Hospitalizações sensíveis à atenção primária em menores de cinco anos

Objetivo: analisar em que medida o coeficiente de incidência das internações sensíveis a atenção primária em menores de cinco anos é influenciada pelo percentual de cobertura da Estratégia de Saúde da Família (ESF). Métodos: trata-se de um estudo ecológico de corte transversal que associa a cobertura da ESF e o coeficiente das internações sensíveis à atenção primária em 2000 e 2010. Utilizaram-se dados do Sistema de Informação Hospitalar (SIH) e o Sistema de Informação da Atenção Básica (SIAB). Resultados: Os dados revelaram que o aumento da cobertura da ESF proporcionou redução dos coeficientes de internação das doenças estudadas. Em 2000 a redução foi maior para as gastroenterites (51% em menores de 01 ano e 30% em crianças de 01 ”“ 04 anos), em 2010 para as doenças respiratórias (51% em menores de 01 ano e 33% em crianças de 01 ”“ 04 anos). Conclusão: constatou-se associação entre a cobertura da ESF e as taxas de internação, entretanto outras variáveis parecem interferir, evidenciando a necessidade de realização de outros estudos

The achievements of the SUS in tackling the communicable diseases

Apresenta-se a evolução da situação epidemiológica de algumas das principais Doenças transmissíveis (DT) no Brasil, assinalando as intervenções proporcionadas pelo SUS e outras políticas sociais. Dados e informações foram levantados do Datasus e Boletins epidemiológicos do Ministério da Saúde e de artigos científicos sobre o tema. A universalização, a descentralização e a ampliação das ações de vigilância, controle e prevenção de DT produziram impacto sobre a morbimortalidade dessas doenças, principalmente das imunopreveníveis. A emergência e reemergência de três arboviroses, para as quais não se dispõe de instrumentos de controle efetivos, interromperam a evolução decrescente no perfil de morbidade das DT no Brasil. Outros programas sociais e econômicos, voltados para a população brasileira mais carente, também contribuíram para a melhoria dos indicadores de saúde analisados. Contudo, a universalização do acesso aos serviços de atenção à saúde, ao lado do aperfeiçoamento do escopo de atuação da vigilância sobre doenças e riscos à saúde, vem desempenhando papel fundamental na melhoria das condições de saúde e qualidade de vida da população, bem como contribuindo para o processo de democratização do país.This article presents the development of the epidemiological situation of some of the major communicable diseases (CD) in Brazil, with emphasis on the interventions by the SUS and other social policies. The data and information were collected from Datasus, epidemiological newsletters from the Brazilian Ministry of Health, and scientific articles on the issue. The universalization, decentralization and expansion of the surveillance, control and prevention of CD has produced an impact on the morbidity and mortality of these diseases, mainly those which are vaccine-preventable. The emergence and re-emergence of three arboviruses, for which there are no effective control instruments, interrupted the downward trend in the morbidity profile of CD in Brazil. Other social and economic programs, which are geared to the needier sectors of the Brazilian population, have also contributed to the improvement of the analyzed health indicators. However, the universalization of access to healthcare services, as well as improvements in the scope of the surveillance of diseases and health risks, has played a key role in improving the health and quality of life of the population, as well as contributing to the process of the democratization of Brazil

Trends and factors associated with dengue mortality and fatality in Brazil.

INTRODUCTION: Studies that generate information that may reduce the dengue death risk are essential. This study analyzed time trends and risk factors for dengue mortality and fatality in Brazil from 2001 to 2011. METHODS: Time trends for dengue mortality and fatality rates were analyzed using simple linear regression. Associations between the dengue mortality and the case fatality rates and socioeconomic, demographic, and health care indicators at the municipality level were analyzed using negative binomial regression. RESULTS: The dengue hemorrhagic fever case fatality rate increased in Brazil from 2001 to 2011 (β=0.67; p=0.036), in patients aged 0-14 years (β=0.48; p=0.030) and in those aged ≥15 years (β=1.1; p<0.01). Factors associated with the dengue case fatality rate were the average income per capita (MRR=0.99; p=0.038) and the number of basic health units per population (MRR=0.89; p<0.001). Mortality rates increased from 2001 to 2011 (β=0.350; p=0.002).Factors associated with mortality were inequality (RR=1.02; p=0.001) high income per capita (MRR=0.99; p=0.005), and higher proportions of populations living in urban areas (MRR=1.01; p<0.001). CONCLUSIONS: The increases in the dengue mortality and case fatality rates and the associated socioeconomic and health care factors, suggest the need for structural and intersectoral investments to improve living conditions and to sustainably reduce these outcomes

Associations between Maternal Dietary Patterns and Infant Birth Weight in the NISAMI Cohort: A Structural Equation Modeling Analysis

