We consider statistical inference for two fundamental hybrid systems based on masked data: series-parallel, and parallel-series. Under constant, and linear hazard functions for component life, we present the maximum likelihood, and interval estimation of parameters of interest. Simulation studies are performed to demonstrate the efficiency of the methods.
Adaptation to selective pressures is crucial for clinically important pathogens to establish epidemics, but the underlying evolutionary drivers remain poorly understood. The current epidemic of carbapenem-resistant Klebsiella pneumoniae (CRKP) poses a significant threat to public health. In this study we analyzed the genome sequences of 794 CRKP bloodstream isolates collected in 40 hospitals in China between 2014 and 2019. We uncovered a subclonal replacement in the predominant clone ST11, where the previously prevalent subclone OL101:KL47 was replaced by O2v1:KL64 over time in a stepwise manner. O2v1:KL64 carried a higher load of mobile genetic elements, and a point mutation exclusively detected in the recC of O2v1:KL64 significantly promotes recombination proficiency. The epidemic success of O2v1:KL64 was further associated with a hypervirulent sublineage with enhanced resistance to phagocytosis, sulfamethoxazole-trimethoprim, and tetracycline. The phenotypic alterations were linked to the overrepresentation of hypervirulence determinants and antibiotic genes conferred by the acquisition of an rmpA-positive pLVPK-like virulence plasmid and an IncFII-type multidrug-resistant plasmid, respectively. The dissemination of the sublineage was further promoted by more frequent inter-hospital transmission. The results collectively demonstrate that the expansion of O2v1:KL64 is correlated to a repertoire of genomic alterations convergent in a subpopulation with evolutionary advantages.
We consider the parameter inference for a two-parameter life distribution with bathtub-shaped or increasing failure rate function. We present the point and interval estimations for the parameter of interest based on type-II censored samples. Through intensive Monte-Carlo simulations, we assess the performance of the proposed estimation methods by a comparison of precision. Example applications are demonstrated for the efficiency of the methods.
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