Diagnóstico situacional de seguridad alimentaria en Argentina, Brazil, Colombia e Inglaterra post Covid-19

O artigo analisa as iniciativas de promoção da segurança alimentar na Argentina, Brasil, Colômbia e Inglaterra a partir do desenho de um diagnóstico situacional dos países em questão, no período pós-Covid-19. São dados secundários recentes de agências de pesquisa locais e multilaterais que questionam a gama de indicadores de riqueza e pobreza versus insegurança alimentar entre a população mais vulnerável. Avança também no modo de produzir alimentos em larga escala, principalmente a economia baseada em commodities, questionando a soberania na produção de alimentos e a contradição com as premissas do desenvolvimento sustentável. Busca evidenciar a implementação de alguns programas e políticas sociais. Nesses países, para cuidar de famílias em situação de vulnerabilidade social.Alternate :El artículo analiza iniciativas para promover la seguridad alimentaria en Argentina, Brazil, Colombia e Inglaterra a partir del diseño de un diagnóstico situacional de los países en mención, en el periodo post-Covid-19. Se trata de datos secundarios recientes de agencias de investigación locales y multilaterales que cuestionan la gama de indicadores de riqueza y pobreza frente a la inseguridad alimentaria entre la población más vulnerable. También avanza sobre la forma de producir alimentos a gran escala, en especial la economía basada en commodities, cuestionando la soberanía en la producción de alimentos y la contradicción frente a las premisas para el desarrollo sostenible. Busca evidenciar sobre la implementación de algunos programas y políticas sociales. En los referidos países, para atender a las familias en situación de vulnerabilidad social.Alternate :The article analyzes the initiatives to promote food security in Argentina, Brazil, Colombia and England based on the design of a situational diagnosis of the countries in question, in the post-Covid-19 period. These are recent secondary data from local and multilateral research agencies that question the range of indicators of wealth and poverty versus food insecurity among the most vulnerable population. It also advances in the way of producing food on a large scale, mainly the economy based on commodities, questioning the sovereignty in food production and the contradiction with the premises of sustainable development. It seeks to highlight the implementation of some social programs and policies. In these countries, to care for families in situations of social vulnerability.

Before and after COVID-19: An examination of social indicators of mental health in early childhood education teachers

The current study aimed to identify individual- and environmental-level social indicators of mental health for Washington State early childhood education (ECE) teachers before and at the onset of the COVID-19 pandemic. Using survey data collected in Fall 2019 and April 2020 from the Washington State ECE Workforce Survey Study (N = 1156), I examined whether ECE teachers' socio-demographic, professional, and work environment characteristics were predictive of ECE teachers' depression scores before the pandemic in Fall 2019. In addition, I also examined whether COVID-19 stressors were predictive of change in depression scores in ECE teachers at the onset of the pandemic, after controlling for pre-pandemic depression levels and other individual- and work environment-level characteristics. When looking at social indicators of mental health before the pandemic, regression model results showed that ECE teachers' age, self-identification as Latinx, weekly work hours, teachers' students' age group, job demands, and job support were each uniquely predictive of depression scores. Specifically, weekly work hours, working with infants and toddlers, and job demands were predictive of increased depression, and teachers' age, self-identification as Latinx, and job support were predictive of decreased depression. In the second regression model, results showed a significant mean increase in depression scores from Fall 2019 to onset of the pandemic in April 2020, indicating a change from mild to more pervasive symptoms of depression in ECE teachers. Further, the model results revealed that ECE teachers' pre-COVID depression scores, age, self-identification as Asian, and other minority racial groups, such as Native American, Middle Eastern, Pacific Islander, and biracial, and job demands, and income worry were predictive of change in depression scores, with income worry being one of the strongest predictors. Specifically, job demands before COVID and income worry were predictive of more change in depression scores (indicating more depression symptoms), and pre-COVID depression scores, self-identification as Asian, Native American, Middle Eastern, Pacific Islander, and biracial were predictive of less change in depression scores, indicating a little less increase in depression scores compared to teachers with higher depression scores before the pandemic and White teachers. Implications of these findings on the ECE teacher workforce, as well as recommendations for policy and practice, are discussed. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

COVID-19 pandemic: environmental and social factors influencing the spread of SARS-CoV-2 in São Paulo, Brazil.

The new coronavirus SARS-CoV-2 has infected more than 14 million people worldwide so far. Brazil is currently the second leading country in number of cases of COVID-19, while São Paulo state accounts for 20% of total confirmed cases in Brazil. The aim of this study was to assess environmental and social factors influencing the spread of SARS-CoV-2 in the expanded metropolitan area of São Paulo, Brazil. Firstly, a spatial analysis was conducted to provide insights into the spread of COVID-19 within the expanded metropolitan area. Moreover, Spearman correlation test and sensitivity analysis were performed to assess social indicators and environmental conditions which possibly influence the incidence of COVID-19. Our results reveal that the spread of COVID-19 from the capital city São Paulo-its epicenter in Brazil-is directly associated with the availability of highways within the expanded metropolitan area of São Paulo. As for social aspects, COVID-19 infection rate was found to be both positively correlated with population density, and negatively correlated with social isolation rate, hence indicating that social distancing has been effective in reducing the COVID-19 transmission. Finally, COVID-19 infection rate was found to be inversely correlated with both temperature and UV radiation. Together with recent literature our study suggests that the UV radiation provided by sunlight might contribute to depletion of SARS-CoV-2 infectivity.

