PMID- 24491921
OWN - NLM
STAT- MEDLINE
DCOM- 20140410
LR  - 20181202
IS  - 1879-3460 (Electronic)
IS  - 0168-1605 (Linking)
VI  - 175
DP  - 2014 Apr 3
TI  - Estimating the correlation between concentrations of two species of bacteria with 
      censored microbial testing data.
PG  - 1-5
LID - S0168-1605(14)00035-X [pii]
LID - 10.1016/j.ijfoodmicro.2014.01.007 [doi]
AB  - Indicator organisms, such as generic Escherichia coli (GEC) and coliforms, can be 
      used to measure changes in microbial contamination during the production of food 
      products. Large and consistent reductions in the concentration of these organisms 
      demonstrates an effective and well-controlled production process. Nevertheless, 
      it is unclear to what degree concentrations of indicator organisms are related to 
      pathogenic organisms such as Campylobacter and Salmonella on a sample-by-sample 
      basis. If a strong correlation exists between the concentrations of different 
      organisms, then the monitoring of indicator organisms would be a cost-effective 
      surrogate for the measurement of pathogenic organisms. Calculating the 
      correlation between the concentrations of an indicator and pathogenic organism is 
      complicated because microbial testing datasets typically contain a large 
      proportion of censored observations (i.e., samples where the true concentration 
      is not observable, with nondetects and samples that are only screen-test positive 
      being examples). This study proposes a maximum likelihood estimator that can be 
      used to estimate the correlation between the concentrations of indicator and 
      pathogenic organisms. An example based on broiler chicken rinse samples 
      demonstrates modest, but significant positive correlations between the 
      concentration of the indicator organism GEC when compared to the concentration of 
      both Campylobacter and Salmonella. A weak positive correlation was also observed 
      between concentrations of Campylobacter and Salmonella, but it was not 
      statistically significant.
CI  - Published by Elsevier B.V.
FAU - Williams, Michael S
AU  - Williams MS
AD  - Risk Assessment and Analytics Staff, Office of Public Health Science, Food Safety 
      and Inspection Service, United States Department of Agriculture, 2150 Centre Ave, 
      Building D., Fort Collins, CO 80526, United States. Electronic address: 
      mike.williams@fsis.usda.gov.
FAU - Ebel, Eric D
AU  - Ebel ED
AD  - Risk Assessment and Analytics Staff, Office of Public Health Science, Food Safety 
      and Inspection Service, United States Department of Agriculture, 2150 Centre Ave, 
      Building D., Fort Collins, CO 80526, United States.
LA  - eng
PT  - Journal Article
DEP - 20140117
PL  - Netherlands
TA  - Int J Food Microbiol
JT  - International journal of food microbiology
JID - 8412849
SB  - IM
MH  - Animals
MH  - Campylobacter/physiology
MH  - Chickens/microbiology
MH  - Colony Count, Microbial
MH  - Escherichia coli/physiology
MH  - Food Handling/standards
MH  - Food Microbiology/*methods/standards
MH  - *Models, Theoretical
MH  - Salmonella/physiology
MH  - Statistics as Topic
OTO - NOTNLM
OT  - Campylobacter
OT  - Maximum likelihood estimation
OT  - Risk assessment
OT  - Salmonella
EDAT- 2014/02/05 06:00
MHDA- 2014/04/11 06:00
CRDT- 2014/02/05 06:00
PHST- 2013/05/14 00:00 [received]
PHST- 2014/01/02 00:00 [revised]
PHST- 2014/01/11 00:00 [accepted]
PHST- 2014/02/05 06:00 [entrez]
PHST- 2014/02/05 06:00 [pubmed]
PHST- 2014/04/11 06:00 [medline]
AID - S0168-1605(14)00035-X [pii]
AID - 10.1016/j.ijfoodmicro.2014.01.007 [doi]
PST - ppublish
SO  - Int J Food Microbiol. 2014 Apr 3;175:1-5. doi: 10.1016/j.ijfoodmicro.2014.01.007. 
      Epub 2014 Jan 17.