The Experts below are selected from a list of 220326 Experts worldwide ranked by ideXlab platform

Timothy C Matisziw - One of the best experts on this subject based on the ideXlab platform.

  • on the use of zip codes and zip code tabulation areas zctas for the spatial analysis of Epidemiological Data
    International Journal of Health Geographics, 2006
    Co-Authors: Tony H Grubesic, Timothy C Matisziw
    Abstract:

    While the use of spatially referenced Data for the analysis of Epidemiological Data is growing, issues associated with selecting the appropriate geographic unit of analysis are also emerging. A particularly problematic unit is the ZIP code. Lacking standardization and highly dynamic in structure, the use of ZIP codes and ZIP code tabulation areas (ZCTA) for the spatial analysis of disease present a unique challenge to researchers. Problems associated with these units for detecting spatial patterns of disease are explored. A brief review of ZIP codes and their spatial representation is conducted. Though frequently represented as polygons to facilitate analysis, ZIP codes are actually defined at a narrower spatial resolution reflecting the street addresses they serve. This research shows that their generalization as continuous regions is an imposed structure that can have serious implications in the interpretation of research results. ZIP codes areas and Census defined ZCTAs, two commonly used polygonal representations of ZIP code address ranges, are examined in an effort to identify the spatial statistical sensitivities that emerge given differences in how these representations are defined. Here, comparative analysis focuses on the detection of patterns of prostate cancer in New York State. Of particular interest for studies utilizing local, spatial statistical tests, is that differences in the topological structures of ZIP code areas and ZCTAs give rise to different spatial patterns of disease. These differences are related to the different methodologies used in the generalization of ZIP code information. Given the difficulty associated with generating ZIP code boundaries, both ZIP code areas and ZCTAs contain numerous representational errors which can have a significant impact on spatial analysis. While the use of ZIP code polygons for spatial analysis is relatively straightforward, ZCTA representations contain additional topological features (e.g. lakes and rivers) and contain fragmented polygons that can hinder spatial analysis. Caution must be exercised when using spatially referenced Data, particularly that which is attributed to ZIP codes and ZCTAs, for Epidemiological analysis. Researchers should be cognizant of representational errors associated with both geographies and their resulting spatial mismatch, especially when comparing the results obtained using different topological representations. While ZCTAs can be problematic, topological corrections are easily implemented in a geographic information system to remedy erroneous aggregation effects.

Clara Guerra Duarte - One of the best experts on this subject based on the ideXlab platform.

  • the ongoing covid 19 epidemic in minas gerais brazil insights from Epidemiological Data and sars cov 2 whole genome sequencing
    Emerging microbes & infections, 2020
    Co-Authors: Joilson Xavier, Marta Giovanetti, Talita Emile Ribeiro Adelino, Vagner Fonseca, Alana Vitor Barbosa Da Costa, Adriana Aparecida Ribeiro, Katlin Nascimento Felicio, Clara Guerra Duarte
    Abstract:

    The recent emergence of a coronavirus (SARS-CoV-2), first identified in the Chinese city of Wuhan in December 2019, has had major public health and economic consequences. Although 61,888 confirmed cases were reported in Brazil by 28 April 2020, little is known about the SARS-CoV-2 epidemic in this country. To better understand the recent epidemic in the second most populous state in southeast Brazil - Minas Gerais (MG) - we sequenced 40 complete SARS-CoV-2 genomes from MG cases and examined Epidemiological Data from three Brazilian states. Both the genome analyses and the geographical distribution of reported cases indicate for multiple independent introductions into MG. Epidemiological estimates of the reproductive number (R) using different Data sources and theoretical assumptions suggest the potential for sustained virus transmission despite a reduction in R from the first reported case to the end of April 2020. The estimated date of SARS-CoV-2 introduction into Brazil was consistent with Epidemiological Data from the first case of a returned traveller from Lombardy, Italy. These findings highlight the nature of the COVID-19 epidemic in MG and reinforce the need for real-time and continued genomic surveillance strategies to better understand and prepare for the epidemic spread of emerging viral pathogens..

