Utilizing genomic epidemiology to explore SARS CoV-2 transmission patterns and support outbreak investigations in long term care facilities, Washington State, April-October 2021
Peggy Douglas1, Veronica Burns2, Cassie Prather1, Stephanie Lunn3, Lauren Frisbie3, Drew Pratt2, Trent MacAllister1, Allison Templeton1, Audrey Brezak1, Nailah Smith1, Lynae Kibiger1
1Washington State Department of Health, Office of Communicable Disease Epidemiology, Healthcare Associated Infections, 2Spokane Regional Health District, 3Washington State Department of Health Office of Communicable Disease Epidemiology, Molecular Epidemiology
Introduction
In Washington State, COVID-19 cases in long-term care facilities (LTCF) have accounted for less than 3% of all cases, yet 30% of all COVID-19 deaths. Individuals living in LTCFs have been disproportionately impacted by the COVID-19 pandemic due to several factors, including overall increased mortality from infection of SARS CoV-2 due to age and underlying illness, increased risk for transmission and outbreaks due to the congregate nature of LTCFs, and many LTCFs facing limited resources for personal protective equipment, testing supplies, infection prevention guidance, and staffing. Additionally, individuals in LTCFs with underlying diagnoses such as dementia often struggle to adhere to prevention strategies such as social distancing and masking, which contributes to increased transmission. When an outbreak of COVID-19 occurs in an LTCF, prompt identification of cases and implementation of transmission-based precautions are critically important measures to contain the outbreak within the facility. These measures are challenging to implement in large LTCFs that face limited space to isolate cases and limited access to testing supplies and staff to perform testing facility-wide. Throughout the pandemic, local health departments and the Washington State Department of Health have conducted focused outreach and epidemiological support for LTCFs experiencing outbreaks. Understanding disease transmission pathways would be of particular use in large facilities where those pathways are not always clear. Offering public health support to facilities in concert with whole genome sequencing and phylogenetic analysis is informative in several ways. Local and state public health employees can use this combination of techniques to better understand disease transmission patterns, guide surveillance testing approaches, identify epidemiologic linkages, and help manage outbreaks. From April to October 2021, two large LTCFs experienced COVID-19 outbreaks. Whole genome sequencing and phylogenetic analysis were leveraged to explore transmission patterns and complement outbreak epidemiology.
Methods
Case-related data from both outbreaks was exported from the Washington Disease Reporting System (WDRS). Sequences, retrieved from GISAID, were aligned to the Wuhan-1 reference genome using Nextalign version 1.11.0. Pairwise single nucleotide polymorphism (SNP) distance matrices were calculated using SNP-Dists version 0.8.2. Phylogenetic trees for each outbreak were generated using IQ-Tree multicore version 2.2.0-beta COVID-edition using the GTR+F+G4 nucleotide substitution model with 1000 bootstrap replicates. Trees were time-resolved using Tree Time, and MicrobeTrace was used to visualize the phylogeny, SNP heatmap, and identify clusters among sequences.
Results
For the duration of the outbreak period, each LTCF conducted facility-wide testing weekly. LTCF A tested 162 residents and 800 staff, and LTCF B tested 60 residents and 144 staff. Of all cases in LTCF A, 23% (n =27) were residents and 77% (n = 92) were staff, compared to 78% (n =28) residents and 22% (n = 7) staff in LTCF B. In LTCF A, 34% (n=40) of the cases had high-quality sequences available. Seven clusters of two or more genetically related sequences and twelve genetically unrelated sequences were identified. Five clusters involved resident and staff cases, linked by unit. Two clusters and remaining unrelated sequences were among staff. In LTCF B, 40% (n=14) of the cases had high-quality sequences available. Five clusters of two genetically related sequences and four genetically unrelated sequences were identified. All sequences were from residents of two floors. LTCF A outbreak shows more diversity between sequences with a maximum genetic distance of 70. LTCF B outbreak shows more similarities between the sequences, with a maximum genetic distance of 6 SNPs.
Conclusion
Phylogenetic analysis of the two outbreaks confirms differences in disease transmission patterns. Multiple independent introductions of SARS-CoV-2 were identified in LTCF A, compared to fewer introductions in LTCF B. Focused outbreak response can decrease the burden on LTCF resources and helps mitigate transmission risk in the facility efficiently. When LTCF outbreaks persist, genomic epidemiology is a valuable tool to understand transmission patterns and inform public health response to outbreaks.
LTCF A
LTCF B
