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BACKGROUND: Detecting and foreseeing pathogen dispersion is crucial in preventing widespread disease transmission. Human mobility is a fundamental issue in human transmission of infectious agents. Through a mobility data-driven approach, we aimed to identify municipalities in Brazil that could comprise an advanced sentinel network, allowing for early detection of circulating pathogens and their associated transmission routes. METHODS: In this modelling and validation study, we compiled a comprehensive dataset on intercity mobility spanning air, road, and waterway transport from the Brazilian Institute of Geography and Statistics (2016 data), National Transport Confederation (2022), and National Civil Aviation Agency (2017-23). We constructed a graph-based representation of Brazil's mobility network. The Ford-Fulkerson algorithm was used to rank the 5570 Brazilian cities according to their suitability as sentinel locations, allowing us to predict the most suitable locations for early detection and to track the most likely trajectory of a newly emerged pathogen. We also obtained SARS-CoV-2 genetic data from Brazilian municipalities during the early stage (Feb 25-April 30, 2020) of the virus's introduction and the gamma (P.1) variant emergence in Manaus (Jan 6-March 1, 2021), for the purposes of model validation. FINDINGS: We found that flights alone transported 79·9 million (95% CI 58·3-101·4 million) passengers annually within Brazil during 2017-22, with seasonal peaks occurring in late spring and summer, and road and river networks had a maximum capacity of 78·3 million passengers weekly in 2016. By analysing the 7â746â479 most probable paths originating from source nodes, we found that 3857 cities fully cover the mobility pattern of all 5570 cities in Brazil, 557 (10·0%) of which cover 6â313â380 (81·5%) of the mobility patterns in our study. By strategically incorporating mobility patterns into Brazil's existing influenza-like illness surveillance network (ie, by switching the location of 111 of 199 sentinel sites to different municipalities), our model predicted that mobility coverage would have a 33·6% improvement from 4â059â155 (52·4%) mobility patterns to 5â422â535 (70·0%) without expanding the number of sentinel sites. Our findings are validated with genomic data collected during the SARS-CoV-2 pandemic period. Our model accurately mapped 22 (51%) of 43 clade 1-affected cities and 28 (60%) of 47 clade 2-affected cities spread from São Paulo city, and 20 (49%) of 41 clade 1-affected cities and 28 (58%) of 48 clade 2-affected cities spread from Rio de Janeiro city, Feb 25-April 30, 2020. Additionally, 224 (73%) of the 307 suggested early-detection locations for pathogens emerging in Manaus corresponded with the first cities affected by the transmission of the gamma variant, Jan 6-16, 2021. INTERPRETATION: By providing essential clues for effective pathogen surveillance, our results have the potential to inform public health policy and improve future pandemic response efforts. Our results unlock the potential of designing country-wide clinical sample collection networks with mobility data-informed approaches, an innovative practice that can improve current surveillance systems. FUNDING: Rockefeller Foundation.
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COVID-19 , SARS-CoV-2 , Humanos , Brasil/epidemiologia , COVID-19/transmissão , COVID-19/epidemiologia , Cidades , Meios de TransporteRESUMO
The global economic downturn due to the COVID-19 pandemic, war in Ukraine, and worldwide inflation surge may have a profound impact on poverty-related infectious diseases, especially in low-and middle-income countries (LMICs). In this work, we developed mathematical models for HIV/AIDS and Tuberculosis (TB) in Brazil, one of the largest and most unequal LMICs, incorporating poverty rates and temporal dynamics to evaluate and forecast the impact of the increase in poverty due to the economic crisis, and estimate the mitigation effects of alternative poverty-reduction policies on the incidence and mortality from AIDS and TB up to 2030. Three main intervention scenarios were simulated-an economic crisis followed by the implementation of social protection policies with none, moderate, or strong coverage-evaluating the incidence and mortality from AIDS and TB. Without social protection policies to mitigate the impact of the economic crisis, the burden of HIV/AIDS and TB would be significantly larger over the next decade, being responsible in 2030 for an incidence 13% (95% CI 4-31%) and mortality 21% (95% CI 12-34%) higher for HIV/AIDS, and an incidence 16% (95% CI 10-25%) and mortality 22% (95% CI 15-31%) higher for TB, if compared with a scenario of moderate social protection. These differences would be significantly larger if compared with a scenario of strong social protection, resulting in more than 230,000 cases and 34,000 deaths from AIDS and TB averted over the next decade in Brazil. Using a comprehensive approach, that integrated economic forecasting with mathematical and epidemiological models, we were able to show the importance of implementing robust social protection policies to avert a significant increase in incidence and mortality from AIDS and TB during the current global economic downturn.