  • the ongoing covid 19 epidemic in minas gerais brazil insights from Epidemiological Data and sars cov 2 whole genome sequencing
    medRxiv, 2020
    Co-Authors: Joilson Xavier, Marta Giovanetti, Talita Emile Ribeiro Adelino, Vagner Fonseca, Alana Vitor Barbosa Da Costa, Adriana Aparecida Ribeiro, Katlin Nascimento Felicio, Clara Guerra Duarte, Marcos Vinicius Ferreira Silva, Alvaro Salgado
    Abstract:

    The recent emergence of a previously unknown coronavirus (SARS-CoV-2), first confirmed in the city of Wuhan in China in December 2019, has caused serious public health and economic issues due to its rapid dissemination worldwide. Although 61,888 confirmed cases had been reported in Brazil by 28 April 2020, little was known about the SARS-CoV-2 epidemic in the country. To better understand the recent epidemic in the second most populous state in southeast Brazil (Minas Gerais, MG), we looked at existing Epidemiological Data from 3 states and sequenced 40 complete genomes from MG cases using Nanopore. We found evidence of multiple independent introductions from outside MG, both from genome analyses and the overly dispersed distribution of reported cases and deaths. Epidemiological estimates of the reproductive number using different Data sources and theoretical assumptions all suggest a reduction in transmission potential since the first reported case, but potential for sustained transmission in the near future. The estimated date of introduction in Brazil was consistent with Epidemiological Data from the first case of a returning-traveler from Lombardia, Italy. These findings highlight the unique reality of MGs epidemic and reinforce the need for real-time and continued genomic surveillance strategies as a way of understanding and therefore preparing against the epidemic spread of emerging viral pathogens.

Vagner Fonseca - One of the best experts on this subject based on the ideXlab platform.

  • the ongoing covid 19 epidemic in minas gerais brazil insights from Epidemiological Data and sars cov 2 whole genome sequencing
    Emerging microbes & infections, 2020
    Co-Authors: Joilson Xavier, Marta Giovanetti, Talita Emile Ribeiro Adelino, Vagner Fonseca, Alana Vitor Barbosa Da Costa, Adriana Aparecida Ribeiro, Katlin Nascimento Felicio, Clara Guerra Duarte
    Abstract:

    The recent emergence of a coronavirus (SARS-CoV-2), first identified in the Chinese city of Wuhan in December 2019, has had major public health and economic consequences. Although 61,888 confirmed cases were reported in Brazil by 28 April 2020, little is known about the SARS-CoV-2 epidemic in this country. To better understand the recent epidemic in the second most populous state in southeast Brazil - Minas Gerais (MG) - we sequenced 40 complete SARS-CoV-2 genomes from MG cases and examined Epidemiological Data from three Brazilian states. Both the genome analyses and the geographical distribution of reported cases indicate for multiple independent introductions into MG. Epidemiological estimates of the reproductive number (R) using different Data sources and theoretical assumptions suggest the potential for sustained virus transmission despite a reduction in R from the first reported case to the end of April 2020. The estimated date of SARS-CoV-2 introduction into Brazil was consistent with Epidemiological Data from the first case of a returned traveller from Lombardy, Italy. These findings highlight the nature of the COVID-19 epidemic in MG and reinforce the need for real-time and continued genomic surveillance strategies to better understand and prepare for the epidemic spread of emerging viral pathogens..

