LIVIVO - The Search Portal for Life Sciences

zur deutschen Oberfläche wechseln
Advanced search

Search results

Result 1 - 10 of total 483

Search options

  1. Book: Big data for infectious disease surveillance and modeling

    Chowell, Gerardo

    (The journal of infectious diseases ; volume 214, supplement S4 (1 December 2016))

    2016  

    Author's details guest editors: Gerardo Chowell, PhD, Lone Simonsen, PhD, Shweta Bansal, PhD, Alex Vespignani, PhD, Cecile Viboud, PhD
    Series title The journal of infectious diseases ; volume 214, supplement S4 (1 December 2016)
    Collection
    Language English
    Size Seite S375-S432, Illustrationen
    Publisher Oxford University Press
    Publishing place Cary, NC
    Publishing country United States
    Document type Book
    HBZ-ID HT019426404
    Database Catalogue ZB MED Medicine, Health

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    Uh II Zs 50 -214,Suppl.S4- verfügbar in Königswinter Königswinter

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  2. Book ; Online ; E-Book: Mathematical and statistical modeling for emerging and re-emerging infectious diseases

    Chowell, Gerardo / Hyman, James M.

    2016  

    Author's details Gerardo Chowell, James M. Hyman editors
    Keywords Mathematics ; Infectious diseases ; Epidemiology ; Probabilities ; Statistics
    Subject code 519.2
    Language English
    Size 1 Online-Ressource (ix, 356 Seiten), Illustrationen
    Publisher Springer
    Publishing place Cham
    Publishing country Switzerland
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT019471288
    ISBN 978-3-319-40413-4 ; 9783319404110 ; 3-319-40413-X ; 3319404113
    DOI 10.1007/978-3-319-40413-4
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

    Full text online

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  3. Article ; Online: Harnessing Telehealth: Improving Epidemic Prediction and Response.

    Chowell, Gerardo / Lawson, Andrew

    American journal of public health

    2024  Volume 114, Issue 2, Page(s) 146–148

    MeSH term(s) Humans ; Telemedicine ; Epidemics
    Language English
    Publishing date 2024-02-09
    Publishing country United States
    Document type Editorial
    ZDB-ID 121100-6
    ISSN 1541-0048 ; 0090-0036 ; 0002-9572
    ISSN (online) 1541-0048
    ISSN 0090-0036 ; 0002-9572
    DOI 10.2105/AJPH.2023.307547
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Un I Zs.279: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  4. Book: Mathematical and statistical estimation approaches in epidemiology

    Chowell, Gerardo

    2009  

    Author's details Gerardo Chowell ... ed
    Language English
    Size XIII, 363 S. : graph. Darst., Kt., 235 mm x 155 mm
    Publisher Springer
    Publishing place Dordrecht u.a.
    Publishing country Netherlands
    Document type Book
    HBZ-ID HT016056283
    ISBN 978-90-481-2312-4 ; 9789048123131 ; 90-481-2312-7 ; 9048123135
    Database Catalogue ZB MED Medicine, Health

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    2009 A 4252 order for loan Magazin

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  5. Article ; Online: Parameter estimation and forecasting with quantified uncertainty for ordinary differential equation models using QuantDiffForecast: A MATLAB toolbox and tutorial.

    Chowell, Gerardo / Bleichrodt, Amanda / Luo, Ruiyan

    Statistics in medicine

    2024  Volume 43, Issue 9, Page(s) 1826–1848

    Abstract: Mathematical models based on systems of ordinary differential equations (ODEs) are frequently applied in various scientific fields to assess hypotheses, estimate key model parameters, and generate predictions about the system's state. To support their ... ...

