• Sleep disorders and anxiety were the most common symptoms. • Most of the participants did not believe they were being adequately supported and informed by their superiors or the institution. • Emotional expression and social support were more frequent among women, and social support seeking was associated with ages 35–50 and was prevalent in Medical, Psychology and Nursing specialization trainees. • The distribution of coping strategies was heterogeneous, which indicates the lack of a proper training in coping with stressful situations. The aim of this paper is to analyze the main coping strategies used by frontline teams during the first days of the COVID pandemic confinement in Spain. This information could be necessary in order to carry out training programs that allow a better handling of future emergency situations, as well as acting more effectively and with less negative emotional impact. A questionnaire was used to identify different psychological profiles for coping, and in turn, other relevant variables were analyzed. The most used strategies by health professionals were problem solving, desiderative thinking and social support. Emotional expression and social support were used more by women. Significantly different behaviors were found in desiderative thinking (lower in people of 35–50 years old, and social support, higher in people 35 years old). The symptoms most commonly experienced by medical personnel were: sleep disorders, anxiety, tension, depressive symptoms, gastrointestinal symptoms and general somatic muscular symptoms. A relationship could be determined between the age/gender of the workers and the participants' overall assessment of their ability to cope with the COVID-19 stress situation they had experienced (men 50 years old and women between 35 and 50 years old, who felt able or very able to cope with the stress caused by the health emergency. However, women <35 years old and >50 years old believed they were able to cope poorly with the circumstances. The advantage of specific training plans in order to help with some stress symptoms could be suggested, aimed at the acquisition of tools based on problem solving, and emotional management in stressful and emergency situations. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel genetic algorithm-based seasonal fractional grey model is proposed. • Monthly electricity generation is forecasted since the Covid-19 lockdown started. • Seasonal grey and machine learning models are used for forecasting. • The selected countries are France, Germany, Spain, Turkey, and the UK. • The share of renewables in total electricity generation is forecasted. Balances in the energy sector have changed since the implementation of the Covid-19 pandemic lockdown in Europe. This paper analyses how the lockdown affected electricity generation in European countries and how it will reshape future energy generation. Monthly electricity generation from total renewables and non-renewables in France, Germany, Spain, Turkey, and the UK from January 2017 to September 2020 were evaluated and compared. Four seasonal grey prediction models and three machine learning methods were used for forecasting; the quarterly results are presented to the end of 2021. Additionally, the share of electricity generation from renewables in total electricity generation from 2017 to 2021 for the selected countries was compared. Electricity generation from total non-renewables in the second quarter of 2020 for France, Germany, Spain, and the UK decreased by 21%–25% compared to the same period of 2019; the decline in Turkey was approximately 11%. Additionally, electricity generation from non-renewables in the third quarter of 2020 for all countries, except Turkey, decreased compared to the same period of the previous year. All grey prediction models and support vector machine method forecast that the share of renewables in total electricity generation will increase continuously in France, Germany, Spain, and the UK to the end of 2021. The forecasting methods provided by this study open new avenues for research on the impact of the Covid-19 pandemic on the future of the energy sector. [ABSTRACT FROM AUTHOR]

• Harmonization and quality control of originally heterogenous observational databases. • Large-scale application of machine learning methods in a distributed data network. • Transparent use of open-source software tools and publicly shared analytical code. As a response to the ongoing COVID-19 pandemic, several prediction models in the existing literature were rapidly developed, with the aim of providing evidence-based guidance. However, none of these COVID-19 prediction models have been found to be reliable. Models are commonly assessed to have a risk of bias, often due to insufficient reporting, use of non-representative data, and lack of large-scale external validation. In this paper, we present the Observational Health Data Sciences and Informatics (OHDSI) analytics pipeline for patient-level prediction modeling as a standardized approach for rapid yet reliable development and validation of prediction models. We demonstrate how our analytics pipeline and open-source software tools can be used to answer important prediction questions while limiting potential causes of bias (e.g. , by validating phenotypes, specifying the target population, performing large-scale external validation, and publicly providing all analytical source code). We show step-by-step how to implement the analytics pipeline for the question: 'In patients hospitalized with COVID-19, what is the risk of death 0 to 30 days after hospitalization?'. We develop models using six different machine learning methods in a USA claims database containing over 20,000 COVID-19 hospitalizations and externally validate the models using data containing over 45,000 COVID-19 hospitalizations from South Korea, Spain, and the USA. Our open-source software tools enabled us to efficiently go end-to-end from problem design to reliable Model Development and evaluation. When predicting death in patients hospitalized with COVID-19, AdaBoost, random forest, gradient boosting machine, and decision tree yielded similar or lower internal and external validation discrimination performance compared to L1-regularized logistic regression, whereas the MLP neural network consistently resulted in lower discrimination. L1-regularized logistic regression models were well calibrated. Our results show that following the OHDSI analytics pipeline for patient-level prediction modelling can enable the rapid development towards reliable prediction models. The OHDSI software tools and pipeline are open source and available to researchers from all around the world. [ABSTRACT FROM AUTHOR]