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Title: Nowcasting influenza activity using Healthmap data.


Abstract not provided.

;  [1]
  1. (Boston Children's Hospital)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Org.:
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the DTRA CBD Conference held May 12-14, 2015 in St. Louis, MO.
Country of Publication:
United States

Citation Formats

Ray, Jaideep, and Brownstein, John. Nowcasting influenza activity using Healthmap data.. United States: N. p., 2015. Web.
Ray, Jaideep, & Brownstein, John. Nowcasting influenza activity using Healthmap data.. United States.
Ray, Jaideep, and Brownstein, John. 2015. "Nowcasting influenza activity using Healthmap data.". United States. doi:.
title = {Nowcasting influenza activity using Healthmap data.},
author = {Ray, Jaideep and Brownstein, John},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2015,
month = 4

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  • Abstract not provided.
  • We construct and verify a statistical method to nowcast influenza activity from a time-series of the frequency of reports concerning influenza related topics. Such reports are published electronically by both public health organizations as well as newspapers/media sources, and thus can be harvested easily via web crawlers. Since media reports are timely, whereas reports from public health organization are delayed by at least two weeks, using timely, open-source data to compensate for the lag in %E2%80%9Cofficial%E2%80%9D reports can be useful. We use morbidity data from networks of sentinel physicians (both the Center of Disease Control's ILINet and France's Sentinelles network)more » as the gold standard of influenza-like illness (ILI) activity. The time-series of media reports is obtained from HealthMap ( We find that the time-series of media reports shows some correlation ( 0.5) with ILI activity; further, this can be leveraged into an autoregressive moving average model with exogenous inputs (ARMAX model) to nowcast ILI activity. We find that the ARMAX models have more predictive skill compared to autoregressive (AR) models fitted to ILI data i.e., it is possible to exploit the information content in the open-source data. We also find that when the open-source data are non-informative, the ARMAX models reproduce the performance of AR models. The statistical models are tested on data from the 2009 swine-flu outbreak as well as the mild 2011-2012 influenza season in the U.S.A.« less
  • The computer expert system for fuel failure analysis of WWER during operation is presented. The diagnostics is based on the measurement of specific activity of reference nuclides in reactor primary coolant and application of a computer code for the data interpretation. The data analysis includes an evaluation of tramp uranium mass in reactor core, detection of failures by iodine and caesium spikes, evaluation of burnup of defective fuel. Evaluation of defective fuel burnup was carried out by applying the relation of caesium nuclides activity in spikes and relations of activities of gaseous fission products for steady state operational conditions. Themore » method of burnup evaluation of defective fuel by use of fission gas activity is presented in detail. The neural-network analysis is performed for determination of failed fuel rod number and defect size. Results of the expert system application are illustrated for several fuel campaigns on operating WWER NPPs. (authors)« less
  • A new multidimensional mapping technique is being developed which determines the three dimensional electron density distribution of the ionosphere over a wide area of several thousand kilometers at any time, from sounder data recorded at the previous period just before this time. Electron density profiles from five Digisonde stations in the northeastern regions of the North American continent are used to describe the electron distribution in a 30 deg longitude by 30 deg latitude region. The time histories over 32 hours of the profiles (the polynomial coefficients) from each station are Fourier transformed to determine the spectral components. For eachmore » spectral component a damped plane wave is fitted to amplitudes and phases at the five stations. This analysis is performed for each of the profile coefficients, and zonal maps are constructed as sums of these plane waves. This nowcasting technique can find applications in ray tracing for OTH radar, HF communication and HF direction finding.« less