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Síndrome da Imunodeficiência Adquirida , Infecções por HIV , Modelos Teóricos , Tuberculose , Humanos , Tuberculose/prevenção & controle , Tuberculose/epidemiologia , Tuberculose/mortalidade , Tuberculose/economia , Brasil/epidemiologia , Infecções por HIV/epidemiologia , Infecções por HIV/prevenção & controle , Incidência , Síndrome da Imunodeficiência Adquirida/prevenção & controle , Síndrome da Imunodeficiência Adquirida/epidemiologia , COVID-19/epidemiologia , COVID-19/prevenção & controle , COVID-19/economia , PobrezaRESUMO
The COVID-19 pandemic highlighted the importance of international data sharing and access to improve health outcomes for all. The International COVID-19 Data Alliance (ICODA) programme enabled 12 exemplar or driver projects to use existing health-related data to address major research questions relating to the pandemic, and developed data science approaches that helped each research team to overcome challenges, accelerate the data research cycle, and produce rapid insights and outputs. These approaches also sought to address inequity in data access and use, test approaches to ethical health data use, and make summary datasets and outputs accessible to a wider group of researchers. This Health Policy paper focuses on the challenges and lessons learned from ten of the ICODA driver projects, involving researchers from 19 countries and a range of health-related datasets. The ICODA programme reviewed the time taken for each project to complete stages of the health data research cycle and identified common challenges in areas such as data sharing agreements and data curation. Solutions included provision of standard data sharing templates, additional data curation expertise at an early stage, and a trusted research environment that facilitated data sharing across national boundaries and reduced risk. These approaches enabled the driver projects to rapidly produce research outputs, including publications, shared code, dashboards, and innovative resources, which can all be accessed and used by other research teams to address global health challenges.
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COVID-19 , Saúde Global , Disseminação de Informação , COVID-19/epidemiologia , Humanos , Disseminação de Informação/métodos , Cooperação Internacional , Emergências , Pandemias , SARS-CoV-2RESUMO
Globally, millions of lives are impacted every year by infectious diseases outbreaks. Comprehensive and innovative surveillance strategies aiming at early alert and timely containment of emerging and reemerging pathogens are a pressing priority. Shortcomings and delays in current pathogen surveillance practices further disturbed informing responses, interventions, and mitigation of recent pandemics, including H1N1 influenza and SARS-CoV-2. We present the design principles of the architecture for an early-alert surveillance system that leverages the vast available data landscape, including syndromic data from primary health care, drug sales, and rumors from the lay media and social media to identify areas with an increased number of cases of respiratory disease. In these potentially affected areas, an intensive and fast sample collection and advanced high-throughput genome sequencing analyses would inform on circulating known or novel pathogens by metagenomics-enabled pathogen characterization. Concurrently, the integration of bioclimatic and socioeconomic data, as well as transportation and mobility network data, into a data analytics platform, coupled with advanced mathematical modeling using artificial intelligence or machine learning, will enable more accurate estimation of outbreak spread risk. Such an approach aims to readily identify and characterize regions in the early stages of an outbreak development, as well as model risk and patterns of spread, informing targeted mitigation and control measures. A fully operational system must integrate diverse and robust data streams to translate data into actionable intelligence and actions, ultimately paving the way toward constructing next-generation surveillance systems.
