Epidemiological aspects and spatial patterns of human visceral leishmaniasis in Brazil.

Human visceral leishmaniasis (HVL) cases are important public health problems due to their zoonotic aspect, with high rates of morbidity and mortality in Brazil. The aim of this this study was to identify spatial patterns in both rates of HVL cases in Brazilian states during the period from 2006 to 2015. This is an ecological study, using geoprocessing tools to create choropleth maps, based on secondary data from open access platforms, to identify priority areas for control actions of the disease. Data were collected in 2017 and analysed according to the global and local Moran's I, using TerraView 4.2.2 software. Similar clusters were observed in neighbouring municipalities in thematic maps of HVL, suggesting spatial similarity in the distribution of the disease in humans mainly in the North and Northeast Regions, which concentrate the states with the highest rates of HVL. Heterogeneous spatial patterns were observed in the distribution of HVL, which show municipalities that need higher priority in the intensification of disease surveillance and control strategies.

Decline in Vaccination Coverage against Poliomyelitis in the municipalities of Vale do Paraíba (SP) under a spatial approach.

OBJECTIVE: To analyze vaccination coverage (VC) for polio in the municipalities of Vale do Paraíba in the State of São Paulo. METHODS: This is an ecological and exploratory study of VC in 35 municipalities using a spatial approach; VC data were obtained from the IT Department of the Unified Health System (DATASUS), for the years 2015 and 2019, and categorized into Low (VC<95%) and ideal (≥95%). Information was obtained on gross domestic product (GDP), professional rates and number of basic health units (UBS) and maternal data such as age, marital status (MS) and education. Univariate and bivariate Moran indices were estimated for the years 2015 and 2019, and thematic maps were created for CV values. RESULTS: The average VC values were 107.7%±27.2 in 2015, and 94.2%±27.8 in 2019 (p<0.05). In 2015 vs. 2019, there were 10 vs. 25 municipalities in the Low category. In 2015, the variables VC, number of UBS, age, education, and MS were spatially correlated, but in 2019 only maternal age and education were spatially correlated. The bivariate Moran was significant and negative for VC in 2019 with maternal education. There was an increase in municipalities with worsening VC values. CONCLUSIONS: The spatial approach identified a decrease in polio vaccination coverage in the studied region.

Spatial patterns of prematurity and its determinants in the metropolitan region of São Paulo, Brazil, 2010-2019.

OBJECTIVE: To analyze spatial distribution of preterm births and their association with maternal, social, and health services indicators in the metropolitan region of São Paulo, Brazil, 2010-2019. METHODS: Ecological study using data on preterm newborns from 39 municipalities in the metropolitan region of São Paulo. Univariate global Moran's index (Im) was used to evaluate spatial association of prematurity, and univariate local Moran's index by using the cluster map (LISA) to identify spatial patterns and clusters. Bivariate global Moran's index was also used to analyze spatial autocorrelation with maternal, social, and health services indicators. RESULTS: A total of 3,103,898 live births were registered in period 2010-2019, of which 331,174 (10.7%) were preterm. The global Moran's index showed spatial independence (Im=0.05; p-value=0.233) of the proportion of preterm births between municipalities. However, in the local spatial analysis it was possible to identify a statistically significant spatial cluster between the municipalities of Biritiba Mirim, Guararema and Salesópolis, with high proportions of preterm births. In the bivariate analysis, a significant positive spatial association was identified with proportions of mothers under 20 years old (Im=0.17; p-value=0.024) and mothers with low schooling (Im=0.17; p-value=0.020), and a significant negative spatial association with HDI (Im=-0.14; p-value=0.039). CONCLUSIONS: The local spatial approach identified a spatial cluster located in the far east of the metropolitan region of São Paulo, where actions by health managers are needed to minimize occurrence of preterm births.

Spatial patterns of mortality in low birth weight infants at term and its determinants in the State of São Paulo, Brazil.

