Rabies in a postpandemic world: resilient reservoirs, redoubtable riposte, recurrent roadblocks, and resolute recidivism

Rabies is an ancient disease. Two centuries since Pasteur, fundamental progress occurred in virology, vaccinology, and diagnostics—and an understanding of pathobiology and epizootiology of rabies in testament to One Health—before common terminological coinage. Prevention, control, selective elimination, and even the unthinkable—occasional treatment—of this zoonosis dawned by the twenty-first century. However, in contrast to smallpox and rinderpest, eradication is a wishful misnomer applied to rabies, particularly post-COVID-19 pandemic. Reasons are minion. Polyhostality encompasses bats and mesocarnivores, but other mammals represent a diverse spectrum of potential hosts. While rabies virus is the classical member of the genus, other species of lyssaviruses also cause the disease. Some reservoirs remain cryptic. Although global, this viral encephalitis is untreatable and often ignored. As with other neglected diseases, laboratory-based surveillance falls short of the notifiable ideal, especially in lower- and middle-income countries. Calculation of actual burden defaults to a flux within broad health economic models. Competing priorities, lack of defined, long-term international donors, and shrinking local champions challenge human prophylaxis and mass dog vaccination toward targets of 2030 for even canine rabies impacts. For prevention, all licensed vaccines are delivered to the individual, whether parenteral or oral–essentially ‘one and done'. Exploiting mammalian social behaviors, future ‘spreadable vaccines' might increase the proportion of immunized hosts per unit effort. However, the release of replication-competent, genetically modified organisms selectively engineered to spread intentionally throughout a population raises significant biological, ethical, and regulatory issues in need of broader, transdisciplinary discourse. How this rather curious idea will evolve toward actual unconventional prevention, control, or elimination in the near term remains debatable. In the interim, more precise terminology and realistic expectations serve as the norm for diverse, collective constituents to maintain progress in the field.

Evaluation Model of Business Sustainability: Analysis and Consolidation of Existing Approaches: Acces la Success

The concept and practicalities of sustainable business development attract increasing interest of general public, companies, legislators, activists, academics and many others. Our understanding of what constitutes sustainability is evolving, especially nowadays when the pandemic and digitalization caused major shifts globally. In such conditions, it is no wonder that managers and business owners may face difficulties in implementation and evaluation of sustainable practices. Therefore, The objective: of the paper is to examine theoretical foundations of the concept of business sustainability and propose an up-to-date model for its appraisal. The paper is divided into two primary parts in addition to introduction and conclusion. The first part is dedicated to the examination of the terms 'stability' and 'sustainability' universally and in business environment. The second part includes description of our suggested evaluation model of economic, social and environmental sustainability perspectives using relevant indicators. Methods/Analysis: the research includes review of academic literature and empirical research on the topic of business sustainability and analytical consolidation of existing approaches to its appraisal. Findings: theoretical contribution to perception and development of the conditions of business stability and sustainability, and evaluation model including specific indicators across the three primary sustainability directions. Application/Improvements: the research is useful to general public, but is of special interest to business leaders interested in implementation of sustainable practices.

Exploratory Factorial Model of Hydric Conservation in the COVID-19 era

Scenarios of scarcity, shortages, healthiness and scarcity are proposed to which HEIs would react, but with nuances according to the capacities of the areas of knowledge such as the case of health sciences and administrative economic sciences. [...]a Modeling is a mapping of the variables indicative of a behavior based on inclusion criteria such as the consensus of the literature regarding the SDG-6 and its observation in HEIs. [...]verifiability frameworks prevail in the biological and health sciences. [...]a comparison between different sources observing the same phenomenon generates the veracity of a data [9]. The IES only covers a few disciplines that respond to the development needs of the region, as well as the projected labor demand [10]. [...]the objective of this work is to contribute with empirical evidence to the SDG indicators: scarcity, drought, depletion, sanitation, purification, quality and floods [11].

Can the New Left Deliver Change in Latin America?

The intense Latin American electoral cycle of 2020–22 coincided with deteriorating socio-economic conditions in the wake of the COVID-19 pandemic and increasing frustration with the status quo. Anti-incumbent sentiment coupled with demands for more inclusive and fair economic models prompted a pronounced shift to the left in the region, although with many different shades of ‘pink'. But an increasingly polarised and fragmented political and social environment is testing the ability of new governments to deliver change, as shown by the popular rejection of a new constitution in Chile. A more limited fiscal space is also constraining these governments' effectiveness. Nevertheless, political alignment among countries with important stakes in global climate-change mitigation and thwarting drug trafficking could produce more cohesive foreign-policy stances and increased regional leverage.

