In Brazil, Dengue (DENV) and Zika (ZIKV) viruses are reported as being transmitted exclusively by Aedes aegypti in urban settings. This study established the vectors and viruses involved in an arbovirus outbreak that occurred in 2019 in a rural area of Espírito Santo state, Brazil. Mosquitoes collected were morphologically identified, sorted in samples, and submitted to molecular analysis for arboviruses detection. Phylogenetic reconstruction was performed for the viral sequence obtained. All 393 mosquitoes were identified as Aedes albopictus. DENV-1 genotype V was present in one sample and another sample was positive for ZIKV. The DENV-1 clustered with viruses that have circulated in previous years in large urban centers of different regions in Brazil. This is the first report of A. albopictus infected by DENV and ZIKV during an outbreak in a rural area in Brazil, indicating its involvement in arboviral transmission. The DENV-1 strain found in the A. albopictus was not new in Brazil, being involved previously in epidemics related to A. aegypti, suggesting the potential to A. albopictus in transmitting viruses already circulating in the Brazilian population. This finding also indicates the possibility of these viruses to disperse across urban and rural settings, imposing additional challenges for the control of the diseases.
Objective: To analyze the survival of patients hospitalized with COVID-19 and its associated factors. Methods: Retrospective study of survival analysis in individuals notified and hospitalized with COVID-19 in the state of Espírito Santo, Brazil. As data source, the reports of hospitalized patients in the period from 1 March 2020, to 31 July 2021 were used. The Cox regression analysis plus the proportional risk assessment (assumption) were used to compare hospitalization time until the occurrence of the event (death from COVID-19) associated with possible risk factors. Results: The sample comprised 9806 notifications of cases, with the occurrence of 1885 deaths from the disease (19.22%). The mean age of the group was 58 years (SD ± 18.3) and the mean hospital length of stay was 10.5 days (SD ± 11.8). The factors that presented a higher risk of death from COVID-19, associated with a lower survival rate, were non-work-related infection (HR = 4.33; p < 0.001), age group 60–79 years (HR: 1.62; p < 0.001) and 80 years or older (HR = 2.56; p < 0.001), presence of chronic cardiovascular disease (HR = 1.18; p = 0.028), chronic kidney disease (HR = 1.5; p = 0.004), smoking (HR = 1.41; p < 0.001), obesity (HR = 2.28; p < 0.001), neoplasms (HR = 1.81; p < 0.001) and chronic neurological disease (HR = 1.68; p < 0.001). Conclusion: It was concluded that non-work-related infection, age group above or equal to 60 years, presence of chronic cardiovascular disease, chronic kidney disease, chronic neurological disease, smoking, obesity and neoplasms were associated with a higher risk of death, and, therefore, a lower survival in Brazilian patients hospitalized with COVID-19. The identification of priority groups is crucial for Health Surveillance and can guide prevention, control, monitoring, and intervention strategies against the new coronavirus.
Objective: To analyze COVID-19 deaths in public hospitals in a Brazilian state, stratified by the three waves of the pandemic, and to test their association with socio-clinical variables. Methods: Observational analytical study, where 5436 deaths by COVID-19 occurred in hospitals of the public network of Espírito Santo, between 1 April 2020, and 31 August 2021, stratified by the three waves of the pandemic, were analyzed. For the bivariate analyses, the Pearson’s chi-square, Fisher’s Exact or Friedman’s tests were performed depending on the Gaussian or non-Gaussian distribution of the data. For the relationship between time from diagnosis to death in each wave, quantile regression was used, and multinomial regression for multiple analyses. Results: The mean time between diagnosis and death was 18.5 days in the first wave, 20.5 days in the second wave, and 21.4 days in the third wave. In the first wave, deaths in public hospitals were associated with the following variables: immunodeficiency, obesity, neoplasia, and origin. In the second wave, deaths were associated with education, O2 saturation < 95%, chronic neurological disease, and origin. In the third wave, deaths were associated with race/color, education, difficulty breathing, nasal or conjunctival congestion, irritability or confusion, adynamia or weakness, chronic cardiovascular disease, neoplasms, and diabetes mellitus. Origin was associated with the outcome in the three waves of the pandemic, in the same way that education was in the second and third waves (p < 0.05). Conclusion: The time interval between diagnosis and death can be impacted by several factors, such as: plasticity of the health system, improved clinical management of patients, and the start of vaccination at the end of January 2021, which covered the age group with the higher incidence of deaths. The deaths occurring in public hospitals were associated with socio-clinical characteristics.