OBJECTIVE: Low birth weight (LBW) is a public health problem strongly associated with infant mortality. This study aimed to identify the spatial distribution of infant mortality in newborns with LBW (750-2,500 g) at term (≥37 weeks of gestation), due to their being small for gestational age, analyzing its association with mother-related determinants, as well as to identify priority areas of mortality in the State of São Paulo, 2010-2019. METHODS: Infant mortality rate was analyzed in the division of neonatal mortality and postneonatal mortality of newborns with LBW at term. The empirical Bayesian method smoothed the rates, the univariate Moran index was used to measure the degree of spatial association between the municipalities, and the bivariate Moran index was employed to identify the existence of a spatial association between the rates and the selected determinants. Thematic maps of excess risk and local Moran were prepared to identify spatial clusters, adopting 5% as a significance level. RESULTS: The excess risk map showed that more than 30% of the municipalities had rates above the state rate. High-risk clusters were identified in the southwest, southeast, and east regions, mainly among more developed municipalities. The determinants of adolescent mothers, mothers over 34 years of age, low education, human development index, social vulnerability index, gross domestic product, physicians, and pediatric beds showed a significant association with the rates evaluated. CONCLUSIONS: Priority areas and significant determinants associated with reduced mortality in newborns with LBW were identified, suggesting the need for intervention measures to achieve the Sustainable Development Goal.

SARS-CoV-2 infection in children and adolescents: a Brazilian experience.

OBJECTIVE: To describe clinical and epidemiological aspects of children and adolescents infected with the SARS-CoV-2 in the Municipality of Taubaté, SP, from March to November 2020. METHODS: Cross-sectional study with secondary data obtained from the Epidemiological Surveillance System about confirmed cases in city residents and from medical records of patients who were treated in hospitals in Taubaté, aged between 0 and 19 years. Chi-square and Student's t tests were used for comparisons. RESULTS: 677 cases in the studied age range were reported during the study period, corresponding to 10.1% of cases reported in the municipality. The rapid antibody test was the most used to confirm infection, followed by RT-PCR and serology. Symptoms were described in 57.7% of the cases, mainly fever and cough. Diarrhea was associated with age below 4 years, while fever, cough, headache, odynophagia, ageusia, anosmia, myalgia, and dyspnea were associated with an age ranging from 10 to 19 years. In the study period, there were no deaths from COVID-19 of residents of the municipality in the age group from 0 to 19 years. CONCLUSIONS: The study was able to identify the proportion of involvement of COVID-19 in children and adolescents in the city, and the disease had a mild evolution. The main symptoms were fever and cough, but mainly diarrhea in younger children, and headache, odynophagia, anosmia, ageusia, and myalgia in adolescents.

Association between exposure to air pollutants and hospitalization for SARS-Cov-2: an ecological time-series study.

BACKGROUND: Exposure to air pollutants and illness by severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection can cause serious pulmonary impairment. OBJECTIVE: To identify a possible association between exposure to air pollutants and hospitalizations due to SARS-Cov-2. DESIGN AND SETTING: Ecological time-series study carried out in Taubaté, Tremembé, and Pindamonhangaba in 2020 and 2021. METHODS: Study with Sars-Cov-2 hospitalizations with information on hospitalization date, sex and age of the subjects, duration of hospitalization, type of discharge, and costs of these hospitalizations. Statistical analysis was performed through a negative binomial regression, with data on pollutant concentrations, temperature, air relative humidity, and hospitalization date. Coefficients obtained by the analysis were transformed into relative risk for hospitalization, which estimated hospitalizations excess according to an increase in pollutant concentrations. RESULTS: There were 1,300 hospitalizations and 368 deaths, with a predominance of men (61.7%). These data represent an incidence rate of 250.4 per 100,000 inhabitants and 28.4% hospital lethality. Significant exposure (P value < 0.05) occurred seven days before hospital admission (lag 7) for nitrogen dioxide (NO2) (relative risk, RR = 1.0124) and two days before hospital admission for PM2.5 (RR = 1.0216). A 10 µg/m3 in NO2 concentration would decrease by 320 hospitalizations and ¼ US $ 240,000 in costs; a 5 µg/m3 in PM2.5 concentration would decrease by 278 hospitalizations and ¼ US $ 190,000 in costs. CONCLUSION: An association between exposure to air pollutants and hospital admission due to Sars-Cov-2 was observed with excess hospitalization and costs for the Brazilian public health system.

Years of life lost due to premature deaths associated with air pollution: an ecological time-series study.

