Evaluation of a national microbiological surveillance system to inform automated outbreak detection

TL;DR: To combat the threat to human health and biosecurity from antimicrobial resistance, an understanding of its mechanisms and drivers is needed, and broad ranging, multidisciplinary research is needed across these five levels.

TL;DR: The spatial-temporal interaction was statistically meaningful and the prevalence of tuberculosis was influenced by the time and space interaction effect, as well as the ecological influential factors for tuberculosis.

TL;DR: A minority of notification systems meets either predefined, standardized or disease specific timeframes, and systems involving reporting by laboratories most often complied sufficiently with predefined or standardized timeframes.

TL;DR: In adults up to 60–69 years of age and in pregnant women, iGBS incidence increased with higher levels of socioeconomic deprivation, and underlying conditions were highly prevalent in nonpregnant adult case-patients.

TL;DR: There has been a surge in interest in statistical methods for the early detection of infectious disease outbreaks over the past decade as mentioned in this paper, and this growth in interest has given rise to much new methodological work, ranging across the spectrum of statistical methods.

TL;DR: It is found that the new system greatly reduces the number of alarms while maintaining good overall performance and in some instances increasing the sensitivity.

TL;DR: An automated statistical software, WHONET-SaTScan, is described and the potential it has to identify hospital infection clusters that had escaped routine detection is identified.

TL;DR: Automated surveillance with user-definable control charts for cluster identification was more sensitive than routine methods and is capable of operating with high specificity and positive predictive value in a time-efficient manner.