Modelagem estatística das internações hospitalares por pneumonia em Campo Grande

Justification and Objectives: Brazil lacks consistent epidemiological data on the respiratory morbidity of children and older adults, which makes it difficult to plan and execute effective preventive and health promotion actions. The objective of this study was to analyze the adjustments of distributions (Weibull, Normal, Gamma, Logistic) of historical series of hospitalizations for respiratory diseases (total hospitalizations), from 2011 to 2015, in Campo Grande, Mato Grosso do Sul. Methods: to determine the statistical models, four statistical indicators (coefficient of determination, mean root square error, mean absolute error and mean absolute percentage error) were performed from 2011 to 2015. Parameter estimates are obtained for the models adopted in the study, with and without a regression structure. Results: the results showed that Weibull, Gamma, Normal and Logistic distributions, applied to the series of hospitalizations for respiratory diseases in Campo Grande, were satisfactory in determining the shape and scale parameters, and the statistical indicators R2, MAE, RSME and MAPE confirmed the data goodness-of-fit, and the graphical analysis indicated a satisfactory distribution fit. Conclusion: the analysis of monthly values indicates that Gamma is the best of the four distributions based on those selected. The regression model can be adjusted to the data and used as an alternative distribution that describes the hospitalization data considered in Campo Grande, Brazil.Justificación y Objetivos: el Brasil carece de datos epidemiológicos consistentes sobre la morbilidad respiratoria de niños y ancianos, lo que dificulta la planificación y ejecución de acciones efectivas de prevención y promoción de la salud. El objetivo de este estudio fue analizar los ajustes de las distribuciones (Weibull, Normal, Gamma, Logística) de la serie histórica de hospitalizaciones por enfermedades respiratorias (hospitalizaciones totales), de 2011 a 2015, en Campo Grande, Mato Grosso do Sul. Métodos: para la determinación de los modelos estadísticos, se realizaron cuatro indicadores estadísticos (coeficiente de determinación, raíz del error cuadrático medio, error medio absoluto y error porcentual absoluto medio) de 2011 a 2015. Se obtienen estimaciones de los parámetros para los modelos adoptados en el estudio, con y sin estructura de regresión. Resultados: los resultados mostraron que las distribuciones Weibull, Gamma, Normal y Logística, aplicadas a la serie de internaciones por enfermedades respiratorias en Campo Grande, fueron satisfactorias en la determinación de los parámetros de forma y escala, y los indicadores estadísticos R2, MAE, RSME y MAPE confirmaron la calidad de ajuste de los datos, y el análisis gráfico indicaron un ajuste satisfactorio de las distribuciones. Conclusión: el análisis de los valores mensuales indica que la Gamma es la mejor de las cuatro distribuciones en base a las seleccionadas. El modelo de regresión se puede ajustar a los datos y utilizar como una distribución alternativa que describe los datos de hospitalización considerados en Campo Grande, Brasil.Justificativa e Objetivos: o Brasil carece de dados epidemiológicos consistentes sobre a morbidade respiratória de crianças e idosos, o que dificulta o planejamento e a execução de ações efetivas de prevenção e promoção da saúde. O objetivo deste estudo foi analisar os ajustes das distribuições (Weibull, Normal, Gamma, Logística) da série histórica de internações por doenças respiratórias (total de internações), no período de 2011 a 2015, em Campo Grande, Mato Grosso do Sul. Métodos: para determinar os modelos estatísticos, foram executados quatro indicadores estatísticos (coeficiente de determinação, erro quadrático médio, erro absoluto médio e erro percentual absoluto médio) de 2011 a 2015. As estimativas dos parâmetros são obtidas para os modelos adotados no estudo com e sem uma estrutura de regressão. Resultados: os resultados mostraram que as distribuições Weibull, Gamma, Normal e Logística, aplicadas à série de internações por doenças respiratórias em Campo Grande, foram satisfatórias na determinação dos parâmetros de forma e escala, e os indicadores estatísticos R2, MAE, RSME e MAPE confirmaram a qualidade do ajuste dos dados, e a análise gráfica apontou um ajuste satisfatório das distribuições. Conclusão: a análise dos valores mensais indica que a Gamma é a melhor das quatro distribuições baseadas nos selecionados. O modelo de regressão pode ser ajustado aos dados e ser usado como uma distribuição alternativa que descreve os dados de internação considerados em Campo Grande, Brasil

Aspectos da mão de obra contratada e qualidade do leite em propriedades leiteiras localizadas no sul de Minas Gerais