BACKGROUND: Exposure to air pollutants is associated with hospital admissions due to cardiovascular diseases and premature deaths. OBJECTIVE: To estimate years of life lost (YLL) due to premature deaths and their financial costs. DESIGN AND SETTING: Ecological time-series study carried out in São José dos Campos, Brazil, in 2016. METHODS: Data on deaths among residents of this city in 2016 were assessed to estimate the financial cost of premature deaths associated with air pollution. The diagnoses studied were ischemic heart disease, congestive heart failure and cerebrovascular disease, according to YLL. The fractions attributable to deaths associated with air pollutant exposure and to each potential year of life lost were calculated using negative binomial regression with lags of 0-7 days between exposure and outcome. Nitrogen dioxide, particulate matter (PM10) and ozone concentrations were included in the model and adjusted for temperature, humidity and seasonality. RESULTS: Exposure to particulate matter was significant at lag 3 days. There were 2177 hospitalizations over the study period, with 201 deaths (9.2%). Premature deaths led to 2035.69 years of life lost. A 10 µg/m3 increase in PM10 concentrations was correlated with 8.0% of the hospitalizations, which corresponded to 152.67 YLL (81.67 for males and 71.00 for females). The cost generated was approximately US$ 9.1 million in 2016. CONCLUSION: In this first study conducted in a medium-sized Brazilian city, using the YLL methodology, we identified an excess expense attributable to air pollution.

CONGENITAL SYPHILIS IN THE PARAÍBA VALLEY USING A SPATIAL APPROACH.

OBJECTIVE: To compare spatial patterns of congenital syphilis (CS) with those of socioeconomic and medical variables in Paraíba Valley, São Paulo, between 2012 and 2016. METHODS: Ecological and exploratory study developed using spatial analysis tools, with information on CS cases obtained from official data reports. Rates were found for CS cases per 1,000 live births, number of family health teams and pediatricians available in the health system per 100,000 inhabitants, and social vulnerability index values. Thematic maps were constructed with these variables and compared using TerraView 4.2.2 software. Estimated global Moran (IM) indexes were calculated. In order to detect areas with priority attention regarding the incidence of CS, BoxMaps were developed. The Spearman correlation was estimated for the variable values and compared using the Kruskal-Wallis test. P <0.05 was significant. RESULTS: 144,613 births and 870 CS cases (6.04/1000 live births) occurred during the study period. The average value of CS rates per municipality was 4.0±4.1, (0.0-17.6/1000 live births). Higher CS rates occurred in municipalities of the Upper Vale do Paraíba, contrary to the proportions of pediatricians who were in the far east of the region. The thematic maps of the variables presented a mosaic aspect, which characterized the random distribution of the variables. The IM were not significant. No significant correlation was found between the variables. The BoxMap identified eight municipalities with high CS rates. CONCLUSIONS: Even though it was not possible to identify a spatial pattern of CS rates, it was shown that eight municipalities deserve the attention of city managers.

Spatial approach of leprosy in the State of São Paulo, 2009-2012.

BACKGROUND: Leprosy is a chronic, infectious disease that affects the skin and the peripheral nervous system and can lead to permanent disability and/or deformity. OBJECTIVES: To identify the distribution and to quantify the spatial dependence of the detection rates of new cases of Hansen's disease in the State of São Paulo, correlating with socioeconomic variables. METHODS: Ecological and exploratory study with data on the detection rates of new cases of Hansen's disease among residents of São Paulo State municipalities between 2009-2012. The average rate per 10,0000 inhabitants was estimated. Information on the proportion of the population with low-income and the values of the Gini index were obtained. Thematic maps were constructed with the average rates and with those obtained by the Bayesian estimator; Moran and Kernel maps were also constructed. Spatial analysis by TerraView program. An alpha of 5% was adopted. RESULTS: In total, 7163 new cases of Hansen's disease were recorded throughout the state. The average rate per 10,000 inhabitants, was 0.71 (SD = 1.06), ranging from zero to 12.87, with higher rates in the west of the State, in the metropolitan area of the capital and the Paraiba Valley. Municipalities with high priority for intervention were located in the west and northwest of the State. There was no correlation between rates with Gini index and low income. STUDY LIMITATIONS: Possible inconsistency of Hansen's disease notification database regarding information quantity, quality and processing. CONCLUSIONS: This study identified the distribution and quantified the spatial dependence of the detection rates of new cases of Hansen's disease in the State of São Paulo, corroborating previous studies and serving as a subsidy to health managers.

Maternal exposure to benzene and toluene and preterm birth. A longitudinal study.

BACKGROUND: Exposure to air pollutants has several effects on human health, including during pregnancy. OBJECTIVE: To identify whether exposure to benzene and toluene among pregnant women contributes to preterm delivery. DESIGN AND SETTING: Longitudinal study using data on newborns from mothers living in São José dos Campos (SP) in 2016, who had been exposed to benzene and toluene. METHODS: A logistic regression model with three hierarchical levels was constructed using maternal variables relating to newborns, and using benzene and toluene concentrations in quartiles. Occurrences of cesarean births, twins or malformations were excluded. Maternal exposure windows of 5, 10, 15, 30, 60 and 90 days prior to delivery were considered. RESULTS: Out of the 9,562 live births, 3,671 newborns were included and 343 newborns were born at less than 37 weeks of gestation (9.3%). The average birth weight was 3,167.2 g. Exposure to benzene and toluene was significantly associated (P = 0.04) with preterm delivery in the five-day window. There was no association in any of the other exposure windows. CONCLUSIONS: It was possible to identify that maternal exposure to benzene and toluene has an acute effect on preterm delivery.