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Inteligência Artificial , Vírus da Influenza A Subtipo H1N1 , Humanos , Vírus da Influenza A Subtipo H1N1/genética , Mapeamento Cromossômico , Ciência de Dados , Surtos de Doenças/prevenção & controleRESUMO
INTRODUCTION: Housing-related factors can be predictors of health, including of diabetes outcomes. We analysed the association between subsidised housing residency and diabetes mortality among a large cohort of low-income adults in Brazil. RESEARCH DESIGN AND METHODS: A cohort of 9 961 271 low-income adults, observed from January 2010 to December 2015, was created from Brazilian administrative records of social programmes and death certificates. We analysed the association between subsidised housing residency and time to diabetes mortality using a Cox model with inverse probability of treatment weighting and regression adjustment. We assessed inequalities in this association by groups of municipality Human Development Index. Diabetes mortality included diabetes both as the underlying or a contributory cause of death. RESULTS: At baseline, the mean age of the cohort was 40.3 years (SD 15.6 years), with a majority of women (58.4%). During 29 238 920 person-years of follow-up, there were 18 775 deaths with diabetes as the underlying or a contributory cause. 340 683 participants (3.4% of the cohort) received subsidised housing. Subsidised housing residents had a higher hazard of diabetes mortality compared with non-residents (HR 1.17; 95% CI 1.05 to 1.31). The magnitude of this association was more pronounced among participants living in municipalities with lower Human Development Index (HR 1.30; 95% CI 1.04 to 1.62). CONCLUSIONS: Subsidised housing residents had a greater risk of diabetes mortality, particularly those living in low socioeconomic status municipalities. This finding suggests the need to intensify diabetes prevention and control actions and prompt treatment of the diabetes complications among subsidised housing residents, particularly among those living in low socioeconomic status municipalities.
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Diabetes Mellitus , Habitação , Humanos , Adulto , Feminino , Brasil/epidemiologia , Estudos Retrospectivos , Diabetes Mellitus/epidemiologiaRESUMO
Rheumatoid arthritis (RA) is a systemic autoimmune disease that impairs mobility. How does sensory information influence postural responses in people with RA? The aim of this study was to evaluate the postural control of people with RA during a sensory organization test, comparing how sensory information influences postural responses in people with rheumatoid arthritis compared with healthy people. Participants were 28 women with rheumatoid arthritis (RA group) and 16 women without any rheumatoid disease (Control group CG). The Sensory Organization Test (SOT) was performed on a Smart Balance Master® (NeuroCom International, Inc., Clackamas, OR, USA) and center of pressure (COP) was measured. SOT conditions: SOT1 (eyes open, fixed support surface and surround; SOT2) eyes closed, fixed support surface and surround; and SOT5) eyes closed, sway-referenced support surface, and fixed surround. To compare the demographic and clinical aspects between groups, independent t-test or Mann-Whitney's U-test were used. Differences were found between groups. Between SOT conditions, for CG and RA, COP was faster for SOT-5 than SOT-1, while SOT-1 and SOT-2 presented similar COP velocity. For SOT-2 and SOT-5, COP was larger for the RA group. For both groups, SOT-1 presented the smallest COP, and SOT-5 showed the largest COP.
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Manipulações Musculoesqueléticas , Equilíbrio Postural , Humanos , Feminino , Equilíbrio Postural/fisiologia , Modalidades de Fisioterapia , Grupos ControleRESUMO
OBJECTIVES: To classify the most up-to-date factors associated with COVID-19 disease outcomes in Brazil. DESIGN: Retrospective study. SETTING: Nationwide Brazilian COVID-19 healthcare registers. PARTICIPANTS: We used healthcare data of individuals diagnosed with mild/moderate (n=70 056 602) or severe (n=2801 380) COVID-19 disease in Brazil between 26 February 2020 and 15 November 2021. MAIN OUTCOME MEASURES: Risk of hospitalisation and mortality affected by demographic, clinical and socioeconomic variables were estimated. The impacts of socioeconomic inequalities on vaccination rates, cases and deaths were also evaluated. RESULTS: 15.6 million SARS-CoV-2 infection cases and 584 761 COVID-19-related deaths occurred in Brazil between 26 February 2020 and 15 November 2021. Overall, men presented a higher odds of death than women (OR=1.14, 95% CI 1.13 to 1.15), but postpartum patients admitted to hospital wards were at increased odds of dying (OR=1.23, 95% CI 1.13 to 1.34) compared with individuals without reported comorbidities. Death in younger age groups was notably higher in most deprived municipalities and also among individuals <40 years belonging to indigenous backgrounds compared with white patients, as shown by descriptive analysis. Ethnic/racial backgrounds exhibited a continuum of decreasing survival chances of mixed-race (OR=1.11, 95% CI 1.10 to 1.12), black (OR=1.34, 95% CI 1.32 to 1.36) and indigenous (OR=1.42, 95% CI 1.31 to 1.54) individuals, while those in most deprived municipalities also presented an increased odds of death (OR=1.38, 95% CI 1.36 to 1.40). Deprivation levels also affect the prompt referral of patients to adequate care. Our results show that the odds of death of individuals hospitalised for less than 4 days is more than double that of patients with close-to-average hospital stays (OR=2.07, 95% CI 2.05 to 2.10). Finally, negative vaccination status also increased the odds of dying from the disease (OR=1.29, 95% CI 1.28 to 1.31). CONCLUSIONS: The data provide evidence that the patterns of COVID-19 mortality in Brazil are influenced by both individual-level health and social risk factors, as well as municipality-level deprivation. In addition, these data suggest that there may be inequalities in the timely provision of appropriate healthcare that are related to municipality-level deprivation.
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COVID-19 , Masculino , Humanos , Feminino , Adulto , Estudos Retrospectivos , SARS-CoV-2 , Brasil/epidemiologia , Fatores de Risco , Fatores SocioeconômicosRESUMO
The collapse of overhead power line guyed towers is one of the leading causes of power grid failures, subjecting electricity companies to pay considerable, high-value fines. In this way, the current work proposes a novel and complete framework for the remote monitoring of mechanical stresses in guyed towers. The framework method comprises a mesh network for data forwarding and neural networks to improve the performance of Low-Power and Lossy Networks. The method also considers the use of multiple sensors in the sensor fusion technique. As a result, the risk of collapse of guyed cable towers reduces, due to the remote monitoring and preventive actions promoted by the framework. Furthermore, the proposed method uses multiple input variable fusions, such as accelerometers and tension sensors, to estimate the tower's displacement. These estimations help address the structural health of the tower against failures (i.e., loosening of the stay cables, displacement, and vibrations) that can cause catastrophic events, such as tower collapse or even cable rupture.
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Redes Neurais de ComputaçãoRESUMO
BACKGROUND: Leprosy remains concentrated among the poorest communities in low-and middle-income countries and it is one of the primary infectious causes of disability. Although there have been increasing advances in leprosy surveillance worldwide, leprosy underreporting is still common and can hinder decision-making regarding the distribution of financial and health resources and thereby limit the effectiveness of interventions. In this study, we estimated the proportion of unreported cases of leprosy in Brazilian microregions. METHODOLOGY/PRINCIPAL FINDINGS: Using data collected between 2007 to 2015 from each of the 557 Brazilian microregions, we applied a Bayesian hierarchical model that used the presence of grade 2 leprosy-related physical disabilities as a direct indicator of delayed diagnosis and a proxy for the effectiveness of local leprosy surveillance program. We also analyzed some relevant factors that influence spatial variability in the observed mean incidence rate in the Brazilian microregions, highlighting the importance of socioeconomic factors and how they affect the levels of underreporting. We corrected leprosy incidence rates for each Brazilian microregion and estimated that, on average, 33,252 (9.6%) new leprosy cases went unreported in the country between 2007 to 2015, with this proportion varying from 8.4% to 14.1% across the Brazilian States. CONCLUSIONS/SIGNIFICANCE: The magnitude and distribution of leprosy underreporting were adequately explained by a model using Grade 2 disability as a marker for the ability of the system to detect new missing cases. The percentage of missed cases was significant, and efforts are warranted to improve leprosy case detection. Our estimates in Brazilian microregions can be used to guide effective interventions, efficient resource allocation, and target actions to mitigate transmission.
