Identification and Characterization of Sporadic Isolates of Streptococcus iniae Isolated from Humans

Seven reference strains and seven clinical isolates of Streptococcus iniae, submitted to the Centers for Disease Control and Prevention Streptococcus Reference Laboratory between 2001 and 2004, were successfully identified by a conventional identification system. The seven randomly submitted clinical isolates were sensitive to β-lactams, macrolides, quinolones, and vancomycin. Two of the seven clinical isolates were resistant to tetracycline. All seven strains grew well and multiplied in a phagocytosis assay. One of the seven randomly submitted strains was more similar to the type strain of S. iniae than to the other six strains. The latter six strains were similar if not identical to representative strains from a cluster of disease in Canada (M. R. Weinstein et al., N. Engl. J. Med. 337:589-594, 1997)

Measles in conflict-affected northern Syria: results from an ongoing outbreak surveillance program

Background: The Syrian conflict has dramatically changed the public health landscape of Syria since its onset in March of 2011. Depleted resources, fractured health systems, and increased security risks have disrupted many routine services, including vaccinations, across several regions in Syria. Improving our understanding of infectious disease transmission in conflict-affected communities is imperative, particularly in the Syrian conflict. We utilize surveillance data from the Early Warning Alert and Response Network (EWARN) database managed by the Assistance Coordination Unit (ACU) to explore trends in the incidence of measles in conflict-affected northern Syria and analyze two consecutive epidemics in 2017 and 2018. Methods: We conducted a retrospective time-series analysis of the incidence of clinically suspected cases of measles using EWARN data between January 2015 and June 2019. We compared regional and temporal trends to assess differences between geographic areas and across time. Results: Between January 2015 and June 2019, there were 30,241 clinically suspected cases of measles reported, compared to 3193 cases reported across the whole country in the decade leading up to the conflict. There were 960 regional events that met the measles outbreak threshold and significant differences in the medians of measles incidence across all years (p-value < 0.001) and in each pairwise comparison of years as well as across all geographic regions (p-value < 0.001). Although most governorates faced an elevated burden of cases in every year of the study, the measles epidemics of 2017 and 2018 in the governorates of Ar-Raqqa, Deir-Ez-Zor, and Idlib accounted for over 71% of the total suspected cases over the entire study period. Conclusions: The 2017 and 2018 measles epidemics were the largest since Syria eliminated the disease in 1999. The regions most affected by these outbreaks were areas of intense conflict and displacement between 2014 and 2018, including districts in Ar-Raqqa, Deir-Ez-Zor, and Idlib. The spread of measles in northern Syria serves as an indicator of low immunization coverage and limited access to care and highlights the Syrian peoples’ vulnerability to infectious diseases and vaccine preventable diseases in the setting of the current conflict

Sex differences and correlates of poor glycaemic control in type 2 diabetes: a cross-sectional study in Brazil and Venezuela.

OBJECTIVE:Examine whether glycaemic control varies according to sex and whether the latter plays a role in modifying factors associated with inadequate glycaemic control in patients with type 2 diabetes (T2D) in Brazil and Venezuela. DESIGN, SETTING AND PARTICIPANTS:This was a cross-sectional, nationwide survey conducted in Brazil and Venezuela from February 2006 to June 2007 to obtain information about glycaemic control and its determinants in patients with diabetes mellitus attending outpatient clinics. MAIN OUTCOME MEASURES:Haemoglobin A1c (HbA1c) level was measured by liquid chromatography, and patients with HbA1c ≥7.0% (53 mmol/mol) were considered to have inadequate glycaemic control. The association of selected variables with glycaemic control was analysed by multivariate linear regression, using HbA1c as the dependent variable. RESULTS:A total of 9418 patients with T2D were enrolled in Brazil (n=5692) and in Venezuela (n=3726). They included 6214 (66%) women and 3204 (34%) men. On average, HbA1c levels in women were 0.13 (95% CI 0.03 to 0.24; p=0.015) higher than in men, after adjusting for age, marital status, education, race, country, body mass index, duration of disease, complications, type of healthcare, adherence to diet, adherence to treatment and previous measurement of HbA1c. Sex modified the effect of some factors associated with glycaemic control in patients with T2D in our study, but had no noteworthy effect in others. CONCLUSIONS:Women with T2D had worse glycaemic control than men. Possible causes for poorer glycaemic control in women compared with men include differences in glucose homeostasis, treatment response and psychological factors. In addition, sex modified factors associated with glycaemic control, suggesting the need to develop specific treatment guidelines for men and women

Sex differences and correlates of poor glycaemic control in type 2 diabetes: a cross-sectional study in Brazil and Venezuela