  • the ongoing covid 19 epidemic in minas gerais brazil insights from Epidemiological Data and sars cov 2 whole genome sequencing
    medRxiv, 2020
    Co-Authors: Joilson Xavier, Marta Giovanetti, Talita Emile Ribeiro Adelino, Vagner Fonseca, Alana Vitor Barbosa Da Costa, Adriana Aparecida Ribeiro, Katlin Nascimento Felicio, Clara Guerra Duarte, Marcos Vinicius Ferreira Silva, Alvaro Salgado
    Abstract:

    The recent emergence of a previously unknown coronavirus (SARS-CoV-2), first confirmed in the city of Wuhan in China in December 2019, has caused serious public health and economic issues due to its rapid dissemination worldwide. Although 61,888 confirmed cases had been reported in Brazil by 28 April 2020, little was known about the SARS-CoV-2 epidemic in the country. To better understand the recent epidemic in the second most populous state in southeast Brazil (Minas Gerais, MG), we looked at existing Epidemiological Data from 3 states and sequenced 40 complete genomes from MG cases using Nanopore. We found evidence of multiple independent introductions from outside MG, both from genome analyses and the overly dispersed distribution of reported cases and deaths. Epidemiological estimates of the reproductive number using different Data sources and theoretical assumptions all suggest a reduction in transmission potential since the first reported case, but potential for sustained transmission in the near future. The estimated date of introduction in Brazil was consistent with Epidemiological Data from the first case of a returning-traveler from Lombardia, Italy. These findings highlight the unique reality of MGs epidemic and reinforce the need for real-time and continued genomic surveillance strategies as a way of understanding and therefore preparing against the epidemic spread of emerging viral pathogens.

Marta Giovanetti - One of the best experts on this subject based on the ideXlab platform.

  • the ongoing covid 19 epidemic in minas gerais brazil insights from Epidemiological Data and sars cov 2 whole genome sequencing
    Emerging microbes & infections, 2020
    Co-Authors: Joilson Xavier, Marta Giovanetti, Talita Emile Ribeiro Adelino, Vagner Fonseca, Alana Vitor Barbosa Da Costa, Adriana Aparecida Ribeiro, Katlin Nascimento Felicio, Clara Guerra Duarte
    Abstract:

    The recent emergence of a coronavirus (SARS-CoV-2), first identified in the Chinese city of Wuhan in December 2019, has had major public health and economic consequences. Although 61,888 confirmed cases were reported in Brazil by 28 April 2020, little is known about the SARS-CoV-2 epidemic in this country. To better understand the recent epidemic in the second most populous state in southeast Brazil - Minas Gerais (MG) - we sequenced 40 complete SARS-CoV-2 genomes from MG cases and examined Epidemiological Data from three Brazilian states. Both the genome analyses and the geographical distribution of reported cases indicate for multiple independent introductions into MG. Epidemiological estimates of the reproductive number (R) using different Data sources and theoretical assumptions suggest the potential for sustained virus transmission despite a reduction in R from the first reported case to the end of April 2020. The estimated date of SARS-CoV-2 introduction into Brazil was consistent with Epidemiological Data from the first case of a returned traveller from Lombardy, Italy. These findings highlight the nature of the COVID-19 epidemic in MG and reinforce the need for real-time and continued genomic surveillance strategies to better understand and prepare for the epidemic spread of emerging viral pathogens..

  • the ongoing covid 19 epidemic in minas gerais brazil insights from Epidemiological Data and sars cov 2 whole genome sequencing
    medRxiv, 2020
    Co-Authors: Joilson Xavier, Marta Giovanetti, Talita Emile Ribeiro Adelino, Vagner Fonseca, Alana Vitor Barbosa Da Costa, Adriana Aparecida Ribeiro, Katlin Nascimento Felicio, Clara Guerra Duarte, Marcos Vinicius Ferreira Silva, Alvaro Salgado
    Abstract:

