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The pandemic caused millions of deaths around the world and forced governments to take drastic measures to reduce the spread of Coronavirus. Understanding the impact of social distancing measures on urban mobility and the number of COVID-19 cases allows governments to change public policies according to the evolution of the pandemic and plan ahead. Given the increasing rates of vaccination worldwide, immunization data may also represent an important predictor of COVID-19 cases. This study investigates the impact of urban mobility and vaccination upon COVID-19 cases in Belo Horizonte, Brazil using Prophet and ARIMA models to predict future outcomes. The developed models generated projections fairly close to real numbers, and some inferences were drawn through experimentation. Brazil became the epicenter of the COVID-19 epidemic shortly after the first case was officially registered on February 25th, 2020. In response, several municipalities adopted lockdown (total or partial) measures to minimize the risk of new infections. Here, we propose prediction models which take into account mobility and vaccination data to predict new COVID-19 cases. [ABSTRACT FROM AUTHOR]

In the last 40 years, Latin America countries, including Brazil, have suffered from the emergence and reemergence of arboviruses, first Dengue (DENV) and recently Zika (ZIKV) and Chikungunya (CHIKV). All three arboviruses are currently endemic in Brazil and have caused major outbreaks in recent years. Rio de Janeiro city, host of the last Summer Olympic Games and the Football World Cup, has been specially affected by them. A surveillance system based on symptomatic reports is in place in Rio, but the true number of affected individuals is unknown due to the great number of Zika, Dengue and Chikungunya asymptomatic cases. Seroprevalence studies are more suitable to evaluate the real number of cases in a given population. We performed a populational seroprevalence survey in Rio, with recruitment of a sample of volunteers of all ages and gender from July to October 2018, within randomly selected census tracts and household. A total of 2,120 volunteers were interviewed and tested with rapid immunochromatographic test for ZIKV, DENV and CHIKV. Individuals with positive results for IgG and/or IgM from only one virus were classified accordingly, while those with test results positive for both ZIKV and DENV were classified as flaviviruses. We corrected for sample design and non-response in data analysis, and calculated point estimate prevalence and 95% confidence intervals for each virus. Arbovirus prevalence in the Rio's population (n = 6,688,927) was estimated at 48.6% [95% CI 44.8–52.4] (n = 3,254,121) for flaviviruses and at 18.0% [95% CI 14.8–21.2] (n = 1,204,765) for CHIKV. Approximately 17.0% [95% CI 14.1–20.1] (n = 1,145,674) of Rio´s population had no contact with any of the three arboviruses. The reported cases of Zika, Dengue and Chikungunya by the current surveillance system in place is insufficient to estimate their real numbers, and our data indicate that Zika seroprevalence could be at least five times and Chikungunya 45 times bigger. The high number of individuals having never been infected by any of the three arboviruses, may indicate a proper scenario for future outbreaks. [ABSTRACT FROM AUTHOR]

Background: Between January 2015 and August 2016, two epidemic waves of Zika virus (ZIKV) disease swept the Northeastern (NE) region of Brazil. As a result, two waves of Guillain-Barré Syndrome (GBS) were observed concurrently. The mandatory reporting of ZIKV disease began region-wide in February 2016, and it is believed that ZIKV cases were significantly under-reported before that. The changing reporting rate has made it difficult to estimate the ZIKV infection attack rate, and studies in the literature vary widely from 17% to > 50%. The same applies to other key epidemiological parameters. In contrast, the diagnosis and reporting of GBS cases were reasonably reliable given the severity and easy recognition of the disease symptoms. In this paper, we aim to estimate the real number of ZIKV cases (i.e., the infection attack rate) and their dynamics in time, by scaling up from GBS surveillance data in NE Brazil. Methodology: A mathematical compartmental model is constructed that makes it possible to infer the true epidemic dynamics of ZIKV cases based on surveillance data of excess GBS cases. The model includes the possibility that asymptomatic ZIKV cases are infectious. The model is fitted to the GBS surveillance data and the key epidemiological parameters are inferred by using a plug-and-play likelihood-based estimation. We make use of regional weather data to determine possible climate-driven impacts on the reproductive number R0 , and to infer the true ZIKV epidemic dynamics. Findings and conclusions: The GBS surveillance data can be used to study ZIKV epidemics and may be appropriate when ZIKV reporting rates are not well understood. The overall infection attack rate (IAR) of ZIKV is estimated to be 24.1% (95% confidence interval: 17.1%—29.3%) of the population. By examining various asymptomatic scenarios, the IAR is likely to be lower than 33% over the two ZIKV waves. The risk rate from symptomatic ZIKV infection to develop GBS was estimated as ρ = 0.0061% (95% CI: 0.0050%—0.0086%) which is significantly less than current estimates. We found a positive association between local temperature and the basic reproduction number, R0. Our analysis revealed that asymptomatic infections affect the estimation of ZIKV epidemics and need to also be carefully considered in related modelling studies. According to the estimated effective reproduction number and population wide susceptibility, we comment that a ZIKV outbreak would be unlikely in NE Brazil in the near future. Author summary: The mandatory reporting of the Zika virus (ZIKV) disease began region-wide in February 2016, and it is believed that ZIKV cases could have been highly under-reported before that. Given the Guillain-Barré syndrome (GBS) is relatively well reported, the GBS surveillance data has the potential to act as a reasonably reliable proxy for inferring the true ZIKV epidemics. We developed a mathematical model incorporating weather effects to study the ZIKV-GBS epidemics and estimated the key epidemiological parameters. It was found that the attack rate of ZIKV was likely to be lower than 33% over the two epidemic waves. The risk rate from symptomatic ZIKV case to develop GBS was estimated to be approximately 0.0061%. The analysis suggests that it would be difficult for another ZIKV outbreak to appear in Northeastern Brazil in the near future. [ABSTRACT FROM AUTHOR]

