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[Preprint]. 2025 Apr 25:2025.04.20.25325828.
doi: 10.1101/2025.04.20.25325828.

Genomic Epidemiology of Healthcare-Associated Respiratory Virus Infections

Affiliations

Genomic Epidemiology of Healthcare-Associated Respiratory Virus Infections

Vatsala Rangachar Srinivasa et al. medRxiv. .

Update in

Abstract

Background: Respiratory virus transmission in healthcare settings is not well understood. To investigate the transmission dynamics of common healthcare-associated respiratory virus infections, we performed retrospective whole genome sequencing (WGS) surveillance at one pediatric and two adult teaching hospitals in Pittsburgh, PA.

Methods: From January 2, 2018, to January 4, 2020, nasal swab specimens positive for rhinovirus, influenza, human metapneumovirus (HMPV), or respiratory syncytial virus (RSV) from patients hospitalized for ≥3 days were sequenced on Illumina platform. High-quality genomes were assessed for genetic relatedness using ≤3 single nucleotide polymorphisms (SNPs) cut-off, except for rhinovirus (10 SNPs). Patient health records were reviewed for genetically related clusters to identify epidemiological connections.

Results: We collected 436 viral specimens from 359 patients: rhinovirus (n=291), influenza (n=50), HMPV (n=47), and RSV (n=48). Of these, 55% (197/359 patients) were from pediatric hospital and 45% from adult hospitals. Patients ranged in age from 14 days to 93 years, 61% were male, and 74% were white. WGS was performed on 61.2% (178/291) rhinovirus, 78% (39/50) influenza, 92% (44/48) RSV, and all HMPV specimens. Among high-quality genomes, we identified 14 genetically related clusters involving 36 patients, ranging in size from 2-5 patients. We identified common epidemiological links for 53% (19/36) of clustered patients; 63% (12/19) patients had same-unit stay, 26% (5/19) had overlapping hospital stays, and 11% (2/19) shared common provider. On average, genetically related clusters spanned 16 days (range:0-55 days).

Conclusion: WGS offered insights into respiratory virus transmission dynamics. These advancements could potentially improve infection prevention and control strategies, leading to enhanced patient safety and healthcare outcomes.

Keywords: genomic epidemiology; healthcare-associated infections; outbreak; respiratory viruses; whole genome sequencing.

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Conflict of interest statement

Declaration of Interests None

Figures

Figure 1.
Figure 1.
Phylogenetic tree of rhinovirus, human metapneumovirus (HMPV), respiratory syncytial virus (RSV), and influenza, by respiratory season, hospital, sex, and race. Tree scale represents the nucleotide substitutions per site. Colored branches represent viral subtypes, colored specimen IDs represent the same-patient specimens, and each vertical strip represents different demographic information.
Figure 2.
Figure 2.
Pairwise single nucleotide polymorphism (SNP) distributions for RSV (respiratory syncytial virus), influenza, and HMPV (human metapneumovirus) genomes. Pairwise SNPs were assessed for all genomes in a given viral subtype, and histograms show the distribution of pairwise SNP distances.
Figure 3.
Figure 3.
3a. Whole genome pairwise SNP distributions for different rhinovirus subtypes; 3b. Pairwise SNPs vs. days between specimens for rhinovirus specimens collected from the same patients and belonging to the same subtype (an outlier with >1500 SNPs was removed from the plot). Circles of the same color represent individual patients; 3c. Pairwise SNP distributions for the rhinovirus IRES region for different rhinovirus subtypes.
Figure 4.
Figure 4.
Cluster networks of respiratory virus genomes analyzed for putative transmission. The different color gradients within each virus represent different subtypes of the virus. The connected circles show patient specimens that were genetically related as defined by cutoffs described in the Methods section. The network plot was visualized with Gephi. RSV, respiratory syncytial virus; HMPV, human metapneumovirus
Figure 5.
Figure 5.
Presumed transmission patterns of genetically related respiratory virus clusters with >2 patients. Day 1 on x-axis is 5 days before the first positive test date within a cluster unless the specimen was collected on the first day of admission. Created in BioRender. Rangachar Srinivasa, V. (2025) https://BioRender.com/mdnle2e

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