Evidence of New Endemic Clusters of Human T-Cell Leukemia Virus (HTLV) Infection in Bahia, Brazil

BackgroundSalvador, Bahia (northeastern Brazil), has been identified as the epicenter of Human T-cell leukemia virus Human T-cell leukemia virus (HTLV) type 1 infection in the country. This study aims to estimate the rate of HTLV infection and the geographical distribution of this virus in this state.MethodsAll HTLV tests (chemiluminescence/ELISA assays/Western Blotting) performed in the Central Laboratory of Public Health of Bahia (LACEN) from 2004 to 2013 were included. Data was extracted from LACEN’s database using high volume extract, transformation and load throughput. Infection rate was expressed as the number of infected individuals per 100,000 inhabitants considering municipalities grouped in microregions and/or mesoregions as the unit of analysis.ResultsA total of 233,876 individuals were evaluated. Individuals were from 394 out of 417 municipalities of Bahia (94.5%). HTLV chemiluminescence/ELISA assay was found to be reactive for 3,138 individuals from whom 2,323 had WB results (1,978 positives, 62 negative and 282 indeterminate). Out of 1978 reactive samples, 1,813 (91.7%) were positive for HTLV-1, 58 (2.9%) for HTLV-2 and 107 (5.4%) were for both HTLV-1 and HTLV-2. The cumulative mean rate of HTLV-positive cases in Bahia was 14.4 per 100,000 inhabitants. Three microregions presented rates >20 HTLV-positive cases/100,000 inhabitants: Barreiras (24.83 cases per 100,000 inhabitants), Salvador (22.90 cases per 100,000 inhabitants), and Ilhéus-Itabuna (22.60 cases per 100,000 inhabitants).ConclusionHTLV infection is disseminated in the state of Bahia, with an overall moderate rate of infection. Further studies should be conducted to characterize the epidemiological and clinical profile of HTLV-infected individuals better and to propose effective prevention measures

Administrative Data Linkage in Brazil: Potentials for Health Technology Assessment.

Health technology assessment (HTA) is the systematic evaluation of the properties and impacts of health technologies and interventions. In this article, we presented a discussion of HTA and its evolution in Brazil, as well as a description of secondary data sources available in Brazil with potential applications to generate evidence for HTA and policy decisions. Furthermore, we highlighted record linkage, ongoing record linkage initiatives in Brazil, and the main linkage tools developed and/or used in Brazilian data. Finally, we discussed the challenges and opportunities of using secondary data for research in the Brazilian context. In conclusion, we emphasized the availability of high quality data and an open, modern attitude toward the use of data for research and policy. This is supported by a rigorous but enabling legal framework that will allow the conduct of large-scale observational studies to evaluate clinical, economical, and social impacts of health technologies and social policies

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

Distribution of Human T-Lymphotropic Virus (HTLV) and Hepatitis C Co-infection in Bahia, Brazil.

Both Human T-lymphotropic virus type 1 (HTLV-1) and hepatitis C virus (HCV) are endemic in Brazil. In Salvador, the capital of the state of Bahia, 2% and 1.5% of the general population is infected with HTLV-1 or HCV. This study aimed to estimate the prevalence and the distribution of HTLV/HCV coinfection in Bahia. This cross-sectional study was conducted at the Central Laboratory of Public Health for the state of Bahia (LACEN-BA). All samples in the LACEN database submitted to serological testing for anti-HCV (chemiluminescence) and anti-HTLV-1/2 (chemiluminescence/ELISA and Western blot) from 2004 to 2013 were included. Infection rate was expressed as the number of infected individuals per 100,000 inhabitants in a given municipality; municipalities were grouped by microregion for further analysis. A total of 120,192 samples originating from 358 of the 417 municipalities in Bahia (85.8%) were evaluated. The overall HCV coinfection rate in HTLV-positive was 14.31% [2.8 (ranging from 0.4 to 8.0) per 100,000 inhabitants.] Twenty-one (5%) of the municipalities reported at least one case of HTLV/HCV coinfection. Most cases (87%) were concentrated in three microregions (Salvador: 79%, Ilhéus/Itabuna: 5%, Porto Seguro: 3%). Coinfection occurred more frequently in males (51%) with a mean age of 59 [(IQR): 46-59] years. HTLV/HCV coinfection in the state of Bahia was more frequently found among males living in the microregions of Salvador, Ilhéus/Itabuna and Porto Seguro, all of which are known to be endemic for HTLV infection

Evidence of New Endemic Clusters of Human T-Cell Leukemia Virus (HTLV) Infection in Bahia, Brazil

