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Summary: Accurately quantifying the social distancing (SD) practice of a population is essential for governments and health agencies to better plan and adapt restrictions during a pandemic crisis. In such a scenario, the reduction of social mobility also has a significant impact on electricity consumption, since people are encouraged to stay at home and many commercial and industrial activities are reduced or even halted. This paper proposes a methodology to qualify the SD of a medium‐sized city, located in the northwest of the state of Rio Grande do Sul (RS), Brazil, using data of electricity consumption measured by the municipality's energy utility. The methodology consists of combining a data set, and an average consumption profile of Sundays is obtained using data from 4‐months, it is then defined as a high SD profile due to the typical lower social activities on Sundays. An supervised and an unsupervised artificial neural network (ANN) are trained with this profile and used to analyze electricity consumption of this city during the COVID‐19 pandemic. Low, moderate, and high SD ranges are also created, and the daily population behavior is evaluated by the ANNs. The results are strongly correlated and discussed with government restrictions imposed during the analyzed period and indicate that the ANNs can correctly classify the intensity of SD practiced by people. The unsupervised ANN is used more easily and in different scenarios, so it can be indicated for use by public administration for purposes of assess the effectiveness of SD policies based on the guidelines established during the COVID‐19 pandemic. [ABSTRACT FROM AUTHOR]

The increasing mortality of COVID-19 can aggravate soil contamination by metals, harmful to the health of the population, requiring new projects for future cemeteries capable of mitigating these impacts to the environment, justifying the importance of studying the concentrations of metals in the soil of urban cemeteries. The paper analyzed the levels of metals in the soil of urban cemeteries in the City of Carazinho, in the state of Rio Grande do Sul, located in southern Brazil, considering the increase in deaths by COVID-19, for the purpose of future projects for cemeteries aimed at mitigating the impacts generated on the environment. The soils of the three urban cemeteries in Carazinho were sampled, with 5 internal and external points, with 3 repetitions at depths of 0–20 and 20–40 cm, adding 180 samples to measure the concentrations of Fe, Mn, Cu, Zn, Cr and Pb (g kg−1), considering the analytical sequence: (1) analysis in triplicate with mean deviation (RDS); (2) R2 of the analytical curve; (3) traceability of the pattern of each metal; (4) quantification limit of each metal (QL), with the performance of nitroperchloric digestion of the samples and the determinations of metals by flame modality atomic absorption spectrometry. Quantitative data on deaths by COVID-19 were analyzed by univariate modeling of time series, in the integrated autoregressive moving averages model. The results of this study were made available to fifteen architects, who attributed future solutions for environmentally sustainable cemeteries. The results showed high levels of copper (Cu) and iron (Fe) in the soil of the cemeteries studied. Considering the increase in deaths and subsequent burials per COVID-19 revealed a prediction for the death toll of 6,082,306 for June 9, 2022, it is assumed that metal contamination can reach even higher levels. To mitigate these levels of contamination by metals, 80% of the architect respondents expressed their preference for a vertical cemetery, with treatment of gases and effluents to mitigate environmental impacts. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the impacts of the Covid-19 pandemic on small companies in the fashion sector in Rio Grande do Sul, as well as to understand the advertising strategies adopted in the maintenance/acquisition of customers. As for its typology, this work uses Descriptive (objectives), Bibliographic, Field Research and Survey (technical procedures) and Qualitative (problem approach) research. script consisting of 13 open questions, having as target audience respondents who act as managers in small companies in the fashion sector in Rio Grande do Sul. At the end of the study, the results showed, among other points, that one of the greatest impacts of the pandemic for fashion companies was, precisely, the increase in price and the lack of raw material, the which led respondents to look for alternative materials to maintain production. Furthermore, brands had to quickly adapt to new changes, as those that did not have a more solid presence within the digital environment felt the need to accelerate this process and put all their efforts into this "new" way of selling. [ABSTRACT FROM AUTHOR]

This paper presents a study about using colors in maps that present information related to the Covid-19 pandemic. A sample was collected from two different governmental websites of the state of Rio Grande do Sul, Brazil. An analysis framework was developed based on the sample and drew from a literature review about the use of colors and maps in data visualization. The analysis showed that one of the examples collected presents an inconsistent use of colors, which could prompt difficulties in visualizing the data; the other example uses color more consistently, potentially being more effective in communicating information. In addition, the study showed potential for continuity and expansion due to the relevance of information design applied to health information. [ABSTRACT FROM AUTHOR]

