COVID-19 and Sustainable Development Goals (SDGs): Scenario analysis through fuzzy cognitive map modeling

Methodological approaches on synergies and trade-offs within the 2030 Agenda

The world is lagging in achieving the 2030 Agenda's 17 Sustainable Development Goals (SDGs), emphasizing social, economic, and environmental dimensions. Meeting one target may either help or hinder meeting another, but the high number of potential interactions complicates the evaluation of synergies and trade-offs. Here, we focus on the water-energy-food nexus to assess how the knowledge of SDG interlinkages has been operationalized to inform policymaking. Specifically, we review the effectiveness of research methodologies, such as correlation analysis, network analysis, meta-analysis and literature reviews, expert-based assessments, and integrated assessment models in characterizing SDG interlinkages. Most studies indicate that synergies are more prevalent than trade-offs, but they have seldom analyzed whether such infrequent trade-offs might nevertheless have a greater impact on sustainable development. Further, existing methods do not always reveal the directionality and strength of SDG interactions or consider projections of future interlinkages such as transboundary and intergenerational spillovers. In this context, it may be worth revisiting earlier definitions of sustainable development that prioritized intergenerational aspects and future needs.

Long COVID science, research and policy

Long COVID represents the constellation of post-acute and long-term health effects caused by SARS-CoV-2 infection; it is a complex, multisystem disorder that can affect nearly every organ system and can be severely disabling. The cumulative global incidence of long COVID is around 400 million individuals, which is estimated to have an annual economic impact of approximately $1 trillion-equivalent to about 1% of the global economy. Several mechanistic pathways are implicated in long COVID, including viral persistence, immune dysregulation, mitochondrial dysfunction, complement dysregulation, endothelial inflammation and microbiome dysbiosis. Long COVID can have devastating impacts on individual lives and, due to its complexity and prevalence, it also has major ramifications for health systems and economies, even threatening progress toward achieving the Sustainable Development Goals. Addressing the challenge of long COVID requires an ambitious and coordinated-but so far absent-global research and policy response strategy. In this interdisciplinary review, we provide a synthesis of the state of scientific evidence on long COVID, assess the impacts of long COVID on human health, health systems, the economy and global health metrics, and provide a forward-looking research and policy roadmap.

Challenges of health and well-being in the world according to SDG indicators

This study reviews the current state of the good health and well-being indicators included in the Sustainable Development Goals (SDG), identifying the most significant challenges faced by countries in the world and in the Americas region. The HJ-Biplot multivariate technique is used to represent variances and covariances between 16 SDG 3 indicators, reported as of 2022, based on data from 176 countries, including 31 countries of the American continent. The findings show that indicators such as life expectancy at birth, universal health coverage and satisfied demand for family planning are key characteristics of developed countries. In contrast, developing countries still face significant challenges in terms of promoting maternal health, the well-being of children and the control of communicable and chronic diseases. For this reason, in the framework of the 2030 Agenda, it is necessary to continue working on public policy actions that enable making progress in the implementation of programs to improve the health and well-being of the population, especially in lower-income countries.

Fuzzy Cognitive Map Applications in Medicine over the Last Two Decades: A Review Study

Fuzzy Cognitive Maps (FCMs) have become an invaluable tool for healthcare providers because they can capture intricate associations among variables and generate precise predictions. FCMs have demonstrated their utility in diverse medical applications, from disease diagnosis to treatment planning and prognosis prediction. Their ability to model complex relationships between symptoms, biomarkers, risk factors, and treatments has enabled healthcare providers to make informed decisions, leading to better patient outcomes. This review article provides a thorough synopsis of using FCMs within the medical domain. A systematic examination of pertinent literature spanning the last two decades forms the basis of this overview, specifically delineating the diverse applications of FCMs in medical realms, including decision-making, diagnosis, prognosis, treatment optimisation, risk assessment, and pharmacovigilance. The limitations inherent in FCMs are also scrutinised, and avenues for potential future research and application are explored.