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Hanseníase/epidemiologia , Teorema de Bayes , Brasil/epidemiologia , Humanos , Incidência , Hanseníase/economia , Fatores SocioeconômicosRESUMO
The SARS-CoV-2 pandemic triggered substantial economic and social disruptions. Mitigation policies varied across countries based on resources, political conditions, and human behavior. In the absence of widespread vaccination able to induce herd immunity, strategies to coexist with the virus while minimizing risks of surges are paramount, which should work in parallel with reopening societies. To support these strategies, we present a predictive control system coupled with a nonlinear model able to optimize the level of policies to stop epidemic growth. We applied this system to study the unfolding of COVID-19 in Bahia, Brazil, also assessing the effects of varying population compliance. We show the importance of finely tuning the levels of enforced measures to achieve SARS-CoV-2 containment, with periodic interventions emerging as an optimal control strategy in the long-term.
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COVID-19/prevenção & controle , Política Pública , Algoritmos , Brasil/epidemiologia , COVID-19/epidemiologia , COVID-19/patologia , COVID-19/virologia , Política de Saúde , Humanos , Modelos Teóricos , Pandemias , SARS-CoV-2/isolamento & purificaçãoRESUMO
COVID-19 is now identified in almost all countries in the world, with poorer regions being particularly more disadvantaged to efficiently mitigate the impacts of the pandemic. In the absence of efficient therapeutics or large-scale vaccination, control strategies are currently based on non-pharmaceutical interventions, comprising changes in population behavior and governmental interventions, among which the prohibition of mass gatherings, closure of non-essential establishments, quarantine and movement restrictions. In this work we analyzed the effects of 707 governmental interventions published up to May 22, 2020, and population adherence thereof, on the dynamics of COVID-19 cases across all 27 Brazilian states, with emphasis on state capitals and remaining inland cities. A generalized SEIR (Susceptible, Exposed, Infected and Removed) model with a time-varying transmission rate (TR), that considers transmission by asymptomatic individuals, is presented. We analyze the effect of both the extent of enforced measures across Brazilian states and population movement on the changes in the TR and effective reproduction number. The social mobility reduction index, a measure of population movement, together with the stringency index, adapted to incorporate the degree of restrictions imposed by governmental regulations, were used in conjunction to quantify and compare the effects of varying degrees of policy strictness across Brazilian states. Our results show that population adherence to social distance recommendations plays an important role for the effectiveness of interventions and represents a major challenge to the control of COVID-19 in low- and middle-income countries.
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COVID-19/prevenção & controle , COVID-19/transmissão , Controle de Doenças Transmissíveis/legislação & jurisprudência , SARS-CoV-2 , Número Básico de Reprodução , Brasil/epidemiologia , COVID-19/epidemiologia , Humanos , Modelos Teóricos , Política PúblicaRESUMO
Even in the period when the Covid-19 pandemic was on the rise in the Northeast of Brazil, the relaxation of social distancing measures was introduced. The scope of the study is to assess, in the light of the epidemiological-sanitary situation in the region, the suitability of relaxation of social distancing measures. Based on the WHO guidelines for relaxation of social distancing, operational indicators were created and analyzed for each guideline in the context of the Northeast. To analyze the behavior of the epidemic, according to selected indicators, Joinpoint trend analysis techniques, heat maps, rate ratios and time trends between capitals and the state interior were compared. The weekly growth peak of the epidemic occurred in May-July 2020 (epidemiological weeks 19 to 31). In most capitals, there was no simultaneous downward trend in the number of cases and deaths in the 14 days prior to flexibilization. In all states the number of tests performed was insufficient. In epidemiological week 24, the state percentages of ICU/Covid-19 bed occupancy were close to or above 70%. The epidemiological situation of the nine Northeastern state capitals analyzed here did not meet criteria and parameters recommended by the World Health Organization for the relaxation of social distancing measures.
Mesmo no período em que a pandemia de Covid-19 encontrava-se em crescimento no Nordeste do Brasil, iniciou-se a adoção de medidas de flexibilização do distanciamento social. O objetivo do estudo é o de avaliar a pertinência das propostas de flexibilização, tomando-se em conta a situação da pandemia em cada local e o momento em que foram adotadas. Tendo como referência as diretrizes da OMS, foram construídos e analisados indicadores operacionais para cada diretriz, no contexto da região Nordeste. Para análise do comportamento da epidemia, conforme indicadores selecionados, foram usadas técnicas de Joinpoint Trend Analysis, mapas de calor, razão de taxas e comparação da tendência temporal entre capitais e interior dos estados. O pico do crescimento semanal ocorreu em maio-julho/2020 (semanas epidemiológicas 19 a 31). Na maioria das capitais não se observou tendência decrescente simultânea do número de casos e óbitos nos 14 dias prévios à flexibilização. Em todos os estados o quantitativo de testes realizados foi insuficiente. Na semana epidemiológica 24 os percentuais estaduais de ocupação de leitos de UTI/Covid-19 foram próximos ou superiores 70%. A situação epidemiológica das nove capitais dos estados do Nordeste, no momento em que a decisão de flexibilização foi tomada, mostra que nenhuma delas atendia aos critérios e parâmetros recomendados pela OMS.
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COVID-19/epidemiologia , Pandemias , Distanciamento Físico , Ocupação de Leitos/estatística & dados numéricos , Brasil/epidemiologia , COVID-19/prevenção & controle , Controle de Doenças Transmissíveis , Humanos , Organização Mundial da SaúdeRESUMO
Zika virus was responsible for the microcephaly epidemic in Brazil which began in October 2015 and brought great challenges to the scientific community and health professionals in terms of diagnosis and classification. Due to the difficulties in correctly identifying Zika cases, it is necessary to develop an automatic procedure to classify the probability of a CZS case from the clinical data. This work presents a machine learning algorithm capable of achieving this from structured and unstructured available data. The proposed algorithm reached 83% accuracy with textual information in medical records and image reports and 76% accuracy in classifying data without textual information. Therefore, the proposed algorithm has the potential to classify CZS cases in order to clarify the real effects of this epidemic, as well as to contribute to health surveillance in monitoring possible future epidemics.
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Complicações Infecciosas na Gravidez/diagnóstico , Complicações Infecciosas na Gravidez/virologia , Infecção por Zika virus/complicações , Infecção por Zika virus/virologia , Zika virus , Gerenciamento Clínico , Suscetibilidade a Doenças , Feminino , Humanos , Recém-Nascido , Gravidez , Reprodutibilidade dos Testes , Avaliação de Sintomas , SíndromeRESUMO
COVID-19 is affecting healthcare resources worldwide, with lower and middle-income countries being particularly disadvantaged to mitigate the challenges imposed by the disease, including the availability of a sufficient number of infirmary/ICU hospital beds, ventilators, and medical supplies. Here, we use mathematical modelling to study the dynamics of COVID-19 in Bahia, a state in northeastern Brazil, considering the influences of asymptomatic/non-detected cases, hospitalizations, and mortality. The impacts of policies on the transmission rate were also examined. Our results underscore the difficulties in maintaining a fully operational health infrastructure amidst the pandemic. Lowering the transmission rate is paramount to this objective, but current local efforts, leading to a 36% decrease, remain insufficient to prevent systemic collapse at peak demand, which could be accomplished using periodic interventions. Non-detected cases contribute to a â½55% increase in R0. Finally, we discuss our results in light of epidemiological data that became available after the initial analyses.
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COVID-19/epidemiologia , Modelos Teóricos , Pandemias , SARS-CoV-2 , Doenças Assintomáticas , Brasil/epidemiologia , COVID-19/prevenção & controle , COVID-19/transmissão , Métodos Epidemiológicos , Hospitalização/estatística & dados numéricos , Humanos , Unidades de Terapia Intensiva , Distanciamento FísicoRESUMO
The new Covid-19 pandemic has left traces of suffering and devastation to individuals of almost all countries worldwide and severe impact on the global economy. Understanding the clinical characteristics, interactions with the environment, and the variables that favor or hinder its dissemination help the public authorities in the fight and prevention, leading for a rapid response in society. Using models to estimate contamination scenarios in real time plays an important role. Population compartments models based on ordinary differential equations (ODE) for a given region assume two homogeneous premises, the contact mechanisms and diffusion rates, disregarding heterogeneous factors as different contact rates for each municipality and the flow of contaminated people among them. This work considers a hybrid model for covid-19, based on local SIR models and the population flow network among municipalities, responsible for a complex lag dynamic in their contagion curves. Based on actual infection data, local contact rates ( ß ) are evaluated. The epidemic evolution at each municipality depends on the local SIR parameters and on the inter-municipality transport flow. When heterogeneity of ß values and flow network are included, forecasts differ from those of the homogeneous ODE model. This effect is more relevant when more municipalities are considered, hinting that the latter overestimates new cases. In addition, mitigation scenarios are assessed to evaluate the effect of earlier interventions reducing the inter-municipality flux. Restricting the flow between municipalities in the initial stage of the epidemic is fundamental for flattening the contamination curve, highlighting advantages of a contamination lag between the capital curve and those of other municipalities in the territories.