The vampire bat (Desmodus rotundus) is a haematophagous animal that feeds exclusively on the blood of domestic mammals. Vampire bat feeding habits enable their contact with mammalian hosts and may enhance zoonotic spillover. Moreover, they may carry several pathogenic organisms, including coronaviruses (CoVs), for which they are important hosts. The human pathogens that cause severe acute respiratory syndrome (SARS‐CoV), Middle East respiratory syndrome (MERS‐CoV) and possibly coronavirus disease 2019 (SARS‐CoV‐2) all originated in bats but required bridge hosts to spread into human populations. To monitor the presence of potential zoonotic viruses in bats, the present work evaluated the presence of CoVs in vampire bats from southern Brazil. A total of 101 vampire bats were captured and euthanized between 2017 and 2019 in Rio Grande do Sul state, southern Brazil. The brain, heart, liver, lungs, kidneys and intestines were collected and macerated individually. The samples were pooled and submitted to high‐throughput sequencing (HTS) using the Illumina MiSeq platform and subsequently individually screened using a pancoronavirus RT‐PCR protocol. We detected CoV‐related sequences in HTS, but only two (2/101; 1.98%) animals had CoV detected in the intestines by RT‐PCR. Partial sequences of RdRp and spike genes were obtained in the same sample and the RdRp region in the other sample. The sequences were classified as belonging to Alphacoronavirus. The sequences were closely related to alphacoronaviruses detected in vampire bats from Peru. The continuous monitoring of bat CoVs may help to map and predict putative future zoonotic agents with great impacts on human health. [ABSTRACT FROM AUTHOR]

During the new coronavirus pandemic in Brazil, the conflicting measures of the central government denying the severity of the issue, on the one hand, and of states and municipalities obeying health and epidemiological guidelines, on the other, exacerbated the already high vulnerability of the population. The insufficient and weak healthcare infrastructure to face the pandemic has affected especially those who are victims of intense socio-spatial exclusion, such as the indigenous population. In this sense, this article seeks to describe deaths from Severe Acute Respiratory Syndrome (SARS) in indigenous people in the context of the Covid-19 pandemic in Rio Grande do Sul, Brazil's southernmost state. It is an ecological, descriptive, and analytical study that uses an open database of deaths from SARS up until September 2021. Clusters and outliers of the indigenous population were mapped with the census sectors parameter, using the Anselin Local Moran's I model and the spatialization of demarcated indigenous lands. The relative risk of death of indigenous people compared to the white population in selected municipalities was calculated. The results indicate that deaths from SARS are disproportionate for indigenous people in clustered areas and that the relative risk of death in some municipalities with a high concentration of this population as compared to whites is especially high in the northern part of the state. Therefore, to adopt geostrategic measures to contain and repair the severe impacts of the Covid-19 pandemic is a pressing need. [ABSTRACT FROM AUTHOR]

Due to its impact, COVID-19 has been stressing the academy to search for curing, mitigating, or controlling it. It is believed that under-reporting is a relevant factor in determining the actual mortality rate and, if not considered, can cause significant misinformation. Therefore, this work aims to estimate the under-reporting of cases and deaths of COVID-19 in Brazilian states using data from the InfoGripe. InfoGripe targets notifications of Severe Acute Respiratory Infection (SARI). The methodology is based on the combination of data analytics (event detection methods) and time series modeling (inertia and novelty concepts) over hospitalized SARI cases. The estimate of real cases of the disease, called novelty, is calculated by comparing the difference in SARI cases in 2020 (after COVID-19) with the total expected cases in recent years (2016–2019). The expected cases are derived from a seasonal exponential moving average. The results show that under-reporting rates vary significantly between states and that there are no general patterns for states in the same region in Brazil. The states of Minas Gerais and Mato Grosso have the highest rates of under-reporting of cases. The rate of under-reporting of deaths is high in the Rio Grande do Sul and the Minas Gerais. This work can be highlighted for the combination of data analytics and time series modeling. Our calculation of under-reporting rates based on SARI is conservative and better characterized by deaths than for cases. [ABSTRACT FROM AUTHOR]

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