Para descrever a distribuição temporal e espacial da Chikungunya no estado do Espírito Santo foi realizado um estudo descritivo e ecológico, entre 2014 e 2017. Foram analisadas as notificações do SINAN e os resultados laboratoriais do GAL, organizados pelo programa Excel e analisados pelo programa SPSS e o software ArcGIS para construir os mapas. Registrou-se um aumento progressivo dos casos desde 2015, com a incidência em 2017 (12,8/100mil habitantes) dobrando em relação a 2016 (6,3/100mil habitantes). Dos pacientes confirmados 392 (66,9%) foram mulheres e 194 (33,1%) homens. A cor parda foi a mais frequente e 15% da população tinha escolaridade de ensino médio completo. A faixa etária de 41 a 60 anos foi a mais acometida. Os sinais e sintomas mais comuns foram: febre (85,5%), artralgia (79,7%), mialgia (78,3%), cefaléia (67,4%). Cerca de 16,4% da população descrevia alguma comorbidade. Foram confirmados 288 (49,1%) por exames laboratoriais. O caráter epidêmico da Chikungunya com elevada taxa de morbidade associada à artralgia persistente, tendo como consequência a redução da produtividade e da qualidade de vida,apontam a necessidade dos serviços de saúde se organizarem para o melhor enfrentamento da doença e disponibilizar um atendimento adequado, multiprofissional e ofertado na atenção primária de saúde.
Health information is particularly essential in times of pandemics in which rapid response is crucial for political and stakeholder decision-making processes, and therefore the availability of data as well as its quality analysis are necessary. This study aimed to describe the completeness and quality of the e-Sistema Único de Saúde (SUS) Health Surveillance database (SUS Vigilância em Saúde) of the state of Espírito Santo, Brazil, from the notification of deaths from corana virus disease 2019 (COVID-19) from January 2020 to June 2021. A descriptive population-based register study was conducted from the analysis of the completeness of secondary data from the record of deaths from COVID-19, retrieved from the e-SUS Vigilância em Saúde (Health Surveillance) (VS) database of the state of Espírito Santo, Brazil, from January 2020 to June 2021. A total of 11,359 death records from COVID-19 via e-SUS VS in the state of Espírito Santo, Brazil, were evaluated. The score used to assess incompleteness was the 1 proposed by Romero and Cunha which classifies as excellent (when < 5%), good (between 5% and 10%), regular (between 10% and 20%), poor (between 20% and 50%), and very poor (when > 50%), according to the percentage of the absence of information. Descriptive statistical analyses were conducted in the Stata program, version 15.1. “Case identification” variables, and “condition” variables were classified as excellent completeness. Among the evolution variables, only “hospitalization” was classified as regular. Among the laboratory variables, only the polymerase chain reaction presented excellent completeness, while the “rapid test” and “serologies for immunoglobulin G, and immunoglobulin M” variables were classified as good completeness. It is concluded that most of the variables available in e-SUS VS of the state of Espírito Santo, Brazil, of notification of deaths from COVID-19 in 2020 presented excellent completeness, confirming the excellent quality of the state database.