The mother's diet during pregnancy is associated with maternal and child health. However, there are few studies with moderation analysis on maternal dietary patterns and infant birth weight. We aim to analyse the association between dietary patterns during pregnancy and birth weight. A prospective cohort study was performed with pregnant women registered with the prenatal service (Bahia, Brazil). A food frequency questionnaire was used to evaluate dietary intake. Birth weight was measured by a prenatal service team. Statistical analyses were performed using factor analysis with a principal component extraction technique and structural equation modelling. The mean age of the pregnant women was 27 years old (SD: 5.5) and the mean birth weight was 3341.18 g. It was observed that alcohol consumption (p = 0.05) and weight-gain during pregnancy (p = 0.05) were associated with birth weight. Four patterns of dietary consumption were identified for each trimester of the pregnancy evaluated. Adherence to the "Meat, Eggs, Fried Snacks and Processed foods" dietary pattern (pattern 1) and the "Sugars and Sweets" dietary pattern (pattern 4) in the third trimester directly reduced birth weight, by 98.42 g (Confidence interval (CI) 95%: 24.26, 172.59) and 92.03 g (CI 95%: 39.88, 165.30), respectively. It was also observed that insufficient dietary consumption in the third trimester increases maternal complications during pregnancy, indirectly reducing birth weight by 145 g (CI 95%: -21.39, -211.45). Inadequate dietary intake in the third trimester appears to have negative results on birth weight, directly and indirectly, but more studies are needed to clarify these causal paths, especially investigations of the influence of the maternal dietary pattern on the infant gut microbiota and the impacts on perinatal outcomes

The need for fast-track, high-quality and low-cost studies about the role of the BCG vaccine in the fight against COVID-19.

Bacillus Calmette-Guérin (BCG) vaccination is routine and near-universal in many low- and middle-income countries (LMIC). It has been suggested that BCG can have a protective effect on COVID-19 morbidity and mortality. This commentary discusses the limitations of the evidence around BCG and COVID-19. We argue that higher-quality evidence is necessary to understand the protective effect of the BCG vaccine from existing, secondary data, while we await results from clinical trials currently conducted in different settings

Network analysis of spreading of dengue, Zika and chikungunya in the state of Bahia based on notified, confirmed and discarded cases

Despite successful results of using complex networks to model and characterize the spread of dengue cases, works to date have mainly used data from primarily reported cases, without further consideration whether they were later confirmed or not. On the other hand, a study of the interdependence of confirmed and discarded cases of arboviruses have emphasized that the co-circulation of three arboviruses—dengue, Zika and chikungunya—may have led to false diagnoses due to several similarities in the early symptoms of the three diseases on acute phase. This implies that case notifications of one disease could be confirmed cases of others, and that discarded cases must be taken into account to avoid misinterpretations of the phenomenon. In this work we investigated the consequences of including information from discarded and confirmed cases in the analysis of arbovirus networks. This is done by firstly evaluating the possible changes in the networks after removing the discarded cases from the database of each arbovirus, and secondly by verifying the cross-relationship of the indices of the networks of confirmed and discarded cases of arboviruses. As will be detailed later on, our results reveal changes in the network indices when compared to when only confirmed cases are considered. The magnitudes of the changes are directly proportional to the amount of discarded cases. The results also reveal a strong correlation between the average degree of the networks of discarded cases of dengue and confirmed cases of Zika, but only a moderate correlation between that for networks of discarded cases of dengue and confirmed cases of chikungunya. This finding is compatible with the fact that dengue and Zika diseases are caused by closely related flaviviruses, what is not the case of the chikungunya caused by a togavirus

Complex network analysis of arboviruses in the same geographic domain: Differences and similarities.

Arbovirus can cause diseases with a broad spectrum from mild to severe and long-lasting symptoms, affecting humans worldwide and therefore considered a public health problem with global and diverse socio-economic impacts. Understanding how they spread within and across different regions is necessary to devise strategies to control and prevent new outbreaks. Complex network approaches have widespread use to get important insights on several phenomena, as the spread of these viruses within a given region. This work uses the motif-synchronization methodology to build time varying complex networks based on data of registered infections caused by Zika, chikungunya, and dengue virus from 2014 to 2020, in 417 cities of the state of Bahia, Brazil. The resulting network sets capture new information on the spread of the diseases that are related to the time delay in the synchronization of the time series among different municipalities. Thus the work adds new and important network-based insights to previous results based on dengue dataset in the period 2001-2016. The most frequent synchronization delay time between time series in different cities, which control the insertion of edges in the networks, ranges 7 to 14 days, a period that is compatible with the time of the individual-mosquito-individual transmission cycle of these diseases. As the used data covers the initial periods of the first Zika and chikungunya outbreaks, our analyses reveal an increasing monotonic dependence between distance among cities and the time delay for synchronization between the corresponding time series. The same behavior was not observed for dengue, first reported in the region back in 1986, either in the previously 2001-2016 based results or in the current work. These results show that, as the number of outbreaks accumulates, different strategies must be adopted to combat the dissemination of arbovirus infections

Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis.