Objetivou-se analisar alguns aspectos socioeconômicos e comportamentais, local de trabalho e direitos trabalhistas de 37 ordenhadores considerados contratados provenientes de 28 propriedades leiteiras localizadas em seis municípios da região sul de Minas Gerais, por meio da aplicação de formulário semiestruturado durante os horários de ordenha. Verificou-se a relação de frequência entre os aspectos verificados e as médias das análises de contagem bacteriana total (CBT) (superiores a 100.000 UFC/mL) e contagem de células somáticas (CCS) (superiores a 600.000 células/mL) do leite dos tanques. Constatou-se que a maioria das propriedades leiteiras estudadas utilizavam sistema de produção do tipo semi-intensivo, com duas ordenhas diárias, realizadas em ordenhadeiras do tipo balde ao pé e sistema de refrigeração em tanques de expansão; produção superior a 151 litros de leite/dia e no máximo 20 litros de leite/vaca/dia. No total, 89% e 57% das propriedades apresentaram médias inferiores aos limites da legislação para CBT e CCS, respectivamente. As questões relacionadas com a tecnificação das propriedades estudadas (tanto alto, quanto baixo) e, algumas questões referentes às características do local de trabalho, comportamentais e direitos trabalhistas dos ordenhadores contratados e substitutos (“folguistas”), apresentaram uma relação com a qualidade higiênico-sanitária do leite produzido, pois, em geral, nas propriedades em que tais questões não condiziam com o preconizado, as médias de CBT e CCS apresentaram-se com maiores frequências superiores aos limites estabelecidos

Área foliar de mudas de urucum (Bixa orellana L.) estimada por diferentes métodos: uma análise comparativa

Leaf area (LA) determination of the crops is a parameter indicative of growth and yield, and precise and accurate methods for its estimation are very important. Urucum (Bixa orellana L.) is an arboreal species, native to the Amazon Rainforest and Atlantic Forest, with economic importance due to its natural dye seed extracts. Thus, the aim of this paper is to compare different methods for LA determination in Urucum seedlings. To do so, the planimetric method was considered the standard method and its equivalence to the method based in leaf size parameters — length (L) and width (W) — and the scanner method were tested. In the method based in leaf size parameters, the f of 0.64 was previously adjusted for the annatto by regression analysis between LA and the C xL product. In the scanner method, the ImageJ app was used to determine the LA. Linear regression without intercept between LA through the standard method and LA estimated through each alternative method was used to check the conformity between the results. Leaf size and scanner methods were equivalent to the standard method (5% error probability) and equivalent to each other (1% error probability). Thus, these methods can be reliably used for estimating the Urucum leaf area. However, the dimension method has practical advantages compared to the others as it is a non-destructive method.A determinação da área foliar (AF) das culturas é um parâmetro indicativo do crescimento e da produtividade, sendo a busca por métodos precisos e exatos para a sua estimativa de extrema importância. O urucum (Bixa orellana L.) é uma espécie arbórea nativa da Floresta Amazônica e da Mata Atlântica, cuja importância econômica está relacionada ao corante natural extraído de suas sementes. Assim, o presente estudo objetivou comparar diferentes métodos para determinação da AF em mudas de urucum. Para isso, o método planimétrico foi considerado padrão e, com base nele, testou-se a equivalência em relação aos métodos das dimensões foliares — comprimento (C) e largura (L) — e ao scanner. No método das dimensões foliares o fator de forma (f) de 0,64 foi ajustado previamente para o urucum por meio da análise de regressão entre AF e o produto C x L. No método do scanner, utilizou-se o aplicativo ImageJ para determinar a AF. A regressão linear sem intercepto entre AF do método padrão e AF estimada por cada método alternativo foi utilizada para verificar a concordância dos resultados. Os métodos das dimensões foliares e do scanner foram equivalentes ao método padrão (5% de probabilidade de erro) e equivalentes entre si (1% de probabilidade de erro). Assim, verificou-se que esses métodos podem ser empregados com segurança na estimativa da área foliar do urucum. Contudo, o método das dimensões apresenta vantagens práticas em relação aos outros por ser não destrutivo

In Utero Exposure to Antiretroviral Drugs: Effect on Birth Weight and Growth Among HIV-exposed Uninfected Children in Brazil.

BACKGROUND There are concerns about the effects of in utero exposure to antiretroviral drugs (ARVs) on the development of HIV-exposed but uninfected (HEU) children. The aim of this study was to evaluate whether in utero exposure to ARVs is associated with lower birth weight/height and reduced growth during the first 2 years of life. METHODS This cohort study was conducted among HEU infants born between 1996 and 2010 in Tertiary children's hospital in Rio de Janeiro, Brazil. Weight was measured by mechanical scale, and height was measured by measuring board. Z-scores for weight-for-age (WAZ), length-for-age (LAZ) and weight-for-length were calculated. We modeled trajectories by mixed-effects models and adjusted for mother's age, CD4 cell count, viral load, year of birth and family income. RESULTS A total of 588 HEU infants were included of whom 155 (26%) were not exposed to ARVs, 114 (19%) were exposed early (first trimester) and 319 (54%) later. WAZ were lower among infants exposed early compared with infants exposed later: adjusted differences were -0.52 (95% confidence interval [CI]: -0.99 to -0.04, P = 0.02) at birth and -0.22 (95% CI: -0.47 to 0.04, P = 0.10) during follow-up. LAZ were lower during follow-up: -0.35 (95% CI: -0.63 to -0.08, P = 0.01). There were no differences in weight-for-length scores. Z-scores of infants exposed late during pregnancy were similar to unexposed infants. CONCLUSIONS In HEU children, early exposure to ARVs was associated with lower WAZ at birth and lower LAZ up to 2 years of life. Growth of HEU children needs to be monitored closely

