Estimating influenza incidence using search query deceptiveness and generalized ridge regression

doi:10.1371/journal.pcbi.1007165

This content will become publicly available on October 1, 2020

Title: Estimating influenza incidence using search query deceptiveness and generalized ridge regression

Authors:

^[1];

^[1]; Barnard, Martha ^[2]; O'Connell, Fiona ^[2];

^[1]

Los Alamos National Laboratory
Minnetonka Public Schools

Publication Date:: 2019-10-01

Research Org.:: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Org.:: USDOE Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:: 1597332

Report Number(s):: LA-UR-18-24467
Journal ID: 1553-7358 (Electronic)

Grant/Contract Number:: 89233218CNA000001

Resource Type:: Accepted Manuscript

Journal Name:: PLoS Computational Biology (Online)

Additional Journal Information:: Journal Name: PLoS Computational Biology (Online); Journal Volume: 15; Journal Issue: 10

Country of Publication:: United States

Language:: English

Subject:: Biological Science; Information Science

Citation Formats


                    Priedhorsky, Reid, Daughton, Ashlynn Rae, Barnard, Martha, O'Connell, Fiona, and Osthus, David Allen. Estimating influenza incidence using search query deceptiveness and generalized ridge regression.  United States: N. p., 2019. 
        Web.  doi:10.1371/journal.pcbi.1007165.

Copy to clipboard


                    Priedhorsky, Reid, Daughton, Ashlynn Rae, Barnard, Martha, O'Connell, Fiona, & Osthus, David Allen. Estimating influenza incidence using search query deceptiveness and generalized ridge regression.  United States.  doi:10.1371/journal.pcbi.1007165.

Copy to clipboard


                    Priedhorsky, Reid, Daughton, Ashlynn Rae, Barnard, Martha, O'Connell, Fiona, and Osthus, David Allen. Tue .  
        "Estimating influenza incidence using search query deceptiveness and generalized ridge regression".  United States.  doi:10.1371/journal.pcbi.1007165.

Copy to clipboard


                    
@article{osti_1597332,

  title        = {Estimating influenza incidence using search query deceptiveness and generalized ridge regression},

  author       = {Priedhorsky, Reid and Daughton, Ashlynn Rae and Barnard, Martha and O'Connell, Fiona and Osthus, David Allen},

  abstractNote = {},

  doi          = {10.1371/journal.pcbi.1007165},

  journal      = {PLoS Computational Biology (Online)},

  number       = 10,

  volume       = 15,

  place        = {United States},

  year         = {2019},

  month        = {10}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

This content will become publicly available on October 1, 2020

Publisher's Version of Record

DOI: 10.1371/journal.pcbi.1007165

Other availability

Search WorldCat to find libraries that may hold this journal

Save / Share:

Export Metadata

Save to My Library

Works referenced in this record:

Importance of disease surveillance
journal, December 1974

Horstmann, Dorothy M.
Preventive Medicine, Vol. 3, Issue 4
DOI: 10.1016/0091-7435(74)90003-6

Timeliness of Nongovernmental versus Governmental Global Outbreak Communications
journal, July 2012

Mondor, Luke; Brownstein, John S.; Chan, Emily
Emerging Infectious Diseases, Vol. 18, Issue 7
DOI: 10.3201/eid1807.120249

Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness
journal, January 2018

Rolfes, Melissa A.; Foppa, Ivo M.; Garg, Shikha
Influenza and Other Respiratory Viruses, Vol. 12, Issue 1
DOI: 10.1111/irv.12486

Evaluation of reporting timeliness of public health surveillance systems for infectious diseases
journal, July 2004

Jajosky, Ruth Ann; Groseclose, Samuel L.
BMC Public Health, Vol. 4, Issue 1
DOI: 10.1186/1471-2458-4-29

Measuring Global Disease with Wikipedia: Success, Failure, and a Research Agenda
conference, January 2017

Priedhorsky, Reid; Osthus, Dave; Daughton, Ashlynn R.
Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW '17
DOI: 10.1145/2998181.2998183

Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance
journal, October 2015

Santillana, Mauricio; Nguyen, André T.; Dredze, Mark
PLOS Computational Biology, Vol. 11, Issue 10
DOI: 10.1371/journal.pcbi.1004513

Validating models for disease detection using twitter
conference, January 2013

Bodnar, Todd; Salathé, Marcel
Proceedings of the 22nd International Conference on World Wide Web - WWW '13 Companion
DOI: 10.1145/2487788.2488027