SoBigDemicSys: A Social Media based Monitoring System for Emerging Pandemics with Big Data

The outbreak of Covid-19 pandemic has caused millions of people infected and dead, resulting in global economy depression. Lessons learned to minimize the damage in an emerging pandemic is that timely tracking and reasonable trend prediction are required to help the society (e.g., municipality, institutions, and industries) with timely planning for efficient resource preparation and allocation. This paper presents a system to monitor the pandemic trends, analyze the correlation and impacts, predict the evolution, and visualize the prediction results to end users as social indicators. The significance lies in the fact that tracing online information collection for pandemic related prediction has less time lag, cheaper cost, and more potential information indicators. © 2022 IEEE.

The Social Indicators of the Reputation of an Expert

A notion that comes from the toolbox of social sciences, trust has become a mainstream epistemological concept in the last 15 years. The notion of epistemic trust has been distinguished from the notion of moral and social trust, the former involves kinds of inferences about the others that are rationally justifiable. If I trust a scientist about the efficacy of a vaccine against COVID-19, I must have an epistemic justification. I am therefore rationally justified in trusting her because I have an epistemic reason to justify my belief. I will challenge the distinction between epistemic and moral and social trust by pointing to several social indicators that contribute to our trustful attitudes in a reasonable way. Social indicators of reputation, values and moral commitments to values are indispensable strategies to come to trust in a rational way, an attitude that is different from merely believing the truth. I also point out the fragility of trusting experts’ reputations and stress the importance of avoiding biases in trusting other people’s reputations to make our deference to experts more robust. [ FROM AUTHOR] Copyright of Social Epistemology is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Why Trust Raoult? How Social Indicators Inform the Reputations of Experts

The COVID-19 crisis has highlighted the considerable challenge of sourcing expertise and determining which experts to trust. Dissonant information fostered controversy in public discourse and encouraged an appeal to a wide range of social indicators of trustworthiness in order to decide whom to trust. We analyze public discourse on expertise by examining how social indicators inform the reputation of Dr. Didier Raoult, the French microbiologist who rose to international prominence as an early advocate for using hydroxychloroquine to treat COVID-19. To comprehend how these indicators came to inform his reputation, we outline Dr. Raoult's rise to fame based on discourse about hydroxychloroquine. We then discuss why we trust in experts like scientist-practitioners. This is followed by an examination of how social indicators of trust like status, epistemic authority, influence and values have informed Dr. Raoult's reputation. We conclude with recommendations for how to improve the selection and evaluation of social indicators of trust and reputations. Our aim here, instead of making a claim about the efficacy of hydroxychloroquine or Dr. Raoult's reputation per se, is to outline through this case study how social indicators of trust inform reputation and the challenge they present to evaluating expertise. [ FROM AUTHOR] Copyright of Social Epistemology is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

CoVID-19 Spread and its Impact Analysis

The proposed research aims at the analysis of spread of coronavirus and factors that contributed significantly in the rise or fall of death rate by correlating it with various social indicators. We will be using data analytics and visualization techniques to get significant insights from data collected from World Health Organization (WHO), John Hopkins University and other data repositories and reputable sources. © 2021 IEEE.

Meta-analysis and adjusted estimation of COVID-19 case fatality risk in India and its association with the underlying comorbidities.

Management of coronavirus disease 2019 (COVID-19) in India is a top government priority. However, there is a lack of COVID-19 adjusted case fatality risk (aCFR) estimates and information on states with high aCFR. Data on COVID-19 cases and deaths in the first pandemic wave and 17 state-specific geodemographic, socio-economic, health and comorbidity-related factors were collected. State-specific aCFRs were estimated, using a 13-day lag for fatality. To estimate country-level aCFR in the first wave, state estimates were meta-analysed based on inverse-variance weighting and aCFR as either a fixed- or random-effect. Multiple correspondence analyses, followed by univariable logistic regression, were conducted to understand the association between aCFR and geodemographic, health and social indicators. Based on health indicators, states likely to report a higher aCFR were identified. Using random- and fixed-effects models, cumulative aCFRs in the first pandemic wave on 27 July 2020 in India were 1.42% (95% CI 1.19%-1.70%) and 2.97% (95% CI 2.94%-3.00%), respectively. At the end of the first wave, as of 15 February 2021, a cumulative aCFR of 1.18% (95% CI 0.99%-1.41%) using random and 1.64% (95% CI 1.64%-1.65%) using fixed-effects models was estimated. Based on high heterogeneity among states, we inferred that the random-effects model likely provided more accurate estimates of the aCFR for India. The aCFR was grouped with the incidence of diabetes, hypertension, cardiovascular diseases and acute respiratory infections in the first and second dimensions of multiple correspondence analyses. Univariable logistic regression confirmed associations between the aCFR and the proportion of urban population, and between aCFR and the number of persons diagnosed with diabetes, hypertension, cardiovascular diseases and stroke per 10,000 population that had visited NCD (Non-communicable disease) clinics. Incidence of pneumonia was also associated with COVID-19 aCFR. Based on predictor variables, we categorised 10, 17 and one Indian state(s) expected to have a high, medium and low aCFR risk, respectively. The current study demonstrated the value of using meta-analysis to estimate aCFR. To decrease COVID-19 associated fatalities, states estimated to have a high aCFR must take steps to reduce co-morbidities.