scholarly journals Time And Mode Of Epidemic Hcv-2 Subtypes Dispersal In Europe: Phylodynamics Of Hcv-2c In Italy And Albania

2021 ◽  
Author(s):  
Erika Ebranati ◽  
Alessandro Mancon ◽  
Martina Airoldi ◽  
Silvia Renica ◽  
Renata Shkjezi ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Temporal Scale ◽  
Effective Number ◽  
Guinea Bissau ◽  
Exponential Increase ◽  
Replication Number ◽  
Prevalent Subtype ◽  
Spatio Temporal ◽  
Phylodynamic Analysis ◽  
The Bayesian Approach

Newly characterising 245 Italian and Albanian HCV-2 NS5B sequences collected between 2001 and 2016 was used to reconstruct the origin and dispersion pathways of HCV-2c. The tree of a subset of these sequences aligned with 247 publicly available sequences was reconstructed in spatio-temporal scale using the Bayesian approach, and the effective replication number (Re) was estimated using the birth-death model. Our findings show that HCV-2c was the most prevalent subtype in Italy and Albania, and that GT2 originated in Guinea Bissau in the XVI century and spread to Europe in the XX century. The HCV-2c subtype had two internal nodes respectively dating back to the 1930s and 1950s having as most probable locations Ghana and Italy, respectively. Phylodynamic analysis revealed an exponential increase in the effective number of infections and Re in both Italy between the 1950s and 1980s, and Albania between the 1990s and the early 2000s. It seems very likely that HCV-2c reached Italy from Africa at the time of the second Italian colonisation (1936-1941), but did not reach Albania until the period of dramatic migration to Italy in the 1990s.

scholarly journals Time and Mode of Epidemic HCV-2 Subtypes Spreading in Europe: Phylodynamics in Italy and Albania

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 327
Author(s):  
Erika Ebranati ◽  
Alessandro Mancon ◽  
Martina Airoldi ◽  
Silvia Renica ◽  
Renata Shkjezi ◽  
...  
Keyword(s):  
Hepatitis C ◽  
African Origin ◽  
Effective Number ◽  
Phylogeographic Analysis ◽  
Exponential Increase ◽  
Genotype 2 ◽  
History Of ◽  
Prevalent Subtype ◽  
Hcv Genotype 2 ◽  
Phylodynamic Analysis

Hepatitis C virus (HCV) genotype 2 causes about 10% of global infections and has the most variable circulation profile in Europe. The history of “endemic” HCV-2 subtypes has been satisfactorily reconstructed, instead there is little information about the recent spread of the “epidemic” subtypes, including HCV-2c. To investigate the origin and dispersion pathways of HCV-2c, 245 newly characterized Italian and Albanian HCV-2 NS5B sequences were aligned with 247 publicly available sequences and included in phylogeographic and phylodynamic analyses using the Bayesian framework. Our findings show that HCV-2c was the most prevalent subtype in Italy and Albania. The phylogeographic analysis suggested an African origin of HCV-2c before it reached Italy about in the 1940s. Phylodynamic analysis revealed an exponential increase in the effective number of infections and Re in Italy between the 1940s and 1960s, and in Albania between the 1990s and the early 2000s. It seems very likely that HCV-2c reached Italy from Africa at the time of the second Italian colonization but did not reach Albania until the period of dramatic migration to Italy in the 1990s. This study contributes to reconstructing the history of the spread of epidemic HCV-2 subtypes to Europe.

scholarly journals Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin

2019 ◽  
Author(s):  
Zhihua He ◽  
Katy Unger-Shayesteh ◽  
Sergiy Vorogushyn ◽  
Stephan M. Weise ◽  
Doris Duethmann ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Model Uncertainty ◽  
Temporal Variability ◽  
Isotope Fractionation ◽  
Cold Season ◽  
Water Sampling ◽  
Hydrograph Separation ◽  
Total Runoff ◽  
Spatio Temporal ◽  
The Bayesian Approach

Abstract. Water tracer data have been successfully used for hydrograph separation in glacierized basins. However, uncertainties in the hydrograph separation are large in these basins, caused by the spatio-temporal variability in the tracer signatures of water sources, the uncertainty of water sampling and the mixing model uncertainty. In this study, we used electrical conductivity (EC) measurements and two isotope signatures (δ18O and δ2H) to label the runoff components, including groundwater, snow and glacier meltwater, and rainfall, in a Central Asia glacierized basin. The contributions of runoff components (CRC) to the total runoff, as well as the corresponding uncertainty, were quantified by two mixing approaches: a traditional end-member mixing approach (TEMMA) and a Bayesian end-member mixing approach. The performance of the two mixing approaches were compared in three seasons, distinguished as cold season, snowmelt season and glacier melt season. Results show that: 1) The Bayesian approach generally estimated smaller uncertainty ranges for the CRC compared to the TEMMA. 2) The Bayesian approach tended to be less sensitive to the sampling uncertainties of meltwater than the TEMMA. 3) Ignoring the model uncertainty caused by the isotope fractionation likely leaded to an overestimated rainfall contribution and an underestimated meltwater share in the melt seasons. Our study provides the first comparison of the two end-member mixing approaches for hydrograph separation in glacierized basins, and gives insights for the application of tracer-based mixing approaches for similar basins.

scholarly journals The Bayesian Approach and the Results of the ISAR-REACT 5 Trial

2021 ◽  
Vol 14 (2) ◽  
pp. 231-232
Author(s):  
Adnan Kastrati ◽  
Alexander Hapfelmeier
Keyword(s):  
Bayesian Approach ◽  
The Bayesian Approach

A new Bayesian approach for QTL mapping of family data

2021 ◽  
Author(s):  
Daiane Aparecida Zuanetti ◽  
Luis Aparecido Milan
Keyword(s):  
Qtl Mapping ◽  
Random Effects ◽  
Bayesian Approach ◽  
Variance Component ◽  
Mendelian Inheritance ◽  
Family Data ◽  
Data Sets ◽  
Mendelian Segregation ◽  
Gaw17 Data ◽  
The Bayesian Approach

In this paper, we propose a new Bayesian approach for QTL mapping of family data. The main purpose is to model a phenotype as a function of QTLs’ effects. The model considers the detailed familiar dependence and it does not rely on random effects. It combines the probability for Mendelian inheritance of parents’ genotype and the correlation between flanking markers and QTLs. This is an advance when compared with models which use only Mendelian segregation or only the correlation between markers and QTLs to estimate transmission probabilities. We use the Bayesian approach to estimate the number of QTLs, their location and the additive and dominance effects. We compare the performance of the proposed method with variance component and LASSO models using simulated and GAW17 data sets. Under tested conditions, the proposed method outperforms other methods in aspects such as estimating the number of QTLs, the accuracy of the QTLs’ position and the estimate of their effects. The results of the application of the proposed method to data sets exceeded all of our expectations.

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