Modeling of the air temperature using the Extreme Value Theory for selected biomes in Mato Grosso do Sul (Brazil).

This paper aims to find probabilities of extreme values of the air temperature for the Cerrado, Pantanal and Atlantic Forest biomes in Mato Grosso do Sul in Brazil. In this case a maximum likelihood estimation was employed for the probability distributions fitting the extreme monthly air temperatures for 2007-2018. Using the Extreme Value Theory approach this work estimates three probability distributions: the Generalized Distribution of Extreme Values (GEV), the Gumbel (GUM) and the Log-Normal (LN). The Kolmogorov-Smirnov test, the corrected Akaike criterion AIC c , the Bayesian information criterion BIC, the root of the mean square error RMSE and the determination coefficient R 2 were applied to measure the goodness-of-fit. The estimated distributions were used to calculate the probabilities of occurrence of maximum monthly air temperatures over 28-32 °C. Temperature predictions were done for the 2-, 5-, 10-, 30-, 50- and 100-year return periods. The GEV and GUM distributions are recommended to be used in the warmer months. In the coldest months, the LN distribution gave a better fit to a series of extreme air temperatures. Deforestation, combustion and extensive fires, and the related aerosol emissions contribute, alongside climate change, to the generation of extreme air temperatures in the studied biomes. Supplementary Information: The online version contains supplementary material available at 10.1007/s00477-022-02206-1.

Variations in the tropospheric concentration of NO2 in the central west of Brazil, MS, and their relationship with the COVID-19.

COVID-19 (coronavirus disease 2019) started in late 2019 in Wuhan, China. Subsequently, the disease was disseminated in several cities around the world, where measures were taken to control the spread of the virus through the adoption of quarantine (social isolation and closure of commercial sectors). This article analyzed the environmental impact of the COVID-19 outbreak in the state of Mato Grosso do Sul, Brazil, regarding the variations of nitrogen dioxide (NO2) in the atmosphere. NO2 data from the AURA satellite, in the period before the beginning of the epidemic (2005-2019) and during the adoption of the preventive and control measures of COVID-19 in 2020, were acquired and compared. The results obtained from the analysis showed that the blockade from COVID-19, beginning in March 2020, improved air quality in the short term, but as soon as coal consumption in power plants and refineries returned to normal levels (since June 2020), due to the resumption of works, the pollution levels returned to the level of the previous years of 2020. NO2 levels showed a significant decrease, since they were mainly associated with the decrease in economic growth and transport restrictions that led to a change in energy consumption and a reduction in emissions. This study can complement the scientific community and policy makers for environmental protection and public management, not only to assess the impact of the outbreak on air quality, but also for its effectiveness as a simple alternative program of action to improve air quality.

Generalized models and the impacts of population density on COVID-19 transmission / Modelos generalizados y los impactos de la densidad de población en la transmisión del COVID-19 / Modelos generalizados e os impactos da densidade populacional na transmissão da COVID-19

Objective: to analyze epidemic curves based on mathematical models for the state of Mato Grosso do Sul and the impacts of population density on COVID-19 transmission. Method: the linear, polynomial and exponential regression model was used to make the numerical adjustment of the respective curves empirical. Result: it was found that the models used describe very well the empirical curves in which they were tested. In particular, the polynomial model is able to identify with reasonable reliability the appearance of the inflection point in the accumulated curves, which corresponds to the maximum point of the respective daily curves. The analysis indicates a weak positive correlation between infection, mortality, lethality and deaths from COVID-19 with population density, as revealed by the correlation and analysis of R2 . Conclusion: the models are very effective in describing the COVID-19 and epidemic curves in the estimation of important epidemiological parameters, such as peak case curves and daily deaths, allowing practical and efficient monitoring of the evolution of the epidemic.