    Abstract Mathematical models based on systems of ordinary differential equations (ODEs) are frequently applied in various scientific fields to assess hypotheses, estimate key model parameters, and generate predictions about the system's state. To support their application, we present a comprehensive, easy-to-use, and flexible MATLAB toolbox, QuantDiffForecast, and associated tutorial to estimate parameters and generate short-term forecasts with quantified uncertainty from dynamical models based on systems of ODEs. We provide software ( https://github.com/gchowell/paramEstimation_forecasting_ODEmodels/) and detailed guidance on estimating parameters and forecasting time-series trajectories that are characterized using ODEs with quantified uncertainty through a parametric bootstrapping approach. It includes functions that allow the user to infer model parameters and assess forecasting performance for different ODE models specified by the user, using different estimation methods and error structures in the data. The tutorial is intended for a diverse audience, including students training in dynamic systems, and will be broadly applicable to estimate parameters and generate forecasts from models based on ODEs. The functions included in the toolbox are illustrated using epidemic models with varying levels of complexity applied to data from the 1918 influenza pandemic in San Francisco. A tutorial video that demonstrates the functionality of the toolbox is included.
    MeSH term(s) Humans ; Models, Biological ; Uncertainty ; Software
    Language English
    Publishing date 2024-02-20
    Publishing country England
    Document type Journal Article
    ZDB-ID 843037-8
    ISSN 1097-0258 ; 0277-6715
    ISSN (online) 1097-0258
    ISSN 0277-6715
    DOI 10.1002/sim.10036
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    In stock of ZB MED Cologne/Königswinter

    Zs.A 1756: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  6. Article ; Online: SubEpiPredict:

    Chowell, Gerardo / Dahal, Sushma / Bleichrodt, Amanda / Tariq, Amna / Hyman, James M / Luo, Ruiyan

    Infectious Disease Modelling

    2024  Volume 9, Issue 2, Page(s) 411–436

    Abstract: ... An ... ...

    Abstract An ensemble
    Language English
    Publishing date 2024-02-09
    Publishing country China
    Document type Journal Article
    ZDB-ID 3015225-2
    ISSN 2468-0427 ; 2468-2152
    ISSN (online) 2468-0427
    ISSN 2468-2152
    DOI 10.1016/j.idm.2024.02.001
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  7. Article ; Online: Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks.

    Mohebbi, Fatemeh / Zelikovsky, Alex / Mangul, Serghei / Chowell, Gerardo / Skums, Pavel

    Nature communications

    2024  Volume 15, Issue 1, Page(s) 2838

    Abstract: The emergence of viral variants with altered phenotypes is a public health challenge underscoring the need for advanced evolutionary forecasting methods. Given extensive epistatic interactions within viral genomes and known viral evolutionary history, ... ...

    Abstract The emergence of viral variants with altered phenotypes is a public health challenge underscoring the need for advanced evolutionary forecasting methods. Given extensive epistatic interactions within viral genomes and known viral evolutionary history, efficient genomic surveillance necessitates early detection of emerging viral haplotypes rather than commonly targeted single mutations. Haplotype inference, however, is a significantly more challenging problem precluding the use of traditional approaches. Here, using SARS-CoV-2 evolutionary dynamics as a case study, we show that emerging haplotypes with altered transmissibility can be linked to dense communities in coordinated substitution networks, which become discernible significantly earlier than the haplotypes become prevalent. From these insights, we develop a computational framework for inference of viral variants and validate it by successful early detection of known SARS-CoV-2 strains. Our methodology offers greater scalability than phylogenetic lineage tracing and can be applied to any rapidly evolving pathogen with adequate genomic surveillance data.
    MeSH term(s) Phylogeny ; Biological Evolution ; Early Diagnosis ; Genome, Viral/genetics ; Genomics ; SARS-CoV-2/genetics
    Language English
    Publishing date 2024-04-02
    Publishing country England
    Document type Journal Article
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-024-47304-6
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  8. Article: Retrospective evaluation of short-term forecast performance of ensemble sub-epidemic frameworks and other time-series models: The 2022-2023 mpox outbreak across multiple geographical scales, July 14

    Bleichrodt, Amanda / Luo, Ruiyan / Kirpich, Alexander / Chowell, Gerardo

    medRxiv : the preprint server for health sciences

    2023  

    Abstract: In May 2022, public health officials noted an unprecedented surge in mpox cases in non-endemic countries worldwide. As the epidemic accelerated, multi-model forecasts of the epidemic's trajectory were critical in guiding the implementation of public ... ...

