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The ST131 multilocus sequence type (MLST) of Escherichia coli is a globally successful pathogen whose dissemination is increasing rates of antibiotic resistance. Numerous global surveys have demonstrated the pervasiveness of this clone; in some regions ST131 accounts for up to 30% of all E. coli isolates. However, many regions are underrepresented in these published surveys, including Africa, South America, and Asia. We collected consecutive bloodstream E. coli isolates from three countries in Southeast Asia; ST131 was the most common MLST type. As in other studies, the C2/H30Rx clade accounted for the majority of ST131 strains. Clinical risk factors were similar to other reported studies. However, we found that nearly all of the C2 strains in this study were closely related, forming what we denote the SEA-C2 clone. The SEA-C2 clone is enriched for strains from Asia, particularly Southeast Asia and Singapore. The SEA-C2 clone accounts for all of the excess resistance and virulence of ST131 relative to non-ST131 E. coli. The SEA-C2 strains appear to be locally circulating and dominant in Southeast Asia, despite the intuition that high international connectivity and travel would enable frequent opportunities for other strains to establish themselves.

BackgroundThe objective of this study was to develop multiple prediction tools that calculate the risk of developing dengue haemorrhagic fever.MethodsTraining data consisted of 1771 individuals from 2006–2008 admitted with dengue fever whereby 304 developed dengue haemorrhagic fever during hospitalisation. Least absolute shrinkage and selection operator regression was used to construct three types of calculators, static admission calculators and dynamic calculators that predict the risk of developing dengue haemorrhagic fever for a subsequent day (DAily Risk Tomorrow [DART]) or for any future point after a specific day since fever onset (DAily Risk Ever [DARE]).ResultsFrom 119 admission covariates, 35 were in at least one of the calculators, which reported area under the curve (AUC) values of at least 0.72. Addition of person-time data for DART improved AUC to 0.76. DARE calculators displayed a large increase in AUC to 0.79 past day 7 with the inclusion of a strong predictor, maximum temperature on day 6 since onset, indicative of a saddleback fever.ConclusionsAll calculators performed well when validated with 2005 data. Addition of daily variables further improved the accuracy. These calculators can be used in tandem to assess the risk of dengue haemorrhagic fever upon admission and updated daily to obtain more precise risk estimates.