Spatial distribution of hospitalization rates of children due to pneumonia in the Unified Health System, in the municipalities of the state of São Paulo. / Distribuição espacial das taxas de internação de crianças por pneumonia no Sistema Único de Saúde, nos municípios do estado de São Paulo.

OBJECTIVE: To identify spatial patterns in the distribution of hospitalization rates of children with pneumonia in the state of São Paulo, Brazil from 2009 to 2013. METHODS: This was an exploratory ecological study with data obtained from DATASUS of hospitalizations of children with pneumonia in the municipalities in São Paulo from 2009 to 2013/ Data on maternal education and family income were obtained and rates per thousand children were calculated and inserted in a database of municipalities obtained from IBGE. Thematic, kernel and Moran maps were constructed for the hospitalization rates and the Moran indices were calculated. The TerraView program was used for spatial analysis. RESULTS: A total of 43,809 children were hospitalized in the study period, with a minimum of zero and a maximum of 69,072. The mean rate per municipality was 11.51 ± 8.62 (SD). The Moran index was 0.21 (p = 0.01). The thematic map showed clusters in the northern, northwestern, midwestern and southwestern regions of the state; the kernel map showed a higher density of rates in the northwestern and midwestern areas, and the Moran map identified 39 municipalities that deserve the attention of municipal and regional managers. CONCLUSIONS: Geoprocessing identifies regions with higher hospitalization rates for pneumonia and also municipalities that deserve a high intervention priority.

OBJETIVO: Identificar padrões espaciais na distribuição das taxas de internação de crianças por pneumonia no estado de São Paulo, no período de 2009 a 2013. MÉTODOS: Estudo ecológico exploratório com dados obtidos do Departamento de Informática do Sistema Único de Saúde (DATASUS) de internações por pneumonia em crianças relativas aos municípios do estado de São Paulo de 2009 a 2013, dados de escolaridade materna e renda familiar; e foram criadas taxas por mil crianças e inseridas numa base digital de municípios obtida do Instituto Brasileiro de Geografia e Estatística. Foram construídos mapas temáticos, de Kernel e de Moran para as taxas de internação e calculados os índices de Moran. Foi utilizado o programa TerraView para a análise espacial. RESULTADOS: Foram internadas 43.809 crianças no período. A taxa média por município foi de 11,51 (DP = 8,62). O índice de Moran foi de 0,21 (p = 0,01). Há aglomerados nas regiões norte, noroeste, centro-oeste e sudoeste; o mapa de Kernel mostra densidade maior de taxas no noroeste e centro-oeste do estado; e o mapa de Moran identificou 39 municípios que merecem atenção por parte dos gestores municipais e regionais. CONCLUSÕES: O geoprocessamento permitiu identificar regiões com maiores taxas de internação por pneumonia e também municípios que merecem prioridade de intervenção.

DIFFERENT RESPONSE TO EXPOSURE TO AIR POLLUTANTS IN GIRLS AND BOYS.

OBJECTIVE: Identify the association between exposure to fine particulate matter and hospitalizations due to respiratory diseases in children up to ten years of age in the city of Cuiabá, Mato Grosso, stratifying the analysis by sex and calculating excess costs. METHODS: Ecological study of time series. The dependent variable was daily hospitalizations according to the 10th Revision of the International Classification of Diseases (ICD10): J04.0, J12.0 to J18.9, J20.0 to J21.9 and J45.0 to J45.0. The independent variables were the concentration of fine particulate, estimated by a mathematical model, temperature and relative air humidity, controlled by short and long-term trends. Generalized additive model of Poisson regression was used. Relative risks, proportional attributable risk (PAR) and excess hospitalizations and their respective costs by the population attributable fraction (PAF) were calculated. RESULTS: 1,165 children were hospitalized, 640 males and 525 females. The mean concentration, estimated by the mathematical model, was 15.1±2.9 mcg/m3 for PM2.5. For boys, there was no significant association; for girls a relative risk of up to 1.04 of daily hospitalizations due to respiratory diseases was observed for exposure to PM 2.5 in lags 1, 2 and 6. Increase of 5 µg/m3 in these concentrations increased the percentage of the risk in 18%; with an excess 95 hospital admissions and with excess expenses in the order of US$ 35 thousand. CONCLUSIONS: Significant effect in daily hospitalizations due to respiratory diseases related to exposure to fine particulate matter was noted for girls, suggesting the need for stratification by sex in further studies.

Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model.

Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was to develop and validate a fuzzy linguistic model for prediction of hospitalization due to respiratory diseases. We constructed a fuzzy model for prediction of hospitalizations due to pneumonia, bronchitis, bronchiolitis and asthma second exposure to fine particulate matter (PM2.5) in residents of Volta Redonda, RJ, in 2012. The model contains two inputs, PM2.5 and temperature, with three membership functions for each input, and an output with three membership functions for admissions, which were obtained from DATASUS. There were 752 hospitalizations in the period, the average concentration of PM2.5 was 17.1 µg/m3 (SD = 4.4). The model showed a good accuracy with PM2.5, the result was between 90% and 76.5% for lags 1, 2 and 3, a sensitivity of up to 95%. This study provides support for creating executable software with a low investment, along with the use of a portable instrument could allow number of hospital admission due to respiratory diseases and provide support to local health managers. Furthermore, the fuzzy model is very simple and involves low computational costs, an implementation making possible.

Fine particulate matter and ischemic heart diseases inrelation to sex. An ecological time series study.

BACKGROUND: Exposure to some air pollutants is associated with cardiovascular diseases. The objective of this study was to quantify the effect of exposure to fine particulate matter in hospitalizations due to ischemic heart disease and the costs to the healthcare system. DESIGN AND SETTING: Time-series ecological study conducted in Taubaté, Brazil. METHODS: Data on hospitalizations due to ischemic heart diseases (ICD I-20 to I-24) in the municipality of Taubaté (SP), Brazil, among adults of both sexes aged 40 years and over, from August 2011 to July 2012, were obtained from DATASUS. Fine particulate matter (PM2.5) concentrations were estimated from a mathematical model. Poisson regression was used in statistical analyses to estimate the relative risks of exposure to PM2.5 for both sexes and after stratification according to sex. The excess of hospitalizations and consequent excess expenditure for the healthcare system were calculated. RESULTS: There were 1040 admissions, among which 382 had ischemic heart diseases (257 males). Themean PM2.5 concentration was 13.2 µg/m3 (SD = 5.6). Significant effects from exposure were noted 4and 5 days after exposure (lag 4 and lag 5) for both sexes and for male sex; for female sex, the effect was 2 days after exposure (lag 2). There were 59 excess hospitalizations for an increase in PM2.5 concentration of 5 µg/m3 and excess expenditure of US$ 150,000 for the National Health System. CONCLUSIONS: An excess of hospital admissions due to ischemic heart disease, with excess expenditure, was identified consequent to PM2.5 exposure.

Spatial patterns of prematurity and its determinants in the metropolitan region of São Paulo, Brazil, 2010-2019 / Padrões espaciais da prematuridade e seus determinantes na região metropolitana de São Paulo, Brasil, 2010-2019

ABSTRACT Objective: To analyze spatial distribution of preterm births and their association with maternal, social, and health services indicators in the metropolitan region of São Paulo, Brazil, 2010-2019. Methods: Ecological study using data on preterm newborns from 39 municipalities in the metropolitan region of São Paulo. Univariate global Moran's index (Im) was used to evaluate spatial association of prematurity, and univariate local Moran's index by using the cluster map (LISA) to identify spatial patterns and clusters. Bivariate global Moran's index was also used to analyze spatial autocorrelation with maternal, social, and health services indicators. Results: A total of 3,103,898 live births were registered in period 2010-2019, of which 331,174 (10.7%) were preterm. The global Moran's index showed spatial independence (Im=0.05; p-value=0.233) of the proportion of preterm births between municipalities. However, in the local spatial analysis it was possible to identify a statistically significant spatial cluster between the municipalities of Biritiba Mirim, Guararema and Salesópolis, with high proportions of preterm births. In the bivariate analysis, a significant positive spatial association was identified with proportions of mothers under 20 years old (Im=0.17; p-value=0.024) and mothers with low schooling (Im=0.17; p-value=0.020), and a significant negative spatial association with HDI (Im=-0.14; p-value=0.039). Conclusions: The local spatial approach identified a spatial cluster located in the far east of the metropolitan region of São Paulo, where actions by health managers are needed to minimize occurrence of preterm births.