    Abstract In May 2022, public health officials noted an unprecedented surge in mpox cases in non-endemic countries worldwide. As the epidemic accelerated, multi-model forecasts of the epidemic's trajectory were critical in guiding the implementation of public health interventions and determining policy. As the case levels have significantly decreased as of early September 2022, evaluating model performance is essential to advance the growing field of epidemic forecasting. Using laboratory-confirmed mpox case data from the Centers for Disease Control and Prevention (CDC) and Our World in Data (OWID) teams through the week of January 26th, 2023, we generated retrospective sequential weekly forecasts (e.g., 1-4-weeks) for Brazil, Canada, France, Germany, Spain, the United Kingdom, the USA, and at the global scale using models that require minimal input data including the auto-regressive integrated moving average (ARIMA), general additive model (GAM), simple linear regression (SLR), Facebook's Prophet model, as well as the sub-epidemic wave (spatial-wave) and
    Language English
    Publishing date 2023-10-17
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.05.15.23289989
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  9. Article: Fitting dynamic models to epidemic outbreaks with quantified uncertainty: A Primer for parameter uncertainty, identifiability, and forecasts.

    Chowell, Gerardo

    Infectious Disease Modelling

    2017  Volume 2, Issue 3, Page(s) 379–398

    Abstract: Mathematical models provide a quantitative framework with which scientists can assess hypotheses on the potential underlying mechanisms that explain patterns in the observed data at different spatial and temporal scales, generate estimates of key kinetic ...

    Abstract Mathematical models provide a quantitative framework with which scientists can assess hypotheses on the potential underlying mechanisms that explain patterns in the observed data at different spatial and temporal scales, generate estimates of key kinetic parameters, assess the impact of interventions, optimize the impact of control strategies, and generate forecasts. We review and illustrate a simple data assimilation framework for calibrating mathematical models based on ordinary differential equation models to time series data describing the temporal progression of case counts relating to population growth or infectious disease transmission dynamics. In contrast to Bayesian estimation approaches that always raise the question of how to set priors for the parameters, this frequentist approach relies on modeling the error structure in the data. We discuss issues related to parameter identifiability, uncertainty quantification and propagation as well as model performance and forecasts along examples based on phenomenological and mechanistic models parameterized using simulated and real datasets.
    Keywords covid19
    Language English
    Publishing date 2017-08-12
    Publishing country China
    Document type Journal Article
    ZDB-ID 3015225-2
    ISSN 2468-0427 ; 2468-2152
    ISSN (online) 2468-0427
    ISSN 2468-2152
    DOI 10.1016/j.idm.2017.08.001
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

  10. Article: Modeling Study: Characterizing the Spatial Heterogeneity of the COVID-19 Pandemic through Shape Analysis of Epidemic Curves.

    Srivastava, Anuj / Chowell, Gerardo

    Research square

    2021  

    Abstract: Background: The COVID-19 incidence rates across different geographical regions (e.g., counties in a state, states in a nation, countries in a continent) follow different shapes and patterns. The overall summaries at coarser spatial scales, that are ... ...

    Abstract Background: The COVID-19 incidence rates across different geographical regions (e.g., counties in a state, states in a nation, countries in a continent) follow different shapes and patterns. The overall summaries at coarser spatial scales, that are obtained by simply averaging individual curves (across regions), hide nuanced variability and blur the spatial heterogeneity at finer spatial scales. For instance, a decreasing incidence rate curve in one region is obscured by an increasing rate curve for another region, when the analysis relies on coarse averages of locally heterogeneous transmission dynamics.
    Objective: To highlight regional differences in COVID-19 incidence rates and to discover prominent patterns in shapes of incidence rate curves in multiple regions (USA and Europe).
    Methods: We employ statistical methods to analyze shapes of local COVID-19 incidence rate curves and statistically group them into distinct clusters, according to their shapes. Using this information, we derive the so-called
    Results: Our analyses reveal that pandemic curves often differ substantially across regions. However, there are only a handful of shapes that dominate transmission dynamics for all states in the USA and countries in Europe. This approach yields a broad classification of spatial areas into different characteristic epidemic trajectories. In particular, spatial areas within the same cluster have followed similar transmission and control dynamics.
    Conclusion: The shape-based analysis of pandemic curves presented here helps divide country or continental data into multiple regional clusters, each cluster containing areas with similar trend patterns. This clustering helps highlight differences in pandemic curves across regions and provides summaries that better reflect dynamical patterns within the clusters. This approach adds to the methodological toolkit for public health practitioners to facilitate decision making at different spatial scales.
    Language English
    Publishing date 2021-02-23
    Publishing country United States
    Document type Preprint
    DOI 10.21203/rs.3.rs-223226/v1
    Database MEDical Literature Analysis and Retrieval System OnLINE

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

To top