Practicalities of Using Non-Local or Non-Recent Multilocus Sequence Typing Data for Source Attribution in Space and Time of Human Campylobacteriosis

Abstract

In this study, 1208 Campylobacter jejuni and C. coli isolates from humans and 400 isolates from chicken, collected in two separate periods over 12 years in The Netherlands, were typed using multilocus sequence typing (MLST). Statistical evidence was found for a shift of ST frequencies in human isolates over time. The human MLST data were also compared to published data from other countries to determine geographical variation. Because only MLST typed data from chicken, taken from the same time point and spatial location, were available in addition to the human data, MLST datasets for other Campylobacter reservoirs from selected countries were used. The selection was based on the degree of similarity of the human isolates between countries. The main aim of this study was to better understand the consequences of using non-local or non-recent MLST data for attributing domestically acquired human Campylobacter infections to specific sources of origin when applying the asymmetric island model for source attribution. In addition, a power-analysis was done to find the minimum number of source isolates needed to perform source attribution using an asymmetric island model. This study showed that using source data from other countries can have a significant biasing effect on the attribution results so it is important to carefully select data if the available local data lack in quality and/or quantity. Methods aimed at reducing this bias were proposed.