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

Journal Article · · Frontiers in Public Health
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  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)
+ Show Author Affiliations

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.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1286929
Journal Information:
Frontiers in Public Health, Vol. 3, Issue 1; ISSN 2296-2565
Publisher:
Frontiers Research FoundationCopyright Statement
Country of Publication:
United States
Language:
English

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60 APPLIED LIFE SCIENCES
97 MATHEMATICS AND COMPUTING
disease co-occurrence
non-negative matrix factorization
public health surveillance
asthma
flu
electronic healthcare reimbursement claims