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Zika virus (ZIKV) became a worldwide public health emergency after its introduction in the Americas. Brazil was implicated as central in the ZIKV dispersion, however, a better understanding of the pathways the virus took to arrive in Brazil and the dispersion within the country is needed. An updated genome dataset was assembled with publicly available data. Bayesian phylogeography methods were applied to reconstruct the spatiotemporal history of ZIKV in the Americas and with more detail inside Brazil. Our analyses reconstructed the Brazilian state of Pernambuco as the likely point of introduction of ZIKV in Brazil, possibly during the 2013 Confederations Cup. Pernambuco played an important role in spreading the virus to other Brazilian states. Our results also underscore the long cryptic circulation of ZIKV in all analyzed locations in Brazil. Conclusions: This study brings new insights about the early moments of ZIKV in the Americas, especially regarding the Brazil-Haiti cluster at the base of the American clade and describing for the first time migration patterns within Brazil.
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Infecção por Zika virus/epidemiologia , Infecção por Zika virus/virologia , Zika virus/fisiologia , América/epidemiologia , Brasil/epidemiologia , Surtos de Doenças , Genoma Viral , Humanos , Filogenia , Filogeografia , Vigilância em Saúde Pública , Análise Espaço-Temporal , Zika virus/classificaçãoRESUMO
BACKGROUND: The clinical manifestations of microcephaly/congenital Zika syndrome (microcephaly/CZS) have harmful consequences on the child's health, increasing vulnerability to childhood morbidity and mortality. This study analyzes the case fatality rate and child-maternal characteristics of cases and deaths related to microcephaly/CZS in Brazil, 2015-2017. METHODS: Population-based study developed by linkage of three information systems. We estimate frequencies of cases, deaths, case fatality rate related to microcephaly/CZS according to child and maternal characteristics and causes of death. Multivariate logistic regression models were applied. RESULTS: The microcephaly/CZS case fatality rate was 10% (95% CI 9.2-10.7). Death related to microcephaly/CZS was associated to moderate (OR = 2.15; 95% CI 1.63-2.83), and very low birth weight (OR = 3.77; 95% CI 2.20-6.46); late preterm births (OR = 1.65; 95% CI 1.21-2.23), Apgar < 7 at 1st (OR = 5.98; 95% CI 4.46-8.02) and 5th minutes (OR = 4.13; 95% CI 2.78-6.13), among others. CONCLUSIONS: A high microcephaly/CZS case fatality rate and important factors associated with deaths related to this syndrome were observed. These results can alert health teams to these problems and increase awareness about the factors that may be associated with worse outcomes.
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Microcefalia/mortalidade , Complicações Infecciosas na Gravidez/virologia , Infecção por Zika virus/mortalidade , Adolescente , Adulto , Brasil/epidemiologia , Feminino , Humanos , Modelos Logísticos , Masculino , Prontuários Médicos , Pessoa de Meia-Idade , Gravidez , Estudos Retrospectivos , Fatores de Risco , Adulto Jovem , Infecção por Zika virus/congênito , Infecção por Zika virus/epidemiologiaRESUMO
The COVID-19 pandemic has been most severe in the poorest regions of Brazil, such as the states of the Northeast Region. The lack of national policies for pandemic control forced state and municipal authorities to implement public health measures. The aim of this study is to show the effect of these measures on the epidemic. The highest incidence of COVID-19 among the nine states in the Northeast was recorded in Sergipe, Paraíba and Ceará. Piauí, Paraíba and Ceará were the states that most tested. Factors associated with transmission included the high proportion of people in informal work. States with international airports played an important role in the entry of the virus and the initial spread, especially Ceará. All states applied social distancing measures, banned public events and closed schools. The response was a significant increase in social distancing, especially in Ceará and Pernambuco, a decline in the reproduction rate (Rt), and a separation of the curve of observed cases versus expected cases if the non-pharmacological interventions had not been implemented in all states. Poverty, inequality, and the high rates of informal work provide clues to the intensity of COVID-19 in the region. On the other hand, the measures taken early by the governments mitigated the effects of the pandemic.
