Statistical adjustment of culture-independent diagnostic tests for trend analysis in the Foodborne Diseases Active Surveillance Network (FoodNet), USA.

Background: Culture-independent diagnostic tests (CIDTs) are increasingly used to diagnose Campylobacter infection in the Foodborne Diseases Active Surveillance Network (FoodNet). Because CIDTs have different performance characteristics compared with culture, which has been used historically and is still used to diagnose campylobacteriosis, adjustment of cases diagnosed by CIDT is needed to compare with culture-confirmed cases for monitoring incidence trends.

Methods: We identified the necessary parameters for CIDT adjustment using culture as the gold standard, and derived formulas to calculate positive predictive values (PPVs). We conducted a literature review and meta-analysis to examine the variability in CIDT performance and Campylobacter prevalence applicable to FoodNet sites. We then developed a Monte Carlo method to estimate test-type and site-specific PPVs with their associated uncertainties.

Results: The uncertainty in our estimated PPVs was largely derived from uncertainty about the specificity of CIDTs and low prevalence of Campylobacter in tested samples. Stable CIDT-adjusted incidences of Campylobacter cases from 2012 to 2015 were observed compared with a decline in culture-confirmed incidence.

Conclusions: We highlight the lack of data on the total numbers of tested samples as one of main limitations for CIDT adjustment. Our results demonstrate the importance of adjusting CIDTs for understanding trends in Campylobacter incidence in FoodNet.