The COVID-19 infodemic in Brazil: trends in Google search data.

Background: Since the beginning of the new coronavirus pandemic, there has been much information about the disease and the virus has been in the spotlight, shared and commented upon on the Internet. However, much of this information is infodemics and can interfere with the advancement of the disease and that way that populations act. Thus, Brazil is a country that requires attention, as despite the fact that in almost two years of pandemic it has shown a devastating numbers of deaths and number of cases, and generates false, distorted and malicious news about the pandemic. This work intends to understand the attitudes of the Brazilian population using infodemic queries from the Google Trends search tool and social and income variables. Methods: Data from infodemic research carried out on Google Trends, between January 1, 2020 and June 30, 2021, with socioeconomic data, such as income and education, were unified in a single database: standardization and exploratory and multivalued techniques based on grouping were used in the study. Results: In the analysis of the search trend of infodemic terms, it is clear that the categories of Prevention and Beliefs should stand out in Brazil, where there is a diverse culture. It is followed by the COVID-19 Treatment category, with treatments that were not those recommended by the authorities. Income transfer programs and information on socioeconomic variables did not have much impact on infodemic surveys, but it was observed that states where President Bolsonaro has more supporters had researched more infodemic information. Conclusions: In a country as geographically large as Brazil, it is important that political authorities go to great lengths to disseminate reliable information and monitor the infodemic in the media and on the internet. It was concluded that the denial of the pandemic and the influence of political leaders influenced the search for infodemic information, contributing to a disorganization in the control of the disease and prevention measures.

An Analysis of the Deleterious Impact of the Infodemic during the COVID-19 Pandemic in Brazil: A Case Study Considering Possible Correlations with Socioeconomic Aspects of Brazilian Demography.

Due to COVID-19, a huge amount of incorrect information has been disseminated on the internet, which may interfere with the disease's advance. This study analyzes the behavior of the Brazilian population during the pandemic, employing queries of infodemic data searched on Google Trends and relating them to socioeconomic and political indicators in the country. The z-score technique was used to standardize the data; and for multivalued analysis, dendrograms and the Elbow method detected similar patterns among Brazilian states. The result was divided into three analyses. In the analysis of the research trend of infodemic terms, the themes "Prevention and Beliefs" and "Treatment" prevailed. In the exploratory analysis, socioeconomic indicators related to income and education, as well as government programs, showed no impact on infodemic searches; but the results suggest that the states that supported the Brazilian president in the 2018 election, where he obtained more than 50% of the votes, were the states that most searched for infodemic terms: a total of 46.58% more infodemic searches than in the other states. In the multivalued analysis, the socioeconomic indicators used showed similarities in the patterns, highlighting a cluster containing 77% of all Brazilian states. The study concludes that denial about the pandemic and the influence of political leadership can influence infodemic information searches, contributing to a disorganization in the control of disease control and prevention measures.

Heterogeneous wireless networks with mobile devices of multiple interfaces for simultaneous connections using Fuzzy System.

With the exponential increase in heterogeneous wireless networks today, there has been a growing interest from the academic community for issues related to handover problems. The main objective of this paper is to evaluate the quality of service and performance of a device with a dual interface that connects simultaneously to two heterogeneous networks with no competition in the exchange of packets between them. It is a proposal to solve the mitigation of handover impacts. The tool used for evaluation was the Network Simulator 2. The results showed a better use of the band in comparison to the scenario using a traditional mobile device.

[Pauliceia 2.0: collaborative mapping of the history of São Paulo, 1870-1940]. / Pauliceia 2.0: mapeamento colaborativo da história de São Paulo, 1870-1940.

This article presents new approaches for investigating the past using digital technologies. "Pauliceia 2.0: collaborative mapping of the history of São Paulo (1870-1920)" is an open-source project intended to broadly engage with the public through collaborative methodologies. This text discusses the concept, current status, and prospects of this project, and presents it as a case study to discuss the relationship between digital technologies and historical methods. The product of this journey (at least the outcome intended by the authors and the other team members listed at the end of the article) is meant to assign new meaning to the project at the juncture between digital humanities, public history, and open science.

O artigo apresenta novas abordagens para investigar o passado usando tecnologias digitais. O projeto "Pauliceia 2.0: mapeamento colaborativo da história de São Paulo (1870-1920)" é de código aberto e visa engajar o público de maneira ampla, usando metodologias colaborativas. O texto discute a concepção do projeto, seu estágio atual e suas perspectivas. Além disso, também se oferece o Pauliceia 2.0 como um estudo de caso para discutir a relação entre tecnologias digitais e métodos históricos. O resultado desse percurso, ao menos essa é a intenção dos autores listados e dos demais integrantes da equipe do projeto, nomeados ao final do artigo, almeja ressignificar o trabalho em questão na confluência entre humanidades digitais, história pública e ciência aberta.