No Brasil, a pandemia da COVID-19 tem sido severa nos estados das regiões mais pobres, como o Nordeste. A falta de políticas nacionais para controle da pandemia levou as autoridades estaduais e municipais a implementarem medidas de saúde pública. O objetivo deste estudo é mostrar o efeito dessas medidas na epidemia. A maior incidência da COVID-19 entre os nove estados do Nordeste foi registrada em Sergipe, Paraíba e Ceará. O Piauí, a Paraíba e Ceará foram os que mais testaram. Muitos estados apresentavam alta proporção de pessoas em trabalho informal. Estados com aeroportos internacionais tiveram importante papel na entrada e disseminação inicial do vírus, em especial o Ceará. Todos os estados aplicaram medidas de distanciamento social, proibição de eventos públicos e fechamento de unidades de ensino. As respostas foram o aumento significativo de distanciamento social, em especial Ceará e Pernambuco, a queda do número de reprodução (Rt) e a separação da curva dos casos observados da curva dos casos esperados sem as intervenções não medicamentosas em todos os estados. A pobreza, a desigualdade e as altas taxas de trabalho informal fornecem pistas do porquê da intensidade da COVID-19 na região. Por outro lado, as medidas de mitigação tomadas precocemente pelos governantes amenizaram os efeitos da pandemia.
Assuntos
Betacoronavirus , Controle de Doenças Transmissíveis/métodos , Infecções por Coronavirus/prevenção & controle , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Política Pública , Brasil/epidemiologia , COVID-19 , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/transmissão , Humanos , Pneumonia Viral/epidemiologia , Pneumonia Viral/transmissão , Pobreza/estatística & dados numéricos , Quarentena , SARS-CoV-2 , Governo Estadual , Abastecimento de ÁguaRESUMO
Resumo Objetivo: Observar o grau de concordância das variáveis analisadas entre os dispositivos IOL Master 500 e Pentacam AXL e descrever as medias Métodos: Foram analisados 35 prontuários, totalizando 61 olhos. Todos os pacientes se submeteram à avaliação biométrica nos dois dispositivos, no período de agosto de 2018 a agosto de 2019. Os dados coletados foram: idade, sexo, profundidade da câmara anterior, comprimento axial, K1, K2, poder dióptrico da LIO e alvo refracional. Resultados: As médias das variáveis analisadas entre os dispositivos de biométricos óptica em questão tiveram diferença estatisticamente significante (p<0,05). A regressão linear não apontou influência de nenhuma das variáveis da câmara anterior na diferença de valores do poder dióptrico da LIO e do alvo refracional entre os dispositivos. Conclusão: Não houve concordância estatística entre os dispositivos para as variáveis analisadas. Portanto, deve se evitar intercambiar o uso do Pentacam AXL com o IOL Master 500.
Abstract Objective: Observe the agreement between IOL Master 500 and Pentacam AXL and describe the averages. Methods: We analyzed 35 medical records, totaling 61 eyes. All patients underwent biometric evaluation on both devices from August 2018 to August 2019. The data collected were: age, gender, anterior chamber depth, axial length, K1, K2, biometrics and IOL target. Results: The averages of the variables analyzed between the optical biometric devices in question had a statistically significant difference (p <0.05). Linear regression showed no influence of any anterior chamber variables on the difference in biometrics and target values between the devices. Conclusion: There was no statistical agreement between the devices for the analyzed variables. Therefore, the interchange of Pentacam AXL with IOL Master 500 should be avoided.