Objetivo: analizar curvas epidémicas basadas en modelos matemáticos para el estado de Mato Grosso do Sul y los impactos de la densidad de población en la transmisión de COVID-19. Método: se utilizó el modelo de regresión lineal, polinomial y exponencial para hacer el ajuste numérico valor de las respectivas curvas empíricas. Resultados: se encontró que los modelos utilizados describen muy bien las curvas empíricas en las que fueron probados. En particular, el modelo polinomial es capaz de identificar con razonable fiabilidad la aparición del punto de inflexión en las curvas acumuladas, que corresponde al punto máximo de las respectivas curvas diarias. El análisis indica una correlación positiva débil entre la infección, la mortalidad, la letalidad y las muertes por COVID-19 con la densidad de población, según lo revelado por la correlación y el análisis de R2 .Conclusión: los modelos son muy efectivos para describir el COVID-19 y curvas epidémicas en la estimación de parámetros epidemiológicos importantes, como las curvas de casos máximos y las muertes diarias, lo que permite un seguimiento práctico y eficaz de la evolución de la epidemia.

Objetivo: analisar as curvas epidêmicas com base em modelos matemáticos para o estado de Mato Grosso do Sul e os impactos da densidade populacional na transmissão da COVID-19. Método: o modelo de regressão linear, polinomial e exponencial foi utilizado para fazer o ajuste numérico das respectivas curvas empíricas. Resultados: verificou-se que os modelos utilizados descrevem muito bem as curvas empíricas nas quais foram testados. Em particular, o modelo polinomial é capaz de identificar com razoável confiabilidade o aparecimento do ponto de inflexão nas curvas acumuladas, que corresponde ao ponto máximo das respectivas curvas diárias. A análise indica uma correlação positiva fraca entre infecção, mortalidade, letalidade e mortes por COVID-19 com a densidade populacional, conforme revelado pela correlação e análise de R 2. Conclusão: os modelos são muito eficazes na descrição das curvas epidêmicas de COVID19 e na estimativa de parâmetros epidemiológicos importantes, como curvas de casos de pico e óbitos diários, permitindo um monitoramento prático e eficiente da evolução da epidemia

Potenciais impactos da variabilidade climática sobre a morbidade respiratória em crianças, lactentes e adultos / Potential impacts of climate variability on respiratory morbidity in children, infants, and adults

OBJETIVO: Estudar a relação existente entre a o número de internações por doenças do aparelho respiratório em lactentes, crianças e adultos e as variações meteorológicas na cidade de Campo Grande (MS). MÉTODOS Foram utilizados dados diários de internações por doenças respiratórias, precipitação, temperatura do ar, umidade e velocidade dos ventos entre 2004 e 2008. Foram calculados os índices de conforto térmico humano, temperatura efetiva e temperatura efetiva com velocidade do vento com base nas variáveis meteorológicas. Foram realizados modelos lineares generalizados utilizando o modelo múltiplo de regressão de Poisson para predizer as internações por doenças respiratórias. RESULTADOS: Foram observados valores relativamente elevados dos coeficientes de correlação entre as variáveis estudadas e internações por pneumonia em crianças (R² = 68,4%), lactentes (R² = 71,8%) e adultos (R² = 81,8%). CONCLUSÕES: Os resultados aqui apresentados indicam em termos quantitativos o risco para um aumento no número de hospitalizações de crianças, lactentes e adultos de acordo com o aumento ou a diminuição das temperaturas, umidade, precipitação, velocidade dos ventos e índice de conforto térmico na cidade de Campo Grande.

OBJECTIVE: To determine whether climate variability influences the number of hospitalizations for respiratory diseases in infants, children, and adults in the city of Campo Grande, Brazil. METHODS: We used daily data on admissions for respiratory diseases, precipitation, air temperature, humidity, and wind speed for the 2004-2008 period. We calculated the thermal comfort index, effective temperature, and effective temperature with wind speed (wind-chill or heat index) using the meteorological data obtained. Generalized linear models, with Poisson multiple regression, were used in order to predict hospitalizations for respiratory disease. RESULTS: The variables studied were (collectively) found to show relatively high correlation coefficients in relation to hospital admission for pneumonia in children (R² = 68.4%), infants (R² = 71.8%), and adults (R² = 81.8%). CONCLUSIONS: Our results indicate a quantitative risk for an increase in the number of hospitalizations of children, infants, and adults, according to the increase or decrease in temperature, humidity, precipitation, wind speed, and thermal comfort index in the city under study.