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2019-05-17T13:17:37Z No. of bitstreams: 1 Pereira FM Front Microbiol 2019.pdf: 7007856 bytes, checksum: a686c7d8db23c266ba2dccc0a311bc2b (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2019-05-17T13:31:24Z (GMT) No. of bitstreams: 1 Pereira FM Front Microbiol 2019.pdf: 7007856 bytes, checksum: a686c7d8db23c266ba2dccc0a311bc2b (MD5)Made available in DSpace on 2019-05-17T13:31:24Z (GMT). No. of bitstreams: 1 Pereira FM Front Microbiol 2019.pdf: 7007856 bytes, checksum: a686c7d8db23c266ba2dccc0a311bc2b (MD5) Previous issue date: 2019National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico-CNPq), the National Foundation for the Development of Higher Education (Fundação Nacional para o Desenvolvimento do Ensino Superior-FUNDADESP), and the Foundation for Research Support of the State of Bahia (Fundação de Amparo à Pesquisa do Estado da Bahia-FAPESB). This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório Avançado de Saúde Pública. Salvador, BA, Brasil / Secretaria da Saúde do Estado da Bahia. Laboratório Central de Saúde Pública Prof. Gonçalo Moniz. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Epidemiologia Molecular e Bioestatística. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório Avançado de Saúde Pública. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimento para a Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório Avançado de Saúde Pública. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório Avançado de Saúde Pública. Salvador, BA, Brasil / Escola Bahiana de Medicina e Saúde Pública, Salvador, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório Avançado de Saúde Pública. Salvador, BA, Brasil / Escola Bahiana de Medicina e Saúde Pública, Salvador, Brasil.Background: Salvador, Bahia (northeastern Brazil), has been identified as the epicenter of Human T-cell leukemia virus Human T-cell leukemia virus (HTLV) type 1 infection in the country. This study aims to estimate the rate of HTLV infection and the geographical distribution of this virus in this state. Methods: All HTLV tests (chemiluminescence/ELISA assays/Western Blotting) performed in the Central Laboratory of Public Health of Bahia (LACEN) from 2004 to 2013 were included. Data was extracted from LACEN’s database using high volume extract, transformation and load throughput. Infection rate was expressed as the number of infected individuals per 100,000 inhabitants considering municipalities grouped in microregions and/or mesoregions as the unit of analysis. Results: A total of 233,876 individuals were evaluated. Individuals were from 394 out of 417 municipalities of Bahia (94.5%). HTLV chemiluminescence/ELISA assay was found to be reactive for 3,138 individuals from whom 2,323 had WB results (1,978 positives, 62 negative and 282 indeterminate). Out of 1978 reactive samples, 1,813 (91.7%) were positive for HTLV-1, 58 (2.9%) for HTLV-2 and 107 (5.4%) were for both HTLV-1 and HTLV-2. The cumulative mean rate of HTLV-positive cases in Bahia was 14.4 per 100,000 inhabitants. Three microregions presented rates >20 HTLVpositive cases/100,000 inhabitants: Barreiras (24.83 cases per 100,000 inhabitants), Salvador (22.90 cases per 100,000 inhabitants), and Ilhéus-Itabuna (22.60 cases per 100,000 inhabitants). Conclusion: HTLV infection is disseminated in the state of Bahia, with an overall moderate rate of infection. Further studies should be conducted to characterize the epidemiological and clinical profile of HTLV-infected individuals better and to propose effective prevention measures

The Centre for Data and Knowledge Integration for Health (CIDACS): Linking Health and Social Data in Brazil

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2019-12-12T14:04:06Z No. of bitstreams: 1 Barreto ML The Center....pdf: 755227 bytes, checksum: c8bcc5d68108b60b3b2ec5cce6be8635 (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2019-12-12T16:31:27Z (GMT) No. of bitstreams: 1 Barreto ML The Center....pdf: 755227 bytes, checksum: c8bcc5d68108b60b3b2ec5cce6be8635 (MD5)Made available in DSpace on 2019-12-12T16:31:27Z (GMT). No. of bitstreams: 1 Barreto ML The Center....pdf: 755227 bytes, checksum: c8bcc5d68108b60b3b2ec5cce6be8635 (MD5) Previous issue date: 2019CIDACS has received support from the Department of Science and Technology, Ministry of Health, Brazil; National Research Council (CNPq), Brazil and the Bill and Melinda Gates Foundation (CHAMADA MCTI/CNPq/MS/SCTIE/Decit/Fundação Bill e Melinda Gates N o 47/2014); Health Surveillance Secretariat, Ministry of Health, Brazil; Fundação de Apoio a Pesquisa do Estado da Bahia (FAPESB), Financiadora de Estudos e Projetos (FINEP), Secretaria de Ciência e Tecnologia do Estado da Bahia (SECTI) and Wellcome Trust.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / Federal University of Bahia. Institute of Collective Health. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / Federal University of Bahia. Institute of Collective Health. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, BrasilFundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / Federal University of Bahia. Computer Science Department. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / Federal University of Bahia. Statistics Department. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / University of Brasília. Tropical Medicine Centre. Brasília, DF, Brazil / Escola Fiocruz de Governo. Brasília, DF, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / University of Oxford. Center for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences. Oxford, UK / London School of Hygiene and Tropical Medicine. Faculty of Epidemiology and Population Health. United, Kingdom.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.University College London. Institute of Health Informatics. United Kingdom.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / London School of Hygiene and Tropical Medicine. Faculty of Epidemiology and Population Health. United, Kingdom.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil / London School of Hygiene and Tropical Medicine. Faculty of Epidemiology and Population Health. United, Kingdom.The Centre for Data and Knowledge Integration for Health (CIDACS) was created in 2016 in Salvador, Bahia-Brazil with the objective of integrating data and knowledge aiming to answer scientific questions related to the health of the Brazilian population. This article details our experiences in the establishment and operations of CIDACS, as well as efforts made to obtain high-quality linked data while adhering to security, ethical use and privacy issues. Every effort has been made to conduct operations while implementing appropriate structures, procedures, processes and controls over the original and integrated databases in order to provide adequate datasets to answer relevant research questions. Looking forward, CIDACS is expected to be an important resource for researchers and policymakers interested in enhancing the evidence base pertaining to different aspects of health, in particular when investigating, from a nation-wide perspective, the role of social determinants of health and the effects of social and environmental policies on different health outcomes