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: 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
This paper examines county-level characteristic factors contributing to opioid-related overdose deaths in the United States. We categorized factors into three groups: demographic, socio-economic, and health care environmental group. These features were used as predictors to model the overdose deaths from all types of opioids including prescription (e.g., oxycodone and hydrocodone) and illicit opioids (e.g., heroin and fentanyl) to investigate general trend, as well as separate models for heroin and fentanyl. Multilevel mixed-effect regression was adopted to adequately model grouping effect across counties.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1109/EMBC44109.2020.9176465 | DOI Listing |
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