Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Syndromic surveillance is a novel automated approach to monitoring influenza activity, but there is no consensus regarding the most informative data sources for use within such a system. By comparing physician billing data from Quebec, Canada and hospital admission records, we assessed the timeliness of medical visits for influenza-like illnesses (ILI) to two types of outpatient healthcare settings. Overall, ILI visits by children aged 5-17 years at community-based settings were the most strongly correlated with hospital admissions and gave the greatest lead over hospital admissions. However, a degree of year-to-year variation suggests that syndromic surveillance of influenza should not focus on just a single subgroup. These findings reveal the richness of these real-time data for epidemic monitoring and demonstrate the flexibility of syndromic surveillance. By using real-time data, an evolving epidemic can be rapidly characterized by its epidemiological patterns, which is not possible with traditional surveillance systems.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.jbi.2010.10.001 | DOI Listing |
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