Carlos Dornels Freire De Dornels Freire de Souza

Dr. Carlos Dornels Freire De Dornels Freire de Souza

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Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 November 2020 in Wiener klinische Wochenschrift
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RMRodrigo da Rosa Mesquita
Rodrigo da Rosa Mesquita
LJLuiz Carlos Francelino Silva Junior
Luiz Carlos Francelino Silva Junior
FSFernanda Mayara Santos Santana
Fernanda Mayara Santos Santana
TOTatiana Farias de Oliveira
Tatiana Farias de Oliveira
RARafaela Campos Alcântara
Rafaela Campos Alcântara
CSCarlos Dornels Freire De Dornels Freire de Souza
Carlos Dornels Freire De Dornels Freire de Souza

31 August 2020 in Infectious Diseases of Poverty
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CSCarlos Dornels Freire De Dornels Freire de Souza
Carlos Dornels Freire De Dornels Freire de Souza
MMMichael Ferreira Machado
Michael Ferreira Machado
RCRodrigo Feliciano Do Carmo
Rodrigo Feliciano Do Carmo
Background: Coronavirus disease 2019 (COVID-19) was confirmed in Brazil in February 2020. Since then, the disease has spread throughout the country, reaching the poorest areas. This study analyzes the relationship between COVID-19 and the population’s living conditions. We aimed to identify social determinants related to the incidence, mortality, and case fatality rate of COVID-19 in Brazil, in 2020. Methods: This is an ecological study evaluating the relationship between COVID-19 incidence, mortality, and case fatality rates and 49 social indicators of human development and social vulnerability. For the analysis, bivariate spatial correlation and multivariate and spatial regression models (spatial lag model and spatial error models) were used, considering a 95% confidence interval and a significance level of 5%. Results: A total of 44.8% of municipalities registered confirmed cases of COVID-19 and 14.7% had deaths. We observed that 56.2% of municipalities with confirmed cases had very low human development (COVID-19 incidence rate: 59.00/100 000; mortality rate: 36.75/1 000 000), and 52.8% had very high vulnerability (COVID-19 incidence rate: 41.68/100 000; mortality rate: 27.46/1 000 000). The regression model showed 17 indicators associated with transmission of COVID-19 in Brazil. Conclusions: Although COVID-19 first arrived in the most developed and least vulnerable municipalities in Brazil, it has already reached locations that are farther from large urban centers, whose populations are exposed to a context of intense social vulnerability. Based on these findings, it is necessary to adopt measures that take local social aspects into account in order to contain the pandemic.

1 November 2020 in The International Journal of Tuberculosis and Lung Disease
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CSCarlos Dornels Freire De Dornels Freire de Souza
Carlos Dornels Freire De Dornels Freire de Souza
HCH. S. Coutinho
H. S. Coutinho
MCM. M. Costa
M. M. Costa
MMM. A. F. M. Magalhães
M. A. F. M. Magalhães
RCR. F. Carmo
R. F. Carmo

1 January 2020 in Brazilian Oral Research
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Journal Article
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CSCarlos Dornels Freire De Dornels Freire de Souza
Carlos Dornels Freire De Dornels Freire de Souza
VGVanessa Tavares de Gois-Santos
Vanessa Tavares de Gois-Santos
DCDivanise Suruagy Correia
Divanise Suruagy Correia
PMPaulo Ricardo Martins-Filho
Paulo Ricardo Martins-Filho
VSVictor Santana Santos
Victor Santana Santos
The emergence of severe acute respiratory coronavirus 2 (SARS-CoV-2) and its association with severe pneumonia and deaths has exposed gaps in the health systems of several countries worldwide. Although the necessary focus has been to care for hospitalized patients, the strengthening of Primary Health Care (PHC) actions is necessary. PHC is the gateway to the health system in several countries, including Brazil and it plays a role in preventing, protecting, promoting, and treating individuals and communities. Brazil, like other countries, has faced the SARS-CoV-2 pandemic. As Brazil has a universal and decentralized health system, in which PHC has been the model of health re-organizing the health system; here we reflected the importance of strengthening PHC in Brazil in the times of coronavirus disease 2019 pandemic.