Detecting influenza epidemics using search engine query data
journal, February 2009

Ginsberg, Jeremy; Mohebbi, Matthew H.; Patel, Rajan S.
Nature, Vol. 457, Issue 7232
DOI: 10.1038/nature07634

Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions
journal, June 2018

Brooks, Logan C.; Farrow, David C.; Hyun, Sangwon
PLOS Computational Biology, Vol. 14, Issue 6
DOI: 10.1371/journal.pcbi.1006134

Evaluation of mechanistic and statistical methods in forecasting influenza-like illness
journal, July 2018

Kandula, Sasikiran; Yamana, Teresa; Pei, Sen
Journal of The Royal Society Interface, Vol. 15, Issue 144
DOI: 10.1098/rsif.2018.0174

Even a good influenza forecasting model can benefit from internet-based nowcasts, but those benefits are limited
journal, February 2019

Osthus, Dave; Daughton, Ashlynn R.; Priedhorsky, Reid
PLOS Computational Biology, Vol. 15, Issue 2
DOI: 10.1371/journal.pcbi.1006599

Ridge Regression: Biased Estimation for Nonorthogonal Problems
journal, February 2000

Hoerl, Arthur E.; Kennard, Robert W.
Technometrics, Vol. 42, Issue 1
DOI: 10.1080/00401706.2000.10485983

An Explicit Solution for Generalized Ridge Regression
journal, August 1975

Hemmerle, William J.
Technometrics, Vol. 17, Issue 3
DOI: 10.1080/00401706.1975.10489333

The solution path of the generalized lasso
journal, June 2011

Tibshirani, Ryan J.; Taylor, Jonathan
The Annals of Statistics, Vol. 39, Issue 3
DOI: 10.1214/11-AOS878

Pathway-Based Genomics Prediction using Generalized Elastic Net
journal, March 2016

Sokolov, Artem; Carlin, Daniel E.; Paull, Evan O.
PLOS Computational Biology, Vol. 12, Issue 3
DOI: 10.1371/journal.pcbi.1004790

Similar records in OSTI.GOV collections:

Reliability analysis framework for computer-assisted medical decision systems

Journal Article Habas, Piotr A. ; Zurada, Jacek M. ; Elmaghraby, Adel S. ; ... - Medical Physics

We present a technique that enhances computer-assisted decision (CAD) systems with the ability to assess the reliability of each individual decision they make. Reliability assessment is achieved by measuring the accuracy of a CAD system with known cases similar to the one in question. The proposed technique analyzes the feature space neighborhood of the query case to dynamically select an input-dependent set of known cases relevant to the query. This set is used to assess the local (query-specific) accuracy of the CAD system. The estimated local accuracy is utilized as a reliability measure of the CAD response to the querymore »« less
DOI: 10.1118/1.2432409
Data-enabled structure–property mappings for lanthanide-activated inorganic scintillators

Journal Article Pilania, Ghanshyam ; Liu, Xiang-Yang ; Wang, Zhehui - Journal of Materials Science

The use of machine learning (ML) models toward development of validated structure–property relationships for two fundamental properties of activated inorganic scintillators for high energy radiation detection, namely the light yield (LY) and the decay time constant, is explored. The ML models are built on easily accessible proxies of materials—interchangeably referred to as features, descriptors or fingerprints—that are carefully selected on the basis of a physical understanding of the scintillation mechanism. Our study indicates that the developed physics-based ML models employing kernel ridge regression (KRR) and AdaBoost algorithm applied on top of a decision tree-based regression are able to “learn” themore »« less
Cited by 2
DOI: 10.1007/s10853-019-03434-7

Full Text Available
Correction of confidence intervals in excess relative risk models using Monte Carlo dosimetry systems with shared errors

Journal Article Zhang, Zhuo ; Preston, Dale L. ; Sokolnikov, Mikhail ; ... - PLoS ONE

Introduction: Measurement errors are ubiquitous in epidemiological studies, especially for doses arising from environmental and occupational exposures, which are difficult to assess. Correction methods for independent measurement errors, have been comprehensively described elsewhere, including regression calibration, simulation extrapolation (SIMEX), etc. However, when exposure estimates are constructed using complicated physical and biological models, uncertainties in the dosimetry system can become very complex. In such systems, uncertainties in some parameters may affect a large group of study participants simultaneously, and hence are “shared” as opposed to independent dosimetric uncertainties. Representing the structure of the uncertainty in the dosimetry by providing multiple realizationsmore »« less
Cited by 9
DOI: 10.1371/journal.pone.0174641