Modeling of Dengue by Cluster Analysis and Probability Distribution Functions in the State of Alagoas in Brazilian

Abstract Dengue is a viral disease whose number of cases has increased in Brazil. This study aimed to characterize the spatio-temporal distribution patterns of the reported dengue infection cases in the state of Alagoas (AL), Northeastern Brazil (NEB). The data of the officially reported dengue cases from 2000 to 2015 was retrieved from the State Health Secretariat of Alagoas (SESAL), which captures national demographic and health data from the System for the Reporting of Notifiable Conditions (SINAN). After applying the Kernel Density Estimation (KDE) function, maps were generated based on the Inverse Distance Weighting (IDW) interpolation method. By using the clusters analysis (CA) technique, three homogeneous groups of dengue in AL were determined. Next, the LN (Lognormal), GUM (Gumbel) and GEV (Generalized Extreme Value) probability distributions were applied to monthly model dengue case data in AL, with the LN continuous probability distribution standing out. Maceió and Arapiraca have a higher number of dengue cases than other cities, being the main reason for their interpretation as separate groups. The coefficients of determination (R2) of dengue cases analysis as a function of month of each year for the studied years were low (between 0.03 and 0.63) and many regression slopes were not significant. Pearson's correlation coefficient (r) between dengue and the Human Development Index (HDI) of LA was considered moderate (0.53) and the correlation between dengue and demographic density was high (0.76). The importance of constant monitoring and assistance for these areas is reinforced

Rainfall in the urban area and its impact on climatology and population growth

Due to the scarcity of studies linking the variability of rainfall and population growth in the capital cities of Northeastern Brazil (NEB), the purpose of this study is to evaluate the variability and multiscale interaction (annual and seasonal), and in addition, to detect their trends and the impact of urban growth. For this, monthly rainfall data between 1960 and 2020 were used. In addition, the detection of rainfall trends on annual and seasonal scales was performed using the Mann–Kendall (MK) test and compared with the phases of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). The relationship between population growth data and rainfall data for different decades was established. Results indicate that the variability of multiscale urban rainfall is directly associated with the ENSO and PDO phases, followed by the performance of rain-producing meteorological systems in the NEB. In addition, the anthropic influence is shown in the relational pattern between population growth and the variability of decennial rainfall in the capitals of the NEB. However, no capital showed a significant trend of increasing annual rainfall (as in the case of Aracaju, Maceió, and Salvador). The observed population increase in the last decades in the capitals of the NEB and the notable decreasing trend of rainfall could compromise the region’s water security. Moreover, if there is no strategic planning about water bodies, these changes in the rainfall pattern could be compromising

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000–18: a geospatial modelling study

Background: More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels. Methods: We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km × 5 km resolution in 98 LMICs based on 2·1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution. Findings: Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205 000 (95% uncertainty interval 147 000–257 000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution. Interpretation: Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution. Funding: Bill & Melinda Gates Foundation

Mapping development and health effects of cooking with solid fuels in low-income and middle-income countries, 2000-18 : a geospatial modelling study

Background More than 3 billion people do not have access to clean energy and primarily use solid fuels to cook. Use of solid fuels generates household air pollution, which was associated with more than 2 million deaths in 2019. Although local patterns in cooking vary systematically, subnational trends in use of solid fuels have yet to be comprehensively analysed. We estimated the prevalence of solid-fuel use with high spatial resolution to explore subnational inequalities, assess local progress, and assess the effects on health in low-income and middle-income countries (LMICs) without universal access to clean fuels.Methods We did a geospatial modelling study to map the prevalence of solid-fuel use for cooking at a 5 km x 5 km resolution in 98 LMICs based on 2.1 million household observations of the primary cooking fuel used from 663 population-based household surveys over the years 2000 to 2018. We use observed temporal patterns to forecast household air pollution in 2030 and to assess the probability of attaining the Sustainable Development Goal (SDG) target indicator for clean cooking. We aligned our estimates of household air pollution to geospatial estimates of ambient air pollution to establish the risk transition occurring in LMICs. Finally, we quantified the effect of residual primary solid-fuel use for cooking on child health by doing a counterfactual risk assessment to estimate the proportion of deaths from lower respiratory tract infections in children younger than 5 years that could be associated with household air pollution.Findings Although primary reliance on solid-fuel use for cooking has declined globally, it remains widespread. 593 million people live in districts where the prevalence of solid-fuel use for cooking exceeds 95%. 66% of people in LMICs live in districts that are not on track to meet the SDG target for universal access to clean energy by 2030. Household air pollution continues to be a major contributor to particulate exposure in LMICs, and rising ambient air pollution is undermining potential gains from reductions in the prevalence of solid-fuel use for cooking in many countries. We estimated that, in 2018, 205000 (95% uncertainty interval 147000-257000) children younger than 5 years died from lower respiratory tract infections that could be attributed to household air pollution.Interpretation Efforts to accelerate the adoption of clean cooking fuels need to be substantially increased and recalibrated to account for subnational inequalities, because there are substantial opportunities to improve air quality and avert child mortality associated with household air pollution. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.Peer reviewe