Statistical modelling of the impact of online courses in higher education on sustainable development

Purpose>The concept of sustainable development (SD) is a popular response to society's need to preserve and extend the life span of natural resources. One of the 17 goals of the SD is "education quality” (Fourth Goal of Sustainable Development [SDG-4]). Education quality is an important goal because education is a powerful force that can influence social policies and social change. The SDG-4 must be measured in different contexts, and the tools to quantify its effects require exploration. So, this study aims to propose a statistical model to measure the impact of higher education online courses on SD and a structural equation model (SEM) to find constructs or factors that help us explain a sustainability benefits rate. These proposed models integrate the three areas of sustainability: social, economic and environmental.Design/methodology/approach>A beta regression model suggests features that include the academic and economic opportunities offered by the institution, the involvement in research activities and the quality of the online courses. A structural equation modelling (SEM) analysis allowed selecting the key variables and constructs that are strongly linked to the SD.Findings>One of the key findings showed that the benefit provided by online courses in terms of SD is 62.99% higher than that of offline courses in aspects such as transportation, photocopies, printouts, books, food, clothing, enrolment fees and connectivity.Research limitations/implications>The SEM model needs large sample sizes to have consistent estimations. Thus, despite the obtained estimations in the proposed SEM model being reliable, the authors consider that a limitation of this study was the required time to collect data corresponding to the estimated sample size.Originality/value>This study proposes two novel and different ways to estimate the sustainability benefits rate focused on SDG-4, and machine learning tools are implemented to validate and gain robustness in the estimations of the beta model. Additionally, the SEM model allows us to identify new constructs associated with SDG-4.

Factors Influencing Students' Continuous Willingness to Use E-Learning Platforms in Higher Education

The COVID-19 pandemic has imposed significant challenges on education worldwide, particularly in areas with limited online teaching experience. The research design is based on constructivism learning theory and the technology acceptance model. A questionnaire was also distributed to a university of finance and economics in China. Structural equation model was used to test the influence mechanism of social media interaction on college students' willingness to use e-learning platform continuously. The positive moderating effect of online teaching context on this mechanism is further analyzed. Therefore, the use of social media in the online teaching process in higher education institutions should be encouraged, and a good online teaching context should be fostered.

Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

We present the CarbonTracker Europe High-Resolution (CTE-HR) system that estimates carbon dioxide (CO2) exchange over Europe at high resolution (0.1 × 0.2∘) and in near real time (about 2 months' latency). It includes a dynamic anthropogenic emission model, which uses easily available statistics on economic activity, energy use, and weather to generate anthropogenic emissions with dynamic time profiles at high spatial and temporal resolution (0.1×0.2∘, hourly). Hourly net ecosystem productivity (NEP) calculated by the Simple Biosphere model Version 4 (SiB4) is driven by meteorology from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) dataset. This NEP is downscaled to 0.1×0.2∘ using the high-resolution Coordination of Information on the Environment (CORINE) land-cover map and combined with the Global Fire Assimilation System (GFAS) fire emissions to create terrestrial carbon fluxes. Ocean CO2 fluxes are included in our product, based on Jena CarboScope ocean CO2 fluxes, which are downscaled using wind speed and temperature. Jointly, these flux estimates enable modeling of atmospheric CO2 mole fractions over Europe.We assess the skill of the CTE-HR CO2 fluxes (a) to reproduce observed anomalies in biospheric fluxes and atmospheric CO2 mole fractions during the 2018 European drought, (b) to capture the reduction of anthropogenic emissions due to COVID-19 lockdowns, (c) to match mole fraction observations at Integrated Carbon Observation System (ICOS) sites across Europe after atmospheric transport with the Transport Model, version 5 (TM5) and the Stochastic Time-Inverted Lagrangian Transport (STILT), driven by ECMWF-IFS, and (d) to capture the magnitude and variability of measured CO2 fluxes in the city center of Amsterdam (the Netherlands).We show that CTE-HR fluxes reproduce large-scale flux anomalies reported in previous studies for both biospheric fluxes (drought of 2018) and anthropogenic emissions (COVID-19 pandemic in 2020). After applying transport of emitted CO2, the CTE-HR fluxes have lower median root mean square errors (RMSEs) relative to mole fraction observations than fluxes from a non-informed flux estimate, in which biosphere fluxes are scaled to match the global growth rate of CO2 (poor person's inversion). RMSEs are close to those of the reanalysis with the CTE data assimilation system. This is encouraging given that CTE-HR fluxes did not profit from the weekly assimilation of CO2 observations as in CTE.We furthermore compare CO2 concentration observations at the Dutch Lutjewad coastal tower with high-resolution STILT transport to show that the high-resolution fluxes manifest variability due to different emission sectors in summer and winter. Interestingly, in periods where synoptic-scale transport variability dominates CO2 concentration variations, the CTE-HR fluxes perform similarly to low-resolution fluxes (5–10× coarsened). The remaining 10 % of the simulated CO2 mole fraction differs by >2 ppm between the low-resolution and high-resolution flux representation and is clearly associated with coherent structures ("plumes”) originating from emission hotspots such as power plants. We therefore note that the added resolution of our product will matter most for very specific locations and times when used for atmospheric CO2 modeling. Finally, in a densely populated region like the Amsterdam city center, our modeled fluxes underestimate the magnitude of measured eddy covariance fluxes but capture their substantial diurnal variations in summertime and wintertime well.We conclude that our product is a promising tool for modeling the European carbon budget at a high resolution in near real time. The fluxes are freely available from the ICOS Carbon Portal (CC-BY-4.0) to be used for near-real-time monitoring and modeling, for example, as an a priori flux product in a CO2 data assimilation system. The data are available at 10.18160/20Z1-AYJ2 .