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Objective: Our study analyzes the cost-effectiveness of the COVID-19 vaccination campaigns in Argentina, Brazil, Chile, Colombia, Costa Rica, Mexico, and Peru. Methods: Using a previously published SVEIR model, we analyzed the impact of a vaccination campaign (2021) from a national healthcare perspective. The primary outcomes were quality adjusted life years (QALYs) lost and total costs. Other outcomes included COVID-19 cases, hospitalizations, deaths, and life years. We applied a discount rate of 3% for health outcomes. We modeled a realistic vaccination campaign in each country (the realistic country-specific campaign). Additionally, we assessed a standard campaign (similar, "typical" for all countries), and an optimized campaign (similar in all countries with higher but plausible population coverage). One-way deterministic sensitivity analyses were performed. Findings: Vaccination was health improving as well as cost-saving in almost all countries and scenarios. Our analysis shows that vaccination in this group of countries prevented 573,141 deaths (508,826 standard; 685,442 optimized) and gained 5.07 million QALYs (4.53 standard; 6.03 optimized). Despite the incremental costs of vaccination campaigns, they had a total net cost saving to the health system of US$16.29 billion (US$16.47 standard; US$18.58 optimized). The realistic (base case) vaccination campaign in Chile was the only scenario, which was not cost saving, but it was still highly cost-effective with an ICER of US$22 per QALY gained. Main findings were robust in the sensitivity analyses. Interpretation: The COVID-19 vaccination campaign in seven Latin American and Caribbean countries -that comprise nearly 80% of the region- was beneficial for population health and was also cost-saving or highly cost-effective. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate and discuss the digital competence of academics at universities, to identify challenges and define recommendations for policy. This study was conducted through collaboration between the Joint Research Centre (JRC) of the European Commission and Metared of the Universia Foundation, surveying 30,407 participants who present the perceptions of their own digital competence levels. These self-reflections took place in universities in seven countries, namely Argentina, Brazil, Colombia, Chile, Peru, Mexico and Portugal, and used the Check-In tool, which consists of 22 questions based on the European Framework for the Digital Competence of Educators--or 'DigCompEdu' framework. A descriptive statistical analysis was performed, followed by a qualitative evaluation. Almost 70% of the academics have an average intermediate level of competence when the data is aggregated, with results varying in each DigCompEdu area according to the specific question asked. There is no significant difference between young and senior academics, as well as between men and women. The results present a discussion of whether the age and gender of educators and their work environment have an impact on their digital competence level, and at the same time highlights the areas in which educators perceive themselves to be most and least competent. It shows how the amount of institutional support that is offered affects the academics' perceptions of their level of digital competence. On the basis of the results, recommendations are presented for higher-education institutions, with the aim of supporting the professional development of their academics.

Formulating effective management plans for addressing the impacts of invasive non-native species (INNS) requires the definition of clear priorities and tangible targets, and the recognition of the plurality of societal values assigned to these species. These tasks require a multi-disciplinary approach and the involvement of stakeholders. Here, we describe procedures to integrate multiple sources of information to formulate management priorities, targets, and high-level actions for the management of INNS. We follow five good-practice criteria: justified, evidence-informed, actionable, quantifiable, and flexible. We used expert knowledge methods to compile 17 lists of ecological, social, and economic impacts of lodgepole pines (Pinus contorta) and American mink (Neovison vison) in Chile and Argentina, the privet (Ligustrum lucidum) in Argentina, the yellow-jacket wasp (Vespula germanica) in Chile, and grasses (Urochloa brizantha and Urochloa decumbens) in Brazil. INNS plants caused a greater number of impacts than INNS animals, although more socio-economic impacts were listed for INNS animals than for plants. These impacts were ranked according to their magnitude and level of confidence on the information used for the ranking to prioritise impacts and assign them one of four high-level actions—do nothing, monitor, research, and immediate active management. We showed that it is possible to formulate management priorities, targets, and high-level actions for a variety of INNS and with variable levels of available information. This is vital in a world where the problems caused by INNS continue to increase, and there is a parallel growth in the implementation of management plans to deal with them. [ABSTRACT FROM AUTHOR]

Fitting Susceptible-Infected-Recovered (SIR) models to incidence data is problematic when not all infected individuals are reported. Assuming an underlying SIR model with general but known distribution for the time to recovery, this paper derives the implied differential-integral equations for observed incidence data when a fixed fraction of newly infected individuals are not observed. The parameters of the resulting system of differential equations are identifiable. Using these differential equations, we develop a stochastic model for the conditional distribution of current disease incidence given the entire past history of reported cases. We estimate the model parameters using Bayesian Markov Chain Monte-Carlo sampling of the posterior distribution. We use our model to estimate the transmission rate and fraction of asymptomatic individuals for the current Coronavirus 2019 outbreak in eight American Countries: the United States of America, Brazil, Mexico, Argentina, Chile, Colombia, Peru, and Panama, from January 2020 to May 2021. Our analysis reveals that the fraction of reported cases varies across all countries. For example, the reported incidence fraction for the United States of America varies from 0.3 to 0.6, while for Brazil it varies from 0.2 to 0.4., Competing Interests: The authors have declared that no competing interests exist.