Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Hypothesis generation about potential food and other exposures is a critical step in an enteric disease outbreak investigation, helping to focus investigation efforts and use of limited resources. Historical outbreak data are an important source of information for hypothesis generation, providing data on common food- and animal-pathogen pairs and other epidemiological trends. We developed a model to predict vehicles for Shiga toxin-producing and outbreaks using demographic and outbreak characteristics from outbreaks in the Centers for Disease Control and Prevention's Foodborne Disease Outbreak Surveillance System (1998-2019) and Animal Contact Outbreak Surveillance System (2009-2019). We evaluated six algorithmic methods for prediction based on their ability to predict multiple class probabilities, selecting the random forest prediction model, which performed best with the lowest Brier score (0.0953) and highest accuracy (0.54). The model performed best for outbreaks transmitted by animal contact and foodborne outbreaks associated with eggs, meat, or vegetables. Expanding the criteria to include the two highest predicted vehicles, 83% of egg outbreaks were predicted correctly, followed by meat (82%), vegetables (74%), poultry (67%), and animal contact (62%). The model performed less well for fruit and poultry vehicles, and it did not predict any dairy outbreaks. The final model was translated into a free, publicly available online tool that can be used by investigators to provide data-driven hypotheses about outbreak vehicles as part of ongoing outbreak investigations. Investigators should use the tool for hypothesis generation along-side other sources, such as food-pathogen pairs, descriptive data, and case exposure assessments. The tool should be implemented in the context of individual outbreaks and with an awareness of its limitations, including the heterogeneity of outbreaks and the possibility of novel food vehicles.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1089/fpd.2021.0090 | DOI Listing |
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