Study on the spatial decomposition of the infection probability of COVID-19

In the course of our observations of the transmission of COVID-19 around the world, we perceived substantial concern about imported cases versus cases of local transmission. This study, therefore, tries to isolate cases due to local transmission (also called community spread) from those due to externally introduced COVID-19 infection, which can be key to understanding the spread pattern of the pandemic. In particular, we offer a probabilistic perspective to estimate the scale of the outbreak at the epicenter of the COVID-19 epidemic with an environmental focus. First, this study proposes a novel explanation of the probability of COVID-19 cases in the local population of the target city, in which the chain of probability is based on the assumption of independent distribution. Then it conducts a spatial statistical analysis on the spread of COVID-19, using two model specifications to identify the spatial dependence, more commonly known as the spillover effect. The results are found to have strong spatial dependence. Finally, it confirms the significance of residential waste in the transmission of COVID-19, which indicates that the fight against COVID-19 requires us to pay close attention to environmental factors. The method shown in this study is critical and has high practical value, because it can be easily applied elsewhere and to other future pandemics.

COVID-19 and sustainable development goals: A bibliometric analysis and SWOT analysis in Malaysian context

The COVID-19 crisis has been a core threat to the lives of billions of individuals over the world. The COVID-19 crisis has influenced governments' aims to meet UN Sustainable Development Goals (SDGs); leading to exceptional conditions of fragility, poverty, job loss, and hunger all over the world. This study aims to investigate the current studies that concentrate on the COVID-19 crisis and its implications on SDGs using a bibliometric analysis approach. The study also deployed the Strengths, Weaknesses, Opportunities, and Threats (SWOT) approach to perform a systematic analysis of the SDGs, with an emphasis on the COVID-19 crisis impact on Malaysia. The results of the study indicated the unprecedented obstacles faced by countries to meet the UN's SDGs in terms of implementation, coordination, trade-off decisions, and regional issues. The study also stressed the impact of COVID-19 on the implementation of the SDGs focusing on the income, education, and health aspects. The outcomes highlighted the emerging opportunities of the crisis that include an improvement in the health sector, the adoption of online modes in education, the swift digital transformation, and the global focus on environmental issues. Our study demonstrated that, in the post-crisis time, the ratio of citizens in poverty could grow up more than the current national stated values. We stressed the need to design an international agreement to reconsider the implementation of SDGs, among which, are strategic schemes to identify vital and appropriate policies.

Does COVID-19 impact on financial markets of China-evidence from during and pre-COVID-19 outbreak

During the outbreak of COVID-19, concern significantly influenced our financial system. This new paper's primary assessment of the COVID-19 virus affects the world's major economies and financial markets. This paper utilizes an event analysis approach and a data model to investigate the influence of COVID-19 on the financial market system from three viewpoints: (1) supply chain finance and titles, (2) processing system, and (3) the financial system of the organization. According to data analysis, the model built in this work may properly depict the influence of COVID-19 on the financial market system. The results indicated that the low age coefficient (p-value (p 0.05)) and a higher blocking condition (p-value (p > 0.05)) impact city tourism market system with p-values of 0.002 and 0.004, respectively. Other results show the impact of the Chinese New Year vacations. Since then, the government has slowly stabilized its recovery, with many measures taken to limit the epidemic in February and a series of regulatory measures enacted to stabilize financial markets. These findings show a small but statistically significant degree of stabilization in international financial markets in response to stay-at-home government policies and social distancing measures, which is encouraging for political actors concerned about economic performance during the coronavirus 2019 pandemic response.

