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Title: Discovering multi-scale co-occurrence patterns of asthma and influenza with the Oak Ridge bio-surveillance toolkit

Here, we describe a data-driven unsupervised machine learning approach to extract geo-temporal co-occurrence patterns of asthma and the flu from large-scale electronic healthcare reimbursement claims (eHRC) datasets. Specifically, we examine the eHRC data from 2009 to 2010 pandemic H1N1 influenza season and analyze whether different geographic regions within the United States (US) showed an increase in co-occurrence patterns of the flu and asthma. Our analyses reveal that the temporal patterns extracted from the eHRC data show a distinct lag time between the peak incidence of the asthma and the flu. While the increased occurrence of asthma contributed to increased flu incidence during the pandemic, this co-occurrence is predominant for female patients. The geo-temporal patterns reveal that the co-occurrence of the flu and asthma are typically concentrated within the south-east US. Further, in agreement with previous studies, large urban areas (such as New York, Miami, and Los Angeles) exhibit co-occurrence patterns that suggest a peak incidence of asthma and flu significantly early in the spring and winter seasons. Together, our data-analytic approach, integrated within the Oak Ridge Bio-surveillance Toolkit platform, demonstrates how eHRC data can provide novel insights into co-occurring disease patterns.
 [1] ;  [1] ;  [1] ;  [1] ;  [1] ;  [2] ;  [3] ;  [3]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. IMS Government Solutions (IMSGS), Inc., Fairfax, VA (United States)
  3. Univ. of Pittsburgh, Pittsburgh, PA (United States)
Publication Date:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Frontiers in Public Health
Additional Journal Information:
Journal Volume: 3; Journal Issue: 1; Journal ID: ISSN 2296-2565
Frontiers Research Foundation
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
Country of Publication:
United States
60 APPLIED LIFE SCIENCES; 97 MATHEMATICS AND COMPUTING; disease co-occurrence; non-negative matrix factorization; public health surveillance; asthma; flu; electronic healthcare reimbursement claims
OSTI Identifier: