Automated use of WHONET and SaTScan to detect outbreaks of Shigella spp. using antimicrobial resistance phenotypes

Abstract

SUMMARY Antimicrobial resistance is a priority emerging public health threat, and the ability to detect promptly outbreaks caused by resistant pathogens is critical for resistance containment and disease control efforts. We describe and evaluate the use of an electronic laboratory data system (WHONET) and a space–time permutation scan statistic for semi-automated disease outbreak detection. In collaboration with WHONET-Argentina, the national network for surveillance of antimicrobial resistance, we applied the system to the detection of local and regional outbreaks of Shigella spp. We searched for clusters on the basis of genus, species, and resistance phenotype and identified 19 statistical ‘events’ in a 12-month period. Of the six known outbreaks reported to the Ministry of Health, four had good or suggestive agreement with SaTScan-detected events. The most discriminating analyses were those involving resistance phenotypes. Electronic laboratory-based disease surveillance incorporating statistical cluster detection methods can enhance infectious disease outbreak detection and response.

AmWeb: a novel interactive web tool for antimicrobial resistance surveillance, applicable to both community and hospital patients

“…However, the group is also exploring the incorporation of real-time resistant phenotype profiling tools as used by WHONET to detect unusual individual resistance, clusters or potential outbreaks. 30 Following a successful pilot in three regions, the AmWeb web reporting tool is now being rolled out across England.…”

Los laboratorios de microbiología del mundo pueden convertirse en una red de detección microbiana

“…These have generally been sufficiently stable on repeated isolates of the same genus/species from the same patient to infer sufficient identity of that strain in another patient to detect most such transfers (30,48,51,52). They have also been shown to greatly increase sensitivity of detection of clusters of cases in trials of the SaTScan program (53,54).…”

“…Another set of algorithmic analyses running on the growing global database would screen for unusual time-space distribution of any subtypes, as we have done successfully with SaTScan in hospitals and for certain kinds of microbes in regions of countries (53,54). Whenever a statistical threshold is exceeded for an area, an alert is sent automatically to responders pre-selected for that area.…”

Bacterial genomes in epidemiology—present and future

“…Such an approach has had success in taking local surveillance data on antibiotic resistance, and making it more globally relevant through international programs such as WHOnet, designed to standardize and improve practice in measuring resistance in clinical laboratories [23][24][25] but with potential for additional functions including outbreak detection [26]. It is reasonable to think a similar approach could be beneficial for genomics.…”