    The recent emergence of a previously unknown coronavirus (SARS-CoV-2), first confirmed in the city of Wuhan in China in December 2019, has caused serious public health and economic issues due to its rapid dissemination worldwide. Although 61,888 confirmed cases had been reported in Brazil by 28 April 2020, little was known about the SARS-CoV-2 epidemic in the country. To better understand the recent epidemic in the second most populous state in southeast Brazil (Minas Gerais, MG), we looked at existing Epidemiological Data from 3 states and sequenced 40 complete genomes from MG cases using Nanopore. We found evidence of multiple independent introductions from outside MG, both from genome analyses and the overly dispersed distribution of reported cases and deaths. Epidemiological estimates of the reproductive number using different Data sources and theoretical assumptions all suggest a reduction in transmission potential since the first reported case, but potential for sustained transmission in the near future. The estimated date of introduction in Brazil was consistent with Epidemiological Data from the first case of a returning-traveler from Lombardia, Italy. These findings highlight the unique reality of MGs epidemic and reinforce the need for real-time and continued genomic surveillance strategies as a way of understanding and therefore preparing against the epidemic spread of emerging viral pathogens.

Myra Spiliopoulou - One of the best experts on this subject based on the ideXlab platform.

  • discovering selecting and exploiting feature sequence records of study participants for the classification of Epidemiological Data on hepatic steatosis
    ACM Symposium on Applied Computing, 2018
    Co-Authors: Tommy Hielscher, Henry Volzke, Panagiotis Papapetrou, Myra Spiliopoulou
    Abstract:

    In longitudinal Epidemiological studies, participants undergo repeated medical examinations and are thus represented by a potentially large number of short examination outcome sequences. Some of those sequences may contain important information in various forms, such as patterns, with respect to the disease under study, while others may be on features of little relevance to the outcome. In this work, we propose a framework for Discovery, Selection and Exploitation (DiSelEx) of longitudinal Epidemiological Data, aiming to identify informative patterns among these sequences. DiSelEx combines sequence clustering with supervised learning to identify sequence groups that contribute to class separation. Newly derived and old features are evaluated and selected according to their redundancy and informativeness regarding the target variable. The selected feature set is then used to learn a classification model on the study Data. We evaluate DiSelEx on cohort participants for the disorder "hepatic steatosis" and report on the impact on predictive performance when using sequential Data in comparison to utilizing only the basic classifier.1

  • Subpopulation Discovery in Epidemiological Data with Subspace Clustering
    Foundations of Computing and Decision Sciences, 2014
    Co-Authors: Uli Niemann, Henry Volzke, Myra Spiliopoulou, Jens-peter Kühn
    Abstract:

    Abstract A prerequisite of personalized medicine is the identification of groups of people who share specific risk factors towards an outcome. We investigate the potential of subspace clustering for finding such groups in Epidemiological Data. We propose a workflow that encompasses clusterability assessment before cluster discovery and quality assessment after learning the clusters. Epidemiological usually do not have a ground truth for the verification of clusters found in subspaces. Hence, we introduce quality assessment through juxtaposition of the learned models to “models-of-randomness”, i.e. models that do not reflect a true cluster structure. On the basis of this workflow, we select subspace clustering methods, compare and discuss their performance. We use a Dataset with hepatic steatosis as outcome, but our findings apply on arbitrary Epidemiological cohort Data that have tenths of variables and exhibit class skew.

  • Learning and inspecting classification rules from longitudinal Epidemiological Data to identify predictive features on hepatic steatosis
    Expert Systems with Applications, 2014
    Co-Authors: Uli Niemann, Henry Volzke, Jens-peter Kühn, Myra Spiliopoulou
    Abstract:

    Abstract Personalized medicine requires the analysis of Epidemiological Data for the identification of subgroups sharing some risk factors and exhibiting dedicated outcome risks. We investigate the potential of Data mining methods for the analysis of subgroups of cohort participants on hepatic steatosis. We propose a workflow for Data preparation and mining on Epidemiological Data and we present InteractiveRuleMiner , an interactive tool for the inspection of rules in each subpopulation, including functionalities for the juxtaposition of labeled individuals and unlabeled ones. We report on our insights on specific subpopulations that have been discovered in a Data-driven rather than hypothesis-driven way.