Optimization of Duplicate Pathogen Sequencing for Outbreak Detection

Background: Healthcare-associated infections (HAIs) are a well-known problem in medical care systems. Outbreak detection is necessary to identify and prevent potential HAI outbreaks. One new advancement in outbreak detection includes the use of proactive pathogen whole genome sequencing to detect outbreaks. Methods and Results: Using data from the Enhanced Detection System for Healthcare-associated Transmission (EDS-HAT), this study aimed to determine the ideal time to perform repeat sequencing for select bacterial pathogens and to determine if there is a relationship between the tissue source the isolate is collected from and the days until a new infection. After narrowing the scope of the study to focus on P. aeruginosa (n=170), the study found that although not statistically significant, there does appear to be a difference in time to identify a new infection. Between those that did not have an isolate source change and those that did with those that did have an isolate source change from the original isolate identifying new infections at a more rapid rate. Based on restricted mean survival time estimates and Kaplan-Meier plots, we suggest that from day 1-36 there may be no need to resequence isolates, but after day 90 there is evidence indicating it would be beneficial to resequence patient isolates. Conclusion: Although this study was unable to identify the ideal time to resequence patient isolates, we were able to characterize the typical time to infection which lays the groundwork for future research. Continuing this research will advance public health by enabling more rapid identification and containment of outbreaks, thereby mitigating their impact more effectively.