title: Relating calls to US poison centers for potential exposures to medications to Centers for Disease Control and Prevention reporting of influenza-like illness.
abstract: BACKGROUND
  The Centers for Disease Control (CDC) monitors influenza like illness (ILI) and the National Poison Data System (NPDS) warehouses call data uploaded by US poison centers regarding reported exposures to medication.
  
  
  OBJECTIVE
  We examined the relationship between calls to poison centers regarding reported exposures to medications commonly used to treat ILI and weekly reports of ILI.
  
  
  METHODS
  The CDC reports ILI, by age group, for each of 10 Health and Human Services (HHS) regions. We examined NPDS summary data from calls reported to poison centers regarding reported exposures to acetaminophen, cough/cold medications, and promethazine, for the same weeks, age groups, and HHS regions for influenza seasons 2000-2013. ILI and NPDS exposures were examined using graphical plots, descriptive statistics, stepwise regression analysis, and Geographic Information Systems (GIS).
  
  
  RESULTS
  About 5,101,841 influenza-like illness cases were reported to the CDC, and 2,122,940 calls regarding reported exposures to medications commonly used to treat ILI, were reported by poison centers to the NPDS over the 13 flu seasons. Analysis of stepwise models of the linear untransformed data involving 24 NPDS data groups and for 60 ILI measures, over the 13 influenza seasons, demonstrated that reported exposures to medications used to treat ILI correlated with reported cases of ILI with a median R(2 )=( )0.489 (min R(2 )=( )0.248, max R(2 )=( )0.717), with mean ± SD of R(2 )=( )0.494 ± 0.121. Median number of parameters used (degrees of freedom - 1) was 7.
  
  
  CONCLUSIONS
  NPDS data regarding poison center calls for selected ILI medication exposures were highly correlated with CDC ILI data. Since NPDS data are available in real time, it provides complimentary ILI monitoring. This approach may provide public health value in predicting other illnesses which are not currently as thoroughly monitored.
authors.affiliation: a Emergency Medicine, Oregon Health & Science University , Portland , OR , USA ;
authors.forename: Gillian A
authors.initials: GA
authors.lastname: Beauchamp
authors.affiliation: a Emergency Medicine, Oregon Health & Science University , Portland , OR , USA ;
authors.forename: Nathanael J
authors.initials: NJ
authors.lastname: McKeown
authors.affiliation: b Department of Geography , Old Dominion University , Norfolk , VA , USA.
authors.forename: Sergio
authors.initials: S
authors.lastname: Rodriguez
authors.affiliation: a Emergency Medicine, Oregon Health & Science University , Portland , OR , USA ;
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Spyker
mesh_terms: D000082:Acetaminophen / Q000506:poisoning; D000293:Adolescent; D000328:Adult; D016907:Adverse Drug Reaction Reporting Systems; D000367:Age Factors; D000368:Aged; D000700:Analgesics / Q000009:adverse effects; D018712:Analgesics, Non-Narcotic / Q000506:poisoning; D000932:Antiemetics / Q000009:adverse effects; D058633:Antipyretics / Q000009:adverse effects; D002487:Centers for Disease Control and Prevention, U.S.; D002648:Child; D002675:Child, Preschool; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007251:Influenza, Human / Q000150:complications* / Q000188:drug therapy*; D008297:Male; D008875:Middle Aged; D011039:Poison Control Centers / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D014481:United States / Q000453:epidemiology; D055815:Young Adult
chemical_list: D000700:Analgesics; D018712:Analgesics, Non-Narcotic; D000932:Antiemetics; D058633:Antipyretics; D000082:Acetaminophen
keywords: Centers for Disease Control and Prevention; Geographic Information Systems; National Poison Data System; epidemiology; influenza; poisoning; public health; statistical models