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2019-08-06T12:51:21Z No. of bitstreams: 1 Duarte F Sex differences correlates... 2019.pdf: 273092 bytes, checksum: 170cd2dcbe9e8edfb04f721c7ef5915c (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2019-08-06T16:36:12Z (GMT) No. of bitstreams: 1 Duarte F Sex differences correlates... 2019.pdf: 273092 bytes, checksum: 170cd2dcbe9e8edfb04f721c7ef5915c (MD5)Made available in DSpace on 2019-08-06T16:36:12Z (GMT). No. of bitstreams: 1 Duarte F Sex differences correlates... 2019.pdf: 273092 bytes, checksum: 170cd2dcbe9e8edfb04f721c7ef5915c (MD5) Previous issue date: 2019-01-05Pfizer Inc. The Brazilian Study of Diabetes Control was funded by Pfizer Inc., Brazil. Coordination for the Improvement of Higher Education Personnel (CAPES), Brazilian Ministry of Education. EDMJ received support from the National Council for Scientific and Technological Development (CNPq).University of California. School of Public Health. Department of Epidemiology. Berkeley, CA, USA.Associação Obras Sociais Irmã Dulce. 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 de Epidemiologia Molecular e Bioestatística. 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 de Epidemiologia Molecular e Bioestatística. Salvador, BA, Brasil / Universidade Federal da Bahia. Escola de Nutrição. Departamento Ciências da Nutrição. Salvador, BA, Brasil.University of California. School of Public Health. Department of Epidemiology. Berkeley, CA, USA.Associação Obras Sociais Irmã Dulce. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Epidemiologia Molecular e Bioestatística. Salvador, BA, Brasil.Examine whether glycaemic control varies according to sex and whether the latter plays a role in modifying factors associated with inadequate glycaemic control in patients with type 2 diabetes (T2D) in Brazil and Venezuela. Design, setting and participants This was a crosssectional, nationwide survey conducted in Brazil and Venezuela from February 2006 to June 2007 to obtain information about glycaemic control and its determinants in patients with diabetes mellitus attending outpatient clinics. Main outcome measures Haemoglobin A1c (HbA1c) level was measured by liquid chromatography, and patients with HbA1c ≥7.0% (53 mmol/mol) were considered to have inadequate glycaemic control. The association of selected variables with glycaemic control was analysed by multivariate linear regression, using HbA1c as the dependent variable. Results A total of 9418 patients with T2D were enrolled in Brazil (n=5692) and in Venezuela (n=3726). They included 6214 (66%) women and 3204 (34%) men. On average, HbA1c levels in women were 0.13 (95% CI 0.03 to 0.24; p=0.015) higher than in men, after adjusting for age, marital status, education, race, country, body mass index, duration of disease, complications, type of healthcare, adherence to diet, adherence to treatment and previous measurement of HbA1c. Sex modified the effect of some factors associated with glycaemic control in patients with T2D in our study, but had no noteworthy effect in others. Conclusions Women with T2D had worse glycaemic control than men. Possible causes for poorer glycaemic control in women compared with men include differences in glucose homeostasis, treatment response and psychological factors. In addition, sex modified factors associated with glycaemic control, suggesting the need to develop specific treatment guidelines for men and women

Substantial underestimation of SARS-CoV-2 infection in the United States due to incomplete testing and imperfect test accuracy

Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Current confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Using a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy, we estimated 6,275,072 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) as of April 18, 2020. Accounting for uncertainty, the number of infections was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference was due to incomplete testing, while 14% (0.3-36%) was due to imperfect test accuracy. Estimates of SARS-CoV-2 infections that transparently account for testing practices and diagnostic accuracy reveal that the pandemic is larger than confirmed case counts suggest

Substantial underestimation of SARS-CoV-2 infection in the United States.

Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Here, we use a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy. We estimate 6,454,951 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) in the United States as of April 18, 2020. Accounting for uncertainty, the number of infections during this period was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference is due to incomplete testing, while 14% (0.3-36%) is due to imperfect test accuracy. The approach can readily be applied in future studies in other locations or at finer spatial scale to correct for biased testing and imperfect diagnostic accuracy to provide a more realistic assessment of COVID-19 burden

Substantial underestimation of SARS-CoV-2 infection in the United States due to incomplete testing and imperfect test accuracy

Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Current confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Using a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy, we estimated 6,275,072 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) as of April 18, 2020. Accounting for uncertainty, the number of infections was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference was due to incomplete testing, while 14% (0.3-36%) was due to imperfect test accuracy. Estimates of SARS-CoV-2 infections that transparently account for testing practices and diagnostic accuracy reveal that the pandemic is larger than confirmed case counts suggest

Substantial underestimation of SARS-CoV-2 infection in the United States.

Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Here, we use a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy. We estimate 6,454,951 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) in the United States as of April 18, 2020. Accounting for uncertainty, the number of infections during this period was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference is due to incomplete testing, while 14% (0.3-36%) is due to imperfect test accuracy. The approach can readily be applied in future studies in other locations or at finer spatial scale to correct for biased testing and imperfect diagnostic accuracy to provide a more realistic assessment of COVID-19 burden