25 January 2022 in PLOS ONE
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JPJoão Paulo Silva de Paiva
João Paulo Silva de Paiva
MMMônica Avelar Figueiredo Mafra Magalhães
Mônica Avelar Figueiredo Mafra Magalhães
TLThiago Cavalcanti Leal
Thiago Cavalcanti Leal
LSLeonardo Feitosa da Silva
Leonardo Feitosa da Silva
LSLucas Gomes da Silva
Lucas Gomes da Silva
CSCarlos Dornels Freire De Dornels Freire de Souza
Carlos Dornels Freire De Dornels Freire de Souza
Introduction: Tuberculosis is one of the ten leading causes of death and the leading infectious cause worldwide. The disease represents a challenge to health systems around the world. In 2018, it is estimated that 10 million people were affected by tuberculosis, and approximately 1.5 million people died due to the disease worldwide, including 251,000 patients coinfected with HIV. In Brazil, the disease caused 4,490 deaths, with rate of 2.2 deaths per 100,000 inhabitants. The objective of this study was to analyze the time behavior, spatial, spatial-temporal distribution, and the effects of social vulnerability on the incidence of TB in Brazil during the period from 2001 to 2017. Materials and methods: A spatial-temporal ecological study was conducted, including all new cases of tuberculosis registered in Brazil during the period from 2001 to 2017. The following variables were analyzed: incidence rate of tuberculosis, the Social Vulnerability Index, its subindices, its 16 indicators, and an additional 14 variables available on the Atlas of Social Vulnerability. The statistical treatment of the data consisted of the following three stages: a) time trend analysis with a joinpoint regression model; b) spatial analysis and identification of risk areas based on smoothing of the incidence rate by local empirical Bayesian model, application of global and local Moran statistics, and, finally, spatial-temporal scan statistics; and c) analysis of association between the incidence rate and the indicators of social vulnerability. Results: Brazil reduced the incidence of tuberculosis from 42.8 per 100,000 to 35.2 per 100,000 between 2001 and 2017. Only the state of Minas Gerais showed an increasing trend, whereas nine other states showed a stationary trend. A total of 326 Brazilian municipalities were classified as high priority, and 22 high-risk spatial-temporal clusters were identified. The overall Social Vulnerability Index and the subindices of Human Capital and Income and Work were associated with the incidence of tuberculosis. It was also observed that the incidence rates were greater in municipalities with greater social vulnerability. Conclusions: This study identified clusters with high risk of TB in Brazil. A significant association was observed between the incidence rate of TB and the indices of social vulnerability.

23 April 2021 in Epidemiology and Infection
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JBJussara Almeida Oliveira Baggio
Jussara Almeida Oliveira Baggio
MMMichael Ferreira Machado
Michael Ferreira Machado
RCRodrigo Carmo
Rodrigo Carmo
AAAnderson da Costa Armstrong
Anderson da Costa Armstrong
ASAllan Dantas Santos
Allan Dantas Santos
CSCarlos Dornels Freire De Dornels Freire de Souza
Carlos Dornels Freire De Dornels Freire de Souza
Brazil ranks second in the number of confirmed cases of COVID-19 worldwide. In spite of this, coping measures differ throughout the national territory, as does the disease's impact on the population. This cross-sectional observational study, with 59 695 cases of COVID-19 registered in the state of Alagoas between March and August 2020, analysed clinical-epidemiological variables, incidence rate, mortality rate, case fatality rate (CFR) and the social indicators municipal human development index (MHDI) and social vulnerability index (SVI). Moran statistics and regression models were applied. Logistic regression analysis was applied to determine the predictors of death. The incidence rate was 1788.7/100 000 inhabitants; mortality rate was 48.0/100 000 and CFR was 2.7%. The highest incidence rates were observed in municipalities with better human development (overall MHDI (I = 0.1668; p = 0.002), education MHDI (I = 0.1649; p = 0.002) and income MHDI (I = 0.1880; p = 0.005)) and higher social vulnerability (overall SVI (I = 0.0599; p = 0.033)). CFR was associated with higher social vulnerability (SVI human capital (I = 0.0858; p = 0.004) and SVI urban infrastructure (I = 0.0985; p = 0.040)). Of the analysed cases, 55.4% were female; 2/3 were Black or Brown and the median age was 41 years. Among deaths, most were male (919; 57.4%) and elderly (1171; 73.1%). The predictors of death were male sex, advanced age and the presence of comorbidities. In Alagoas, Brazil, the disease has undergone a process of interiorisation and caused more deaths in poorer municipalities. The presence of comorbidities and advanced age were predictors of death.