Assessment of COVID-19 impact on sustainable development goals indicators in Egypt using fuzzy analytic hierarchy process

COVID-19 significantly influences the Sustainable Development Goals (SDGs) in both developed and developing countries. Within the 2030 agenda, Egypt is likely to face enormous negative ramifications from the virus spread. As a result, efficient control of the adverse repercussions of this virus is critical to achieving this objective. This research assesses indicators of specific SDGs in reflecting COVID-19 impact by conducting several questionnaire surveys among experts in Egypt. The scope of this research is limited to addressing poverty alleviation (SDG1), hunger abatement (SDG2), healthcare promotion (SDG3), sustainable economic growth (SDG8), and climate change mitigation (SDG13). The indicators are prioritized using the relative importance index, weighted aggregated sum product assessment technique for order preference by similarity to an ideal solution, and fuzzy analytic hierarchy process. The rankings are finally aggregated using an approach based on the half-quadratic theory. The results reveal that the most significant indicators in reflecting the COVID-19 impact are the share of population living below the international poverty line, undernourishment prevalence, official health sector support, annual gross domestic product per capita growth rate, and number of disaster deaths for SDG1, SDG2, SDG3, SDG8, and SDG13, respectively. Recognizing and ranking the indicators could help decision-makers understand the behavior of SDG indicators in light of COVID-19. The research findings could assist policymakers in making informed decisions to reduce the pandemic effects and sustain achieving SDGs by 2030.

Employing Eye Tracking to Study Visual Attention to Live Streaming: A Case Study of Facebook Live

In recent years, the COVID-19 pandemic has led to the development of a new business model, “Live Streaming + Ecommerce”, which is a new method for commercial sales that shares the goal of sustainable economic growth (SDG 8). As information technology finds its way into the digital lives of internet users, the real-time and interactive nature of live streaming has overturned the traditional entertainment experience of audio and video content, moving towards a more nuanced division of labor with multiple applications. This study used a portable eye tracker to collect eye movement information from participants watching Facebook Live, with 31 participants who had experience using the live streaming platform. The four eye movement indicators, namely, latency of first fixation (LFF), duration of first fixation (DFF), total fixation durations (TFD), and the number of fixations (NOF), were used to analyze the distribution of the visual attention in each region of interest (ROI) and explore the study questions based on the ROIs. The findings of this study were as follows: (1) the fixation order of the ROIs in the live ecommerce platform differed between participants of different sexes; (2) the DFF of the ROIs in the live ecommerce platform differed among participants of different sexes; and (3) regarding the ROIs of participants on the live ecommerce platform, participants of different sexes showed the same attention to the live products according to the TFD and NOF eye movement indicators. This study explored the visual search behaviors of existing consumers watching live ecommerce and provides the results as a reference for operators and researchers of live streaming platforms.

Biofuel supply chain management in the circular economy transition: An inclusive knowledge map of the field

Investment in biofuels, as sustainable alternatives for fossil fuels, has gained momentum over the last decade due to the global environmental and health concerns regarding fossil fuel consumption. Hence, effective management of biofuel supply chain (BSC) components, including biomass feedstock production, biomass logistics, biofuel production in biorefineries, and biofuel distribution to consumers, is crucial in transitioning towards a low-carbon and circular economy (CE). The present study aims to render an inclusive knowledge map of the BSC-related scientific production. In this vein, a systematic review, supported by a keywords co-occurrence analysis and qualitative content analysis, was carried out on a total of 1,975 peer-reviewed journal articles in the target literature. The analysis revealed four major research hotspots in the BSC literature, namely (1) biomass-to-biofuel supply chain design and planning, (2) environmental impacts of biofuel production, (3) biomass to bioenergy, and (4) techno-economic analysis of biofuel production. Besides, the findings showed that the following subject areas of research in the BSC research community have recently attracted more attention: (i) global warming and climate change mitigation, (ii) development of the third-generation biofuels produced from algal biomass, which has recently gained momentum in the CE debate, and (iii) government incentives, pricing, and subsidizing policies. The provided insights shed light on the understanding of researchers, stakeholders, and policy-makers involved in the sustainable energy sector by outlining the main research backgrounds, developments, and tendencies within the BSC arena. Looking at the provided knowledge map, potential research directions in BSCs towards implementing the CE model, including (i) integrative policy convergence at macro, meso, and micro levels, and (ii) industrializing algae-based biofuel production towards the CE transition, were proposed.

