Invasive Pneumococcal Strain Distributions and Isolate Clusters Associated With Persons Experiencing Homelessness During 2018

Abstract

Background: We aimed to characterize invasive pneumococcal disease (IPD) isolates collected from multistate surveillance in the United States during 2018 and examine within-serotype propensities of isolates to form related clusters.