Potential impacts of climate variability on respiratory morbidity in children, infants, and adults.

OBJECTIVE: To determine whether climate variability influences the number of hospitalizations for respiratory diseases in infants, children, and adults in the city of Campo Grande, Brazil. METHODS: We used daily data on admissions for respiratory diseases, precipitation, air temperature, humidity, and wind speed for the 2004-2008 period. We calculated the thermal comfort index, effective temperature, and effective temperature with wind speed (wind-chill or heat index) using the meteorological data obtained. Generalized linear models, with Poisson multiple regression, were used in order to predict hospitalizations for respiratory disease. RESULTS: The variables studied were (collectively) found to show relatively high correlation coefficients in relation to hospital admission for pneumonia in children (R² = 68.4%), infants (R² = 71.8%), and adults (R² = 81.8%). CONCLUSIONS: Our results indicate a quantitative risk for an increase in the number of hospitalizations of children, infants, and adults, according to the increase or decrease in temperature, humidity, precipitation, wind speed, and thermal comfort index in the city under study.

Qualidade do ar e transtornos respiratórios agudos em crianças / Air quality and acute respiratory disorders in children

Objetivo: Avaliar a relação entre poluição do ar e efeitos respiratórios agudos em crianças. Métodos: Estudo ecológico de séries temporais realizado em unidades públicas de saúde, no município do Campo Grande-MS, Brasil, entre 01 de janeiro de 2004 a 31 de dezembro de 2007. Analisaram-se dados diários de O3 (ozônio) e, como variáveis de desfecho, 16.981 atendimentos pediátricos de emergência por sintomas respiratórios, incluindo-se, no modelo para controle, as variáveis referentes à tendência temporal; sazonalidade; temperatura mínima, média e máxima; umidade relativa do ar; precipitação e infecções respiratórias. Determinou-se o coeficiente de correlação de Pearson das doenças respiratórias em função dos parâmetros climáticos para os anos 2004-2007. Resultados: Somente o O3 apresentou associação positiva e estatisticamente significativa, tanto com todos os atendimentos de emergência por queixas respiratórias, quanto com os atendimentos motivados por sintomas nas vias aéreas inferiores. As concentrações médias diárias de O3 não ultrapassaram os limites diários recomendados. Conclusão: Encontraram-se associações entre indicadores de poluição atmosférica e o número de atendimentos pediátricos de emergência, por motivos respiratórios, em Campo Grande, apesar de os níveis do poluente monitorado ozônio permanecerem abaixo dos limites recomendados, durante todo o período de estudo.

Objective: To evaluate the relationship between air pollution and acute respiratory disorders in children. Methods: An ecological study of time series conducted in public health units in the city of Campo Grande-MS, Brazil, from January 1, 2004 to December 31, 2007. Daily data of O3 (ozone) were analyzed and, as outcome variables, 16,981 emergency pediatric consultations for respiratory symptoms; including in control model the variables related to time trend; seasonality; minimum, maximum and average temperature; relative humidity; rainfall and respiratory infections. We determined the Pearson correlation coefficient of respiratory diseases in relation to climatic parameters for the years 2004-2007. Results: Only O3 had a positive and statistically significant association, both with all emergency care attendances for respiratory complaints, as with these due to symptoms in lower airways.The daily average concentrations of O3 did not exceed the recommended daily limits. Conclusion: We found associations between air pollution and the number of emergency pediatric consultations for respiratory causes in Campo Grande, although the levels of monitored pollutant ozone remained below recommended levels throughout the study period.