ResumoPara descrever a distribuição temporal e espacial da Chikungunya, no estado do Espírito Santo, foi realizado um estudo descritivo e ecológico, entre 2014 e 2017. Foram analisadas as notificações do SINAN -Sistema de Informação de Agravos de Notificação, organizadas pelo programa Excel e analisadas pelo programa SPSS e o software ArcGIS para construir os mapas. Registrou-se um aumento progressivo dos casos desde 2015, com a incidência em 2017 (12,8/100mil habitantes) dobrando em relação a 2016 (6,3/100mil habitantes). Dos pacientes confirmados, 392 (66,9%) foram mulheres e 194 (33,1%) homens. A cor parda foi a mais frequente e 15% da população tinha escolaridade de ensino médio completo. A faixa etária de 41 a 60 anos foi a mais acometida. Os sinais e sintomas mais comuns foram: febre (85,5%), artralgia (79,7%), mialgia (78,3%), cefaléia (67,4%). Cerca de 16,4% da população descrevia alguma comorbidade. Foram confirmados 288 (49,1%) por exames laboratoriais. O caráter epidêmico da Chikungunya com elevada taxa de morbidade associada à artralgia persistente, tendo como consequência a redução da produtividade e da qualidade de vida, apontam a necessidade dos serviços de saúde se organizarem para o melhor enfrentamento da doença e disponibilizar um atendimento adequado, multiprofissional e ofertado na atenção primária de saúde. AbstractIn order to describe the temporal and spatial distribution of Chikungunya in Espírito Santo, it was made an observational study between 2014 and 2017. We analyzed the notifications in SINAN and organized it at the Excel program. Then, the data were analyzed by SPSS and Arc-GIS software to construct the maps. A progressive rise in the numbers of cases was registered since 2015, and the incidence in 2017 (12,8/100.000 habitants) doubled in relation to 2016 (6,3/100.000 habitants). From the confirmed patients, 392 (66,9%) were women and 194 (33,1%) were men. The brown-skinned people and those between 41-60 year-old were the most affected and 15% of the population had high-school level of education. The most common signs and symptoms were: fever (85,5%), arthralgias (79,7%), myalgias (78,3%), headache (67,4%). Approximately 16,4% of the population informed any comorbidity. 288 cases (49,1%) were confirmed by laboratory. The epidemic profile of Chikungunya, with high morbidity rates, associated to persistent arthralgias, resulting in productivity reduction and quality of life, suggest the urgent need of better organization of the health services to face the disease and provide an appropriate and multiprofessional service in public health departments.
Introdução: O adequado e sistemático acompanhamento dos casos de COVID-19 ocorre por meio da utilização de um sistema de informação qualificado. A notificação dos casos de COVID-19 no Espírito Santo se deu por um sistema próprio de informação em saúde instituído em janeiro de 2020, o e-SUS Vigilância em Saúde (e-SUS VS). Por ele foi possível monitorar os casos notificados mais rapidamente assim como os grupos de risco, como as gestantes que demonstraram alta incidência e mortalidade materna por essa doença. Objetivo: Descrever a qualidade e oportunidade dos dados de notificação de COVID-19 em gestantes, obtidos através do novo sistema de informação e-SUS VS implantado no Espírito Santo. Métodos: Estudo descritivo utilizando-se de dados obtidos através do e-SUS VS. A completude no preenchimento da notificação foi classificada como excelente (menos de 5% de preenchimento incompleto), bom (5% a 10%), regular (10% a 20%), ruim (20% a 50%) ou muito ruim (50% ou mais). A oportunidade foi definida pela diferença entre as datas do início de sintomas e a notificação. Resultados: Identificou-se 8.989 notificações em gestantes. A notificação para COVID-19 do e-SUS VS possui 59 variáveis, a completude de 53 (89,83%) variáveis foi excelente, boa e regular em 1 (1,70%), e ruim em 4 (6,77%). A oportunidade obteve média de 3,37 dias. Conclusão: A qualidade dos dados do e-SUS VS foi excelente, tornando-o uma importante fonte de informações para subsidiar ações e de aprimoramento de políticas públicas voltadas a esse grupo de risco.
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