Study on the mechanism of public attention to a major event: The outbreak of COVID-19 in China

This study focuses on public attention to major events, which has become an important topic in the context of the COVID-19 pandemic. In the background of the global transmission of COVID-19, this study discusses the relationship between information shock and sustainable development, which is rarely mentioned before. By developing an appropriate theoretical model, we discuss how the level of public attention changes over time and with the severity of events. Then we use data on the daily clicks on a popular Chinese medical website to indicate public attention to the pandemic. Our analysis shows that, in the first half of 2020, the level of public attention is closely related to the scale of domestic transmission. The marginal effect of the domestic cases in the first wave is 1% to 0.217%. After the pandemic was largely under control in China, people still followed the latest news, but the scale of public attention to regional transmission diminished. And when the pandemic quickly and severely worsened in other countries, people in China were very attentive, that is, public attention increased. The time interval of social reaction we calculate is fairly stable, with a value of between 0 and 5 most of the time. The average time interval from January 2020 to May 2021 ranges from 1.76 days to 1.94 days, depending on the choice of models and parameters. This study suggests that raising public participation in dealing with the crisis over the long term would be enhanced in China by media encouragement to pay more attention to small-scale regional transmission and the course of the pandemic in other countries. The goal of sustainable development requires dealing with health and economic crises much better in the long term. Thus, the model and method used in the paper serve to enhance general interest.

Suitability Evaluation of Different Measured Variables to Assess the Occupancy Patterns of a Building: Analysis of a Classroom of a School in Madrid during the COVID-19 Pandemic

Building occupancy is one of the relevant variables to understand the energy performance of buildings and to reduce the current gap between simulation-based and actual energy performance. In this study, the occupancy of a classroom in an educational center monitored over a full year was experimentally assessed. The classroom had different occupancy levels during the school year, with a theoretical minimum of eleven students, and no occupancy during vacations and weekends. Different variables such as indoor air temperature, relative humidity, CO2 concentration, overall electrical energy consumption of the educational center, electrical energy consumption of the building in which the monitored classroom is located, and heating energy consumption were recorded. We analyzed which of these variables were possible indicators of classroom occupancy, using the school timetable as a theoretical reference value for the validation of the results. Based on previous studies, one-hour moving averages are used to better identify the occupancy patterns by smoothing the fluctuations that are not a consequence of a change in the classroom occupancy. Histograms of each variable are used to identify the variable ranges associated within the occupancy: occupied or empty. The concentration of CO2 and electric measurements, identified in previous works as suitable to assess the occupancy patterns of rooms like offices with lower levels of occupancy, are recognized as potential occupancy indicators. It is therefore concluded that a higher level of space occupancy does not affect the result, and the same variables are identified as potential occupancy indicators.

Green Synthesis of Nanoparticles by Mushrooms: A Crucial Dimension for Sustainable Soil Management

Soil is the main component in the agroecosystem besides water, microbial communities, and cultivated plants. Several problems face soil, including soil pollution, erosion, salinization, and degradation on a global level. Many approaches have been applied to overcome these issues, such as phyto-, bio-, and nanoremediation through different soil management tools. Mushrooms can play a vital role in the soil through bio-nanoremediation, especially under the biological synthesis of nanoparticles, which could be used in the bioremediation process. This review focuses on the green synthesis of nanoparticles using mushrooms and the potential of bio-nanoremediation for polluted soils. The distinguished roles of mushrooms of soil improvement are considered a crucial dimension for sustainable soil management, which may include controlling soil erosion, improving soil aggregates, increasing soil organic matter content, enhancing the bioavailability of soil nutrients, and resorting to damaged and/or polluted soils. The field of bio-nanoremediation using mushrooms still requires further investigation, particularly regarding the sustainable management of soils.