Pauliceia 2.0: mapeamento colaborativo da história de São Paulo, 1870-1940 / Pauliceia 2.0: collaborative mapping of the history of São Paulo, 1870-1940

Resumo O artigo apresenta novas abordagens para investigar o passado usando tecnologias digitais. O projeto "Pauliceia 2.0: mapeamento colaborativo da história de São Paulo (1870-1920)" é de código aberto e visa engajar o público de maneira ampla, usando metodologias colaborativas. O texto discute a concepção do projeto, seu estágio atual e suas perspectivas. Além disso, também se oferece o Pauliceia 2.0 como um estudo de caso para discutir a relação entre tecnologias digitais e métodos históricos. O resultado desse percurso, ao menos essa é a intenção dos autores listados e dos demais integrantes da equipe do projeto, nomeados ao final do artigo, almeja ressignificar o trabalho em questão na confluência entre humanidades digitais, história pública e ciência aberta.

Abstract This article presents new approaches for investigating the past using digital technologies. "Pauliceia 2.0: collaborative mapping of the history of São Paulo (1870-1920)" is an open-source project intended to broadly engage with the public through collaborative methodologies. This text discusses the concept, current status, and prospects of this project, and presents it as a case study to discuss the relationship between digital technologies and historical methods. The product of this journey (at least the outcome intended by the authors and the other team members listed at the end of the article) is meant to assign new meaning to the project at the juncture between digital humanities, public history, and open science.

Characterizing the Impact of Social Inequality on COVID-19 Propagation in Developing Countries.

The world faces a pandemic not previously experienced in modern times. The internal mechanism of SARS-Cov-2 is not well known and there are no Pharmaceutical Interventions available. To stem the spread of the virus, measures of respiratory etiquette, social distancing and hand hygiene have been recommended. Based on these measures, some countries have already managed to control the COVID-19 propagation, although in the absence of pharmaceutical interventions, this control is not definitive. However, we have seen that social heterogeneity across populations makes the effects of COVID-19 also different. Social inequality affects the population of developing countries not only from an economic point of view. The relationship between social inequality and the health condition is not new, but it becomes even more evident in times of crisis, such as the one the world has been facing with COVID-19. How does social inequality affect the COVID-19 propagation in developing countries is the object of this study. We propose a new epidemic SEIR model based on social indicators to predict outbreak and mortality of COVID-19. The estimated number of infected and fatalities are compared with different levels of Non-Pharmaceutical Interventions. We present a case study for the Deep Brazil. The results showed that social inequality has a strong effect on the propagation of COVID-19, increasing its damage and accelerating the collapse of health infrastructure.

Concentration of Access to Information and Communication Technologies in the Municipalities of the Brazilian Legal Amazon.

This study fills demand for data on access and use of information and communication technologies (ICT) in the Brazilian legal Amazon, a region of localities with identical economic, political, and social problems. We use the 2010 Brazilian Demographic Census to compile data on urban and rural households (i) with computers and Internet access, (ii) with mobile phones, and (iii) with fixed phones. To compare the concentration of access to ICT in the municipalities of the Brazilian Amazon with other regions of Brazil, we use a concentration index to quantify the concentration of households in the following classes: with computers and Internet access, with mobile phones, with fixed phones, and no access. These data are analyzed along with municipal indicators on income, education, electricity, and population size. The results show that for urban households, the average concentration in the municipalities of the Amazon for computers and Internet access and for fixed phones is lower than in other regions of the country; meanwhile, that for no access and mobile phones is higher than in any other region. For rural households, the average concentration in the municipalities of the Amazon for computers and Internet access, mobile phones, and fixed phones is lower than in any other region of the country; meanwhile, that for no access is higher than in any other region. In addition, the study shows that education and income are determinants of inequality in accessing ICT in Brazilian municipalities and that the existence of electricity in rural households is directly associated with the ownership of ICT resources.

Social Network Analysis and Mining to Monitor and Identify Problems with Large-Scale Information and Communication Technology Interventions.

The published literature reveals several arguments concerning the strategic importance of information and communication technology (ICT) interventions for developing countries where the digital divide is a challenge. Large-scale ICT interventions can be an option for countries whose regions, both urban and rural, present a high number of digitally excluded people. Our goal was to monitor and identify problems in interventions aimed at certification for a large number of participants in different geographical regions. Our case study is the training at the Telecentros.BR, a program created in Brazil to install telecenters and certify individuals to use ICT resources. We propose an approach that applies social network analysis and mining techniques to data collected from Telecentros.BR dataset and from the socioeconomics and telecommunications infrastructure indicators of the participants' municipalities. We found that (i) the analysis of interactions in different time periods reflects the objectives of each phase of training, highlighting the increased density in the phase in which participants develop and disseminate their projects; (ii) analysis according to the roles of participants (i.e., tutors or community members) reveals that the interactions were influenced by the center (or region) to which the participant belongs (that is, a community contained mainly members of the same region and always with the presence of tutors, contradicting expectations of the training project, which aimed for intense collaboration of the participants, regardless of the geographic region); (iii) the social network of participants influences the success of the training: that is, given evidence that the degree of the community member is in the highest range, the probability of this individual concluding the training is 0.689; (iv) the North region presented the lowest probability of participant certification, whereas the Northeast, which served municipalities with similar characteristics, presented high probability of certification, associated with the highest degree in social networking platform.