Background: In Brazil, a substantial number of coronavirus disease (COVID-19) cases and deaths have been reported. It has become the second most affected country worldwide, as of June 9, 2020. Official Brazilian government sources present contradictory data on the impact of the disease; thus, it is possible that the actual number of infected individuals and deaths in Brazil is far larger than those officially reported. It is very likely that the actual spread of the disease has been underestimated. Objective: This study investigates the underreporting of cases and deaths related to COVID-19 in the most affected cities in Brazil, based on public data available from official Brazilian government internet portals, to identify the actual impact of the pandemic. Methods: We used data from historical deaths due to respiratory problems and other natural causes from two public portals: DATASUS (Department of Informatics of the Unified Healthcare System) (2010-2018) and the Brazilian Transparency Portal of Civil Registry (2019-2020). These data were used to build time-series models (modular regressions) to predict the expected mortality patterns for 2020. The forecasts were used to estimate the possible number of deaths that were incorrectly registered during the pandemic and posted on government internet portals in the most affected cities in the country. Results: Our model found a significant difference between the real and expected values. The number of deaths due to severe acute respiratory syndrome (SARS) was considerably higher in all cities, with increases between 493% and 5820%. This sudden increase may be associated with errors in reporting. An average underreporting of 40.68% (range 25.9%-62.7%) is estimated for COVID-19–related deaths. Conclusions: The significant rates of underreporting of deaths analyzed in our study demonstrate that officially released numbers are much lower than actual numbers, making it impossible for the authorities to implement a more effective pandemic response. Based on analyses carried out using different fatality rates, it can be inferred that Brazil’s epidemic is worsening, and the actual number of infectees could already be between 1 to 5.4 million.

Since December 2019, with the discovery of a new coronavirus, humanity has been exposed to a large amount of information from different media. Information is not always true and official. Known as an infodemic, false information can increase the negative effects of the pandemic by impairing data readability and disease control. The paper aims to find similar patterns of behavior of the Brazilian population during 2021 in two analyses: with vaccination data of all age groups and using the age group of 64 years or more, representing 13% of the population, using the multivariate analysis technique. Infodemic vaccination information and pandemic numbers were also used. Dendrograms were used as a cluster visualization technique. The result of the generated clusters was verified by two algorithms: the cophenetic correlation coefficient, which obtained satisfactory results above 0.7, and the elbow method, which corroborated the number of clusters found. In the result of the analysis with all age groups, more homogeneous divisions were perceived among Brazilian states, while the second analysis resulted in more heterogeneous clusters, recalling that at the start of vaccinations they could have had fear, doubts, and significant belief in the infodemic.

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.

Objective: This study aims to investigate the importance of technology in supporting neurodiversity in higher education, with the goal of promoting academic inclusion and the well-being of neurodivergent students. Theoretical Framework: This topic discusses neurodiversity as a natural variation of human cognition, not a deficit, encompassing conditions such as Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). It explores the gaps in institutional support within higher education and the potential of assistive technologies to mitigate educational barriers. Method: The methodology adopted for this research comprises a systematic literature review on the use of digital technologies for the inclusion of neurodivergent individuals in the academic context. Data collection was performed by analyzing specialized literature and indicative data on the demand for support in higher education institutions. Results and Discussion: The results obtained revealed that, despite the growing number of neurodivergent students, higher education institutions frequently lack adequate infrastructure and support. This makes assistive technologies, such as mobile applications developed with inclusive design principles and a focus on academic organization and routine management, indispensable tools for promoting autonomy and academic performance. Research Implications: The practical implications of this research point to the need for greater investment in technological development and accessibility policies in universities. Theoretically, the study reinforces the importance of inclusive and technologically mediated approaches to higher education. Originality/Value: This study contributes to the literature by highlighting the urgency of personalized technological solutions and the practical application of software engineering to meet the needs of neurodiversity in higher education. The relevance and value of this research are evidenced by its potential to transform the academic environment into a more equitable and welcoming space.

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.

BACKGROUND In Brazil, a substantial number of coronavirus disease (COVID-19) cases and deaths have been reported. It has become the second most affected country worldwide, as of June 9, 2020. Official Brazilian government sources present contradictory data on the impact of the disease; thus, it is possible that the actual number of infected individuals and deaths in Brazil is far larger than those officially reported. It is very likely that the actual spread of the disease has been underestimated. OBJECTIVE This study investigates the underreporting of cases and deaths related to COVID-19 in the most affected cities in Brazil, based on public data available from official Brazilian government internet portals, to identify the actual impact of the pandemic. METHODS We used data from historical deaths due to respiratory problems and other natural causes from two public portals: DATASUS (Department of Informatics of the Unified Healthcare System) (2010-2018) and the Brazilian Transparency Portal of Civil Registry (2019-2020). These data were used to build time-series models (modular regressions) to predict the expected mortality patterns for 2020. The forecasts were used to estimate the possible number of deaths that were incorrectly registered during the pandemic and posted on government internet portals in the most affected cities in the country. RESULTS Our model found a significant difference between the real and expected values. The number of deaths due to severe acute respiratory syndrome (SARS) was considerably higher in all cities, with increases between 493% and 5820%. This sudden increase may be associated with errors in reporting. An average underreporting of 40.68% (range 25.9%-62.7%) is estimated for COVID-19–related deaths. CONCLUSIONS The significant rates of underreporting of deaths analyzed in our study demonstrate that officially released numbers are much lower than actual numbers, making it impossible for the authorities to implement a more effective pandemic response. Based on analyses carried out using different fatality rates, it can be inferred that Brazil’s epidemic is worsening, and the actual number of infectees could already be between 1 to 5.4 million.