Using Pandemic-Era Longitudinal Surveillance Data to Improve Investigations of Carbapenem-Resistant Acinetobacter baumannii Clusters

Abstract

Objectives:

Epidemiologic investigations of multidrug-resistant organism (MDRO) clusters depend on a thorough history of health care exposures for case patients; however, histories are often incomplete. We describe how the robust influx of longitudinal infectious disease surveillance data from the COVID-19 pandemic improved whole-genome sequence–related cluster investigations and validated single nucleotide polymorphism (SNP) cluster definition thresholds for carbapenem-resistant Acinetobacter baumannii (CRAB) in Massachusetts.

Methods:

We used data from infectious disease laboratory test results reported through an integrated person-based surveillance system. We extracted all results from January 1, 2019, through March 19, 2024, for each CRAB case patient in a cluster to identify health care exposures. In addition, we extracted data from epidemiologic investigations. We used data to identify spatial links between cases. We combined timelines with whole-genome sequence data to determine whether genetically related cases were spatially linked.

Results:

We extracted 2354 test results for 69 CRAB case patients across 9 clusters; 2007 test results were from COVID-19 events. Three-quarters (n = 1775) of test results indicated a health care exposure not identified through standard investigation. Fifty-five case patients had a spatial link with at least 1 other case patient in their cluster. The median number of SNP differences between all spatially linked cases and all non–spatially linked cases was 4 SNPs and 10 SNPs, respectively.

Practice Implications:

Using longitudinal surveillance data identified possible CRAB transmission events undetected through standard investigation. Comparing the median SNP differences between spatially linked and non–spatially linked cases confirmed that the 10-SNP threshold was appropriate for defining CRAB clusters. Health departments can apply this method to enhance infectious disease investigations and determine appropriate SNP thresholds for infectious disease clusters.