Full Text Available
Dose Response for Radiation Cataractogenesis: A Meta-Regression of Hematopoietic Stem Cell Transplantation Regimens

Journal Article Hall, Matthew D. ; Schultheiss, Timothy E., E-mail: schultheiss@coh.org ; Smith, David D. ; ... - International Journal of Radiation Oncology, Biology and Physics

Purpose/Objective(s): To perform a meta-regression on published data and to model the 5-year probability of cataract development after hematopoietic stem cell transplantation (HSCT) with and without total body irradiation (TBI). Methods and Materials: Eligible studies reporting cataract incidence after HSCT with TBI were identified by a PubMed search. Seventeen publications provided complete information on radiation dose schedule, fractionation, dose rate, and actuarial cataract incidence. Chemotherapy-only regimens were included as zero radiation dose regimens. Multivariate meta-regression with a weighted generalized linear model was used to model the 5-year cataract incidence and contributory factors. Results: Data from 1386 patients in 21 seriesmore »« less
DOI: 10.1016/J.IJROBP.2014.07.049
Getting more from heterogeneous HIV-1 surveillance data in a high immigration country: estimation of incidence and undiagnosed population size using multiple biomarkers

Journal Article Giardina, Federica ; Romero-Severson, Ethan O. ; Axelsson, Maria ; ... - International Journal of Epidemiology

Most HIV infections originate from individuals who are undiagnosed and unaware of their infection. Estimation of this quantity from surveillance data is hard because there is incomplete knowledge about (i) the time between infection and diagnosis (TI) for the general population, and (ii) the time between immigration and diagnosis for foreign-born persons. We developed a new statistical method for estimating the incidence of HIV-1 and the number of undiagnosed people living with HIV (PLHIV), based on dynamic modelling of heterogeneous HIV-1 surveillance data. The methods consist of a Bayesian non-linear mixed effects model using multiple biomarkers to estimate TI ofmore »« less
DOI: 10.1093/ije/dyz100

Full Text Available

Similar Records

This content will become publicly available on October 1, 2020

Title: Estimating influenza incidence using search query deceptiveness and generalized ridge regression

Citation Formats

Importance of disease surveillance journal, December 1974

Timeliness of Nongovernmental versus Governmental Global Outbreak Communications journal, July 2012

Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness journal, January 2018

Evaluation of reporting timeliness of public health surveillance systems for infectious diseases journal, July 2004

Measuring Global Disease with Wikipedia: Success, Failure, and a Research Agenda conference, January 2017

Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance journal, October 2015

Validating models for disease detection using twitter conference, January 2013

Detecting influenza epidemics using search engine query data journal, February 2009

Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions journal, June 2018

Evaluation of mechanistic and statistical methods in forecasting influenza-like illness journal, July 2018

Even a good influenza forecasting model can benefit from internet-based nowcasts, but those benefits are limited journal, February 2019

Ridge Regression: Biased Estimation for Nonorthogonal Problems journal, February 2000

An Explicit Solution for Generalized Ridge Regression journal, August 1975

The solution path of the generalized lasso journal, June 2011

Pathway-Based Genomics Prediction using Generalized Elastic Net journal, March 2016

Importance of disease surveillance
journal, December 1974

Timeliness of Nongovernmental versus Governmental Global Outbreak Communications
journal, July 2012

Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness
journal, January 2018

Evaluation of reporting timeliness of public health surveillance systems for infectious diseases
journal, July 2004

Measuring Global Disease with Wikipedia: Success, Failure, and a Research Agenda
conference, January 2017

Combining Search, Social Media, and Traditional Data Sources to Improve Influenza Surveillance
journal, October 2015

Validating models for disease detection using twitter
conference, January 2013

Detecting influenza epidemics using search engine query data
journal, February 2009

Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions
journal, June 2018

Evaluation of mechanistic and statistical methods in forecasting influenza-like illness
journal, July 2018

Even a good influenza forecasting model can benefit from internet-based nowcasts, but those benefits are limited
journal, February 2019

Ridge Regression: Biased Estimation for Nonorthogonal Problems
journal, February 2000

An Explicit Solution for Generalized Ridge Regression
journal, August 1975

The solution path of the generalized lasso
journal, June 2011

Pathway-Based Genomics Prediction using Generalized Elastic Net
journal, March 2016