RESUMO Objetivo: Analisar a distribuição espacial dos nascimentos prematuros e sua associação com indicadores maternos, sociais e de serviços de saúde na região metropolitana de São Paulo, Brasil, 2010-2019. Métodos: Estudo ecológico utilizando dados sobre recém-nascidos pré-termo dos 39 municípios da região metropolitana de São Paulo. Utilizou-se o índice de Moran (Im) global univariado para avaliar a associação espacial da prematuridade, e o índice de Moran local univariado por meio do mapa de clusters (LISA) para a identificação de padrões e aglomerados espaciais. Também foi utilizado o índice de Moran global bivariado para analisar a autocorrelação espacial com os indicadores maternos, sociais e de serviços de saúde. Resultados: Foram registrados 3.103.898 nascidos vivos no período 2010-2019, dos quais 331.174 (10,7%) foram prematuros. O índice de Moran global mostrou independência espacial (Im=0,05; p-valor=0,233) da proporção dos nascimentos prematuros entre municípios. No entanto, na análise espacial local foi possível identificar aglomerado espacial estatisticamente significativo entre os municípios de Biritiba Mirim, Guararema e Salesópolis, com proporções altas de nascimentos pré-termo. Na análise bivariada, identificou-se associação espacial significativa positiva com proporções de mães menores de 20 anos (Im=0,17; p-valor=0,024) e mães com baixa escolaridade (Im=0,17; p-valor=0,020), e associação espacial significativa negativa com IDH (Im=-0,14; p-valor=0,039). Conclusão: A abordagem espacial local identificou agrupamento espacial situado no extremo leste da região metropolitana de São Paulo, onde ações dos gestores de saúde são necessárias para minimizar a ocorrência de partos prematuros.

Effects of exposure to air pollutants on children's health in Cuiabá, Mato Grosso State, Brazil. / Efeitos da exposição a poluentes do ar na saúde das crianças de Cuiabá, Mato Grosso, Brasil.

Exposure to air pollutants, usually measured by environmental agencies that are not present in all states, may be associated with respiratory admissions in children. An ecological time series study was conducted with data on hospitalizations due to selected respiratory diseases in children under 10 years of age in 2012 in the city of Cuiabá, Mato Grosso State, Brazil. Mean levels of fine particulate matter (PM2.5) were estimated with a mathematical model, data on low temperatures and relative humidity were obtained from the Brazilian National Institute of Meteorology, and the numbers of brush burnings were obtained from the Environmental Information System. The statistical approach used the Poisson regression generalized additive model with lags of 0 to 7 days. The financial costs and increases in hospitalizations due to increments in PM2.5 were estimated. There were 565 hospitalizations (mean 1.54 admissions/day; SD = 1.52), and mean PM2.5 concentration was 15.7µg/m3 (SD = 3.2). Associations were observed between exposure and hospitalizations in the second semester at lags 2 and 3, and at lag 2 when the entire year was analyzed. An increment of 5µg/m3 in PM2.5 was associated with an increase of 89 hospitalizations and costs exceeding BRL 95,000 (≈ USD 38,000) for the Brazilian Unified National Health System. Data estimated by mathematical models can be used in locations where pollutants are not monitored.

Exposição a poluentes do ar, que costumam ser quantificados por agências ambientais que não estão presentes em todos os estados, pode estar associada a internações por doenças respiratórias de crianças. Foi desenvolvido um estudo ecológico de séries temporais com dados referentes às internações por algumas doenças respiratórias de crianças menores de dez anos de idade, em 2012, na cidade de Cuiabá, Mato Grosso, Brasil. Os níveis médios de material particulado fino (PM2,5) foram estimados por modelo matemático, os dados de temperatura mínima e umidade relativa do ar foram obtidos do Instituto Nacional de Meteorologia, e número de focos de queimadas do Sistema de Informações Ambientais. A abordagem estatística utilizou o modelo aditivo generalizado da regressão de Poisson com defasagens de 0 a 7 dias. Foram estimados os custos financeiros e aumentos do número de internações decorrentes de elevações de PM2,5. Foram 565 internações (média de 1,54/dia; DP = 1,52) e concentração de PM2,5 de 15,7µg/m3 (DP = 3,2). Foram encontradas associações entre exposição e internações no segundo semestre, nos lags 2 e 3, e quando analisado o ano todo, no lag 2. Uma elevação de 5µg/m3 do PM2,5 implicou o aumento de 89 internações e custos acima dos R$ 95 mil para o Sistema Único de Saúde. Dados estimados por modelo matemático podem ser utilizados em locais onde não há monitoramento de poluentes.

La exposición a contaminantes del aire, que suelen ser cuantificados por agencias ambientales que no están presentes en todos los estados, puede estar asociada a internamientos por enfermedades respiratorias de niños. Se desarrolló un estudio ecológico de series temporales con datos referentes a los internamientos por algunas enfermedades respiratorias de niños menores de 10 años de edad, en 2012, en la ciudad de Cuiabá, Mato Grosso, Brasil. Los niveles medios de material particulado fino (PM2,5) se estimaron mediante un modelo matemático, los datos de temperatura mínima y humedad relativa del aire se obtuvieron del Instituto Nacional de Meteorología, y el número de focos de incendios del Sistema de Información Ambiental. El enfoque estadístico usó el modelo aditivo generalizado de la regresión de Poisson con desfases de 0 a 7 días. Se estimaron los costes financieros y aumentos del número de internamientos derivados de elevaciones de PM2,5. Fueron 565 internamientos (media de 1,54/día; DE = 1,52) y concentración de PM2,5 de 15,7µg/m3 (DE = 3,2). Se encontraron asociaciones entre exposición e internamientos en el segundo semestre, en los lags 2 y 3, y cuando se analizó todo el año, en el lag 2. Una elevación de 5µg/m3 del PM2,5 implicó el aumento de 89 internamientos y costes por encima de los BRL 95 mil para el Sistema Único de Salud. Los datos estimados por el modelo matemático pueden ser utilizados en lugares, donde no existe un monitoreo de contaminantes.

Exposure to NO2 and children hospitalization due to respiratory diseases in Ribeirão Preto, SP, Brazil.

The effects of exposure to air pollutants on human health are mainly reflected in respiratory diseases in children and elderly ones. An ecological time series study was carried out in Ribeirão Preto/SP data to examine the role of exposure to air pollutants and hospital admissions due to respiratory diseases in children under 10 years old. The study period was between January, 2011 and December, 2013. Particulate Matter (PM10), Nitrogen dioxide (NO2), and ozone (O3), temperature and air relative humidity, were analyzed to estimate the association with hospital admissions using a generalized linear model of Poisson's regression with lags of zero up to seven days after exposure to pollutants, adjusted by the day of the week, seasonality and effective temperature. The significance level adopted was p < 0.05. NO2, when analyzed in single pollutant model shown to be significant at lag 2 and 3 and when analyzed in the multi-pollutant model it shown to be significant at lags 2 up to 5, and lag 7 with relative risk between 1.05 and 1.09 per 10 µg/m3 increase in NO2 concentration, with an excess of 150 hospital admission and substantial increase in costs to Public Health System. The data enable the local health managers can take action to minimize these effects.

Accidents involving motorcycles and potential years of life lost. An ecological and exploratory study.

CONTEXT AND OBJECTIVE: Traffic accidents have gained prominence as one of the modern epidemics that plague the world. The objective of this study was to identify the spatial distribution of potential years of life lost (PYLL) due to accidents involving motorcycles in the state of São Paulo, Brazil. DESIGN AND SETTING: Ecological and exploratory study conducted in São Paulo. METHODS: Data on deaths among individuals aged 20-39 years due to motorcycle accidents (V20-V29 in the International Classification of Diseases, 10th revision) in the state of São Paulo in the years 2007-2011 were obtained from DATASUS. These data were stratified into a database for the 63 microregions of this state, according to where the motorcyclist lived. PYLL rates per 100,000 inhabitants were calculated. Spatial autocorrelations were estimated using the Global Moran index (IM). Thematic, Moran and Kernel maps were constructed using PYLL rates for the age groups of 20-29 and 30-39 years. The Terraview 4.2.2 software was used for the analysis. RESULTS: The PYLL rates were 486.9 for the ages of 20-29 years and 199.5 for 30-39 years. Seventeen microregions with high PYLL rates for the age group of 20-29 years were identified. There was higher density of these rates on the Kernel map of the southeastern region (covering the metropolitan region of São Paulo). There were no spatial autocorrelations between rates. CONCLUSIONS: The data presented in this study identified microregions with high accident rates involving motorcycles and microregions that deserve special attention from regional managers and traffic experts.

FUZZY COMPUTATIONAL MODELS TO EVALUATE THE EFFECTS OF AIR POLLUTION ON CHILDREN. / MODELOS COMPUTACIONAIS FUZZY PARA AVALIAR EFEITOS DA POLUIÇÃO DO AR EM CRIANÇAS.