CPC 25 (2009) is the main accounting standard in Brazil that deals with contingent gains and it presents the disclosure requirements of these contingencies. This standard does not give the contingent asset item the same level of detail as it gives contingent liabilities and provisions. There are academic studies that have shown that: (i) this issue is controversial, (ii) the identification of a contingent asset is not an easy task, (iii) companies do not usually disclose their active contingencies, (iv) the values of the contingent gains can reach numbers of billions of Reals and (v) the Brazilian Securities and Exchange Commission (CVM) ordered the restatement of the financial statements of companies due to undue accounting of contingent gains. Considering this information, the objective of this research was to (a) analyze the adherence to CPC 25 (2009), regarding the disclosure of the contingent gains of the companies of the cyclical and non-cyclical consumer sectors listed on the BM&FBovespa and (b) propose a flowchart to assist companies and general accountants in the accounting treatment of contingent assets. The results of the analysis showed that 73% of companies did not meet contingent asset disclosure requirements, while 6% partially responded and only 21% were fully compliant with CPC 25 (2009). The low level of adherence to the standard evidences the need for additional clarification in CPC 25 (2009) and in the accounting literature in general. In presenting the proposed flowchart for accounting treatment of contingent gains, this study aims to make a direct and applied contribution to the corporate and academic world in order to aid in the improvement of the disclosure of contingent gains. Additionally, it was verified that the total estimated contingent assets disclosed exceeded R $ 6 billion. The present study is classified as an applied, descriptive, qualitative, quantitative, bibliographical and documentary research. [ABSTRACT FROM AUTHOR]

In this paper we analyse the introduction of irrational and real numbers in secondary textbooks, and specifically the propositions on how these should be taught, in a sample of Brazilian textbooks used in state schools and approved by the Ministry of Education. The analyses discussed in this paper follow an institutional perspective (using Chevallard's Anthropological Theory of Didactics). Our results indicate that the notion of irrational number is generally introduced on the basis of the decimal representation of numbers, and that the mathematical need for the construction of the field of real numbers remains unclear in the textbooks. It seems that textbooks used in secondary teaching institutions develop mathematical organisations which focus on the practical block. [ABSTRACT FROM AUTHOR]

The article offers information on ninth workshop on Logic, Language, Information and Computation (WoLLIC) 2002 held at the Auditório Padre Anchieta of the Pontifífica Universidade Católica do Rio de Janeiro, Brazil in 2002. The topics included computing with real numbers, model checking games and automata theory and logic.

Wildlife vehicle collisions (WVC) are a threat to wildlife and humans, killing millions of animals of numerous species, as well as causing significant damage to vehicles, drivers and passengers. Road fencing is a highly effective mitigation measure at reducing WVC, however its large-scale implementation requires a high investment. We questioned how long it would take for savings from avoided collisions to offset the investments in road fencing mitigation, focusing on vehicle damage costs. Using the information of a 3-year systematic roadkill monitoring of 1158 km in Mato Grosso do Sul, Brazil, we estimated the real number of casualties accounting for bias in roadkill counting. We obtained information on the material costs on cars and trucks due to WVC and, considering the road traffic volume characteristics, estimated the total material costs resulting from collisions with larger animals. Cost-benefit analyses allowed estimating the time required to amortize the investment in fencing, considering its application along the full surveyed roads or only in hotspots of mortality. We recorded over 10,000 WVC, 40% of which involved animals that can cause significant material damage to vehicles, namely the endangered lowland tapir (Tapirus terrestris , n = 267) and giant anteater (Myrmecophaga tridactyla , n = 608). The average material cost per accident was US$ 885 ± 1575 (mean ± SD). We show that investments are likely to pay off in 16–40 years for the mitigation of the full roads, and in 9–25 years for hotspots of mortality. Thus, road mitigation is a win-win solution for increasing traffic safety for humans and reduces road-related negative effects on biodiversity. [ABSTRACT FROM AUTHOR]

The presence of a large number of infected individuals with few or no symptoms is an important epidemiological difficulty and the main mathematical feature of COVID-19. The A-SIR model, i.e. a SIR (Susceptible–Infected–Removed) model with a compartment for infected individuals with no symptoms or few symptoms was proposed by Gaeta (2020). In this paper we investigate a slightly generalized version of the same model and propose a scheme for fitting the parameters of the model to real data using the time series only of the deceased individuals. The scheme is applied to the concrete cases of Lombardy, Italy and São Paulo state, Brazil, showing different aspects of the epidemic. In both cases we see strong evidence that the adoption of social distancing measures contributed to a slower increase in the number of deceased individuals when compared to the baseline of no reduction in the infection rate. Both for Lombardy and São Paulo we show that we may have good fits to the data up to the present, but with very large differences in the future behavior. The reasons behind such disparate outcomes are the uncertainty on the value of a key parameter, the probability that an infected individual is fully symptomatic, and on the intensity of the social distancing measures adopted. This conclusion enforces the necessity of trying to determine the real number of infected individuals in a population, symptomatic or asymptomatic. • COVID-19 epidemic previsions must take into account a large class of asymptomatic cases. • Disparate outcomes in previsions are consequence of the uncertainty in the number of asymptomatic individuals. • Necessity of determining the real number of infected individuals, symptomatic or asymptomatic. • Parameters of the model fitted to real data using only time series of deceased individuals. • Social distancing measures contributed to slower increase in the number of deceased individuals. [ABSTRACT FROM AUTHOR]