WhatsApp and audio misinformation during the Covid-19 pandemic

Given user choices and the commercial offerings of internet providers, WhatsApp has increasingly become established as a new standard for communication by audio, image, and text. This paper explores the role of misinformation during the Covid-19 pandemic by using content disseminated through WhatsApp, thereby making three main contributions: a discussion about the potential shift toward nontextual and nonvisual forms of misinformation;the new social role of audio, namely related to the critique of policies and political actors during the early stage of the Covid-19 pandemic;and the questioning of the First Draft News disinformation conceptual model by proposing a complementary approach that focuses only on factuality. Conclusions were drawn after conducting a content analysis of 988 units of Covid-19-related audio files, images, videos, and texts shared via WhatsApp during the early stage of the pandemic. A typology was identified to address distinct claims that focus on five different topics (society, policy and politics, health science, pandemic, and other), as well as audio messaging trending as a novel format for spreading misinformation. The results help us to contextualize and discuss a potential shift toward nontextual and nonvisual forms of misinformation, reflecting the increasing adoption of the audio format among WhatsApp users and making WhatsApp a fertile environment for the circulation and dissemination of misinformation regarding Covid-19-related themes. In a society characterized by the rapid consumption of information, the idea that content must have a degree of falsehood to mislead is an indicator of the distance between theoretical models and social reality. This indicator is important to identify true content as potential misinformation on the basis of its factuality. © 2022, El Profesional de la Informacion. All rights reserved.

Machine Learning Prediction of Hospitalization due to COVID-19 based on Self-Reported Symptoms: A study for Brazil

Predicting the need for hospitalization due to COVID-19 may help patients to seek timely treatment and assist health professionals to monitor cases and allocate resources. We investigate the use of machine learning algorithms to predict the risk of hospitalization due to COVID-19 using the patient's medical history and self-reported symptoms, regardless of the period in which they occurred. Three datasets containing information regarding 217,580 patients from three different states in Brazil have been used. Decision trees, neural networks, and support vector machines were evaluated, achieving accuracies between 79.1% to 84.7%. Our analysis shows that better performance is achieved in Brazilian states ranked more highly in terms of the official human development index (HDI), suggesting that health facilities with better infrastructure generate data that is less noisy. One of the models developed in this study has been incorporated into a mobile app that is available for public use. © 2021 IEEE

Newspaper covers as display windows in a pandemic season: Analysis of three Portuguese daily newspapers

In this article, which presents the findings of a study carried out at MediaLab CIES-Iscte, we start from the idea of COVID-19 pandemic as a media event and the mediatization as a structuring aspect of the journalistic narrative to propose three models of 'journalistic display windows' - sales, product and diversity - in which the characteristics and criteria of news adopted by each of the analyzed outlets are considered. The analysis encompassed three dimensions: The distribution of content in the newspaper's physical and hierarchical space;the marks, which can be highlighted words in the titles and headlines;and the image resources used. The survey included 90 covers of three Portuguese daily newspapers published during the first 30 days of coverage of the pandemic in Portugal. The covers were divided into three cycles: The first, between the disclosure of the first identified cases of COVID-19 in Portugal (March 3, 2020) and the declaration of a national state of alertness (March 12, 2020);the second, from the closure of schools (March 13) until the eve of the presidential decree authorizing the government to declare a state of emergency (March 18);the third, from the immediate reaction of the presidential decree (March 19) until the eve of the approval of the state of emergency in the Portuguese Parliament (April 1). The study concludes that the narratives identified on the covers of newspapers are different from each other and affected by the models of different 'journalistic display windows' (an analogy to fashion shop windows), which reflect the dichotomy between journalistic and commercial interests. In this context, we question if the model public that guides the construction of the different shop windows is only one, among several possible "robot portraits", to "sell" newspapers, or a clear socio-cultural identifier of the Portuguese press publics?. © 2021 Obercom. All rights reserved.

Rethinking post-Covid-19 school design in Brazil: Adaptation strategies for public schools PEE-12 FNDE

In 2020, the World Health Organization (WHO) declared the disease COVID-19, whose causative virus is SARS-CoV-2, a pandemic. An important measure was the closure of schools in several countries to try to reduce the contagion levels, so that students were not exposed to risk, nor their families. The question that arises within this context is: In school architecture, what are the appropriate design methods to deal with challenges during and after a pandemic? In this scope, the article aimed to propose an adaptive design scenario in the post-pandemic moment for a standard school in Brazil. The methodology was built through a literature review and multidisciplinary research, to later present strategies based on the recommendations of competent bodies and studies focused on the school architecture, design patterns for 21st-century schools, technology and security. The focus was on design challenges in the education field in the post-pandemic moment, and on the adaptation of the school built spaces for the return of activities. The results can help the school community and public agencies in making decisions to face this challenge, recreating safer, user-centered schools. © 2021 Universidade do Vale do Rio dos Sinos. All rights reserved.

Bibliometric analysis of brazilian production on COVID-19

Objective: to analyze the Brazilian scientific production on COVID-19. Method: bibliographic, descriptive, quantitative and bibliometric analysis research. The source of information was PubMed, with a period between November 17, 2019 and May 18, 2020. RSudio and VOSviewer software, bibliometrix and biblioshiny bibliometric packages, and Word Cloud Art were used for data analysis. Results: the Brazilian authors identified in the 248 articles are mostly from the medical area, working in institutions in the Southeast and Northeast regions of Brazil and maintain international collaboration, mainly with the United States, Italy and Canada. There is publication in several journals, especially those of Brazilian origin. The keywords and published articles refer to biomedical themes. Conclusion: Brazilian scientific production lacks researches on COVID-19 that reflect on the impacts of the pandemic on society, workers and health economy in Brazil. © 2020 Universidade Federal da Bahia. All rights reserved.