The co-circulation of different arboviruses in the same time and space poses a significant threat to public health given their rapid geographic dispersion and serious health, social, and economic impact. Therefore, it is crucial to have high quality of case registration to estimate the real impact of each arboviruses in the population. In this work, a Vector Autoregressive (VAR) model was developed to investigate the interrelationships between discarded and confirmed cases of dengue, chikungunya, and Zika in Brazil. We used data from the Brazilian National Notifiable Diseases Information System (SINAN) from 2010 to 2017. There were three peaks in the series of dengue notification in this period occurring in 2013, 2015 and in 2016. The series of reported cases of both Zika and chikungunya reached their peak in late 2015 and early 2016. The VAR model shows that the Zika series have a significant impact on the dengue series and vice versa, suggesting that several discarded and confirmed cases of dengue could actually have been cases of Zika. The model also suggests that the series of confirmed and discarded chikungunya cases are almost independent of the cases of Zika, however, affecting the series of dengue. In conclusion, co-circulation of arboviruses with similar symptoms could have lead to misdiagnosed diseases in the surveillance system. We argue that the routinely use of mathematical and statistical models in association with traditional symptom-surveillance could help to decrease such errors and to provide early indication of possible future outbreaks. These findings address the challenges regarding notification biases and shed new light on how to handle reported cases based only in clinical-epidemiological criteria when multiples arboviruses co-circulate in the same population

Previous BCG vaccination is associated with less severe clinical progression of COVID-19

Background: BCG vaccination, originally used to prevent tuberculosis, is known to “train” the immune system to improve defence against viral respiratory infections. We investigated whether a previous BCG vaccination is associated with less severe clinical progression of COVID-19./ Methods: A case-control study comparing the proportion with a BCG vaccine scar (indicating previous vaccination) in cases and controls presenting with COVID-19 to health units in Brazil. Cases were subjects with severe COVID-19 (O2 saturation < 90%, severe respiratory effort, severe pneumonia, severe acute respiratory syndrome, sepsis, and septic shock). Controls had COVID-19 not meeting the definition of “severe” above. Unconditional regression was used to estimate vaccine protection against clinical progression to severe disease, with strict control for age, comorbidity, sex, educational level, race/colour, and municipality. Internal matching and conditional regression were used for sensitivity analysis./ Results: BCG was associated with high protection against COVID-19 clinical progression, over 87% (95% CI 74–93%) in subjects aged 60 or less and 35% (95% CI − 44–71%) in older subjects./ Conclusions: This protection may be relevant for public health in settings where COVID-19 vaccine coverage is still low and may have implications for research to identify vaccine candidates for COVID-19 that are broadly protective against mortality from future variants. Further research into the immunomodulatory effects of BCG may inform COVID-19 therapeutic research.

Combined association of obesity and other cardiometabolic diseases with severe COVID-19 outcomes: a nationwide cross-sectional study of 21 773 Brazilian adult and elderly inpatients.

OBJECTIVES: To investigate the combined association of obesity, diabetes mellitus (DM) and cardiovascular disease (CVD) with severe COVID-19 outcomes in adult and elderly inpatients. DESIGN: Cross-sectional study based on registry data from Brazil's influenza surveillance system. SETTING: Public and private hospitals across Brazil. PARTICIPANTS: Eligible population included 21 942 inpatients aged ≥20 years with positive reverse transcription-PCR test for SARS-CoV-2 until 9 June 2020. MAIN OUTCOME MEASURES: Severe COVID-19 outcomes were non-invasive and invasive mechanical ventilation use, intensive care unit (ICU) admission and death. Multivariate analyses were conducted separately for adults (20-59 years) and elders (≥60 years) to test the combined association of obesity (without and with DM and/or CVD) and degrees of obesity with each outcome. RESULTS: A sample of 8848 adults and 12 925 elders were included. Among adults, obesity with DM and/or CVD showed higher prevalence of invasive (prevalence ratio 3.76, 95% CI 2.82 to 5.01) and non-invasive mechanical ventilation use (2.06, 1.58 to 2.69), ICU admission (1.60, 1.40 to 1.83) and death (1.79, 1.45 to 2.21) compared with the group without obesity, DM and CVD. In elders, obesity alone (without DM and CVD) had the highest prevalence of ICU admission (1.40, 1.07 to 1.82) and death (1.67, 1.00 to 2.80). In both age groups, obesity alone and combined with DM and/or CVD showed higher prevalence in all outcomes than DM and/or CVD. A dose-response association was observed between obesity and death in adults: class I 1.32 (1.05 to 1.66), class II 1.41 (1.06 to 1.87) and class III 1.77 (1.35 to 2.33). CONCLUSIONS: The combined association of obesity, diabetes and/or CVD with severe COVID-19 outcomes may be stronger in adults than in elders. Obesity alone and combined with DM and/or CVD had more impact on the risk of COVID-19 severity than DM and/or CVD in both age groups. The study also supports an independent relationship of obesity with severe outcomes, including a dose-response association between degrees of obesity and death in adults