OBJECTIVE: To build a fuzzy computational model to estimate the number of hospitalizations of children aged up to 10 years due to respiratory conditions based on pollutants and climatic factors in the city of São José do Rio Preto, Brazil. METHODS: A computational model was constructed using the fuzzy logic. The model has 4 inputs, each with 2 membership functions generating 16 rules, and the output with 5 pertinence functions, based on the Mamdani's method, to estimate the association between the pollutants and the number of hospitalizations. Data from hospitalizations, from 2011-2013, were obtained in DATASUS - and the pollutants Particulate Matter (PM10) and Nitrogen Dioxide (NO2), wind speed and temperature were obtained by the Environmental Company of São Paulo State (Cetesb). RESULTS: A total of 1,161 children were hospitalized in the period and the mean of pollutants was 36 and 51 µg/m3 - PM10 and NO2, respectively. The best values of the Pearson correlation (0.34) and accuracy measured by the Receiver Operating Characteristic (ROC) curve (NO2 - 96.7% and PM10 - 90.4%) were for hospitalizations on the same day of exposure. CONCLUSIONS: The model was effective in predicting the number of hospitalizations of children and could be used as a tool in the hospital management of the studied region.

OBJETIVO: Construir um modelo computacional fuzzy para estimar o número de internações de crianças até 10 anos por doenças respiratórias, com base nos dados de poluentes e fatores climáticos da cidade de São José do Rio Preto, Brasil. MÉTODOS: Foi construído modelo computacional utilizando a lógica fuzzy. O modelo tem 4 entradas, cada uma com 2 funções de pertinência gerando 16 regras, e a saída com 5 funções de pertinência, baseado no método de Mamdani, para estimar a associação entre os poluentes e o número de internações. Os dados de internações, de 2011-2013, foram obtidos no Departamento de Informática do Sistema de Saúde (DATASUS) e os poluentes material particulado (PM10) e dióxido de nitrogênio (NO2), a velocidade do vento e a temperatura foram obtidos pela Companhia Ambiental do Estado de São Paulo (Cetesb). RESULTADOS: Foram internadas 1.161 crianças no período analisado, e a média dos poluentes foi 36 e 51 µg/m3 - PM10 e NO2, respectivamente. Os melhores valores da correlação de Pearson (0,34) e da acurácia avaliada pela curva Receiver Operating Characteristic - ROC (NO2 - 96,7% e PM10 - 90,4%) foram para internações no mesmo dia da exposição. CONCLUSÕES: O modelo mostrou-se eficaz na predição do número de internações de crianças, podendo ser utilizado como ferramenta na gestão hospitalar da região estudada.

Association between exposure to air pollutants and hospitalization for SARS-Cov-2: an ecological time-series study

ABSTRACT BACKGROUND: Exposure to air pollutants and illness by severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection can cause serious pulmonary impairment. OBJECTIVE: To identify a possible association between exposure to air pollutants and hospitalizations due to SARS-Cov-2. DESIGN AND SETTING: Ecological time-series study carried out in Taubaté, Tremembé, and Pindamonhangaba in 2020 and 2021. METHODS: Study with Sars-Cov-2 hospitalizations with information on hospitalization date, sex and age of the subjects, duration of hospitalization, type of discharge, and costs of these hospitalizations. Statistical analysis was performed through a negative binomial regression, with data on pollutant concentrations, temperature, air relative humidity, and hospitalization date. Coefficients obtained by the analysis were transformed into relative risk for hospitalization, which estimated hospitalizations excess according to an increase in pollutant concentrations. RESULTS: There were 1,300 hospitalizations and 368 deaths, with a predominance of men (61.7%). These data represent an incidence rate of 250.4 per 100,000 inhabitants and 28.4% hospital lethality. Significant exposure (P value < 0.05) occurred seven days before hospital admission (lag 7) for nitrogen dioxide (NO2) (relative risk, RR = 1.0124) and two days before hospital admission for PM2.5 (RR = 1.0216). A 10 μg/m3 in NO2 concentration would decrease by 320 hospitalizations and ¼ US $ 240,000 in costs; a 5 μg/m3 in PM2.5 concentration would decrease by 278 hospitalizations and ¼ US $ 190,000 in costs. CONCLUSION: An association between exposure to air pollutants and hospital admission due to Sars-Cov-2 was observed with excess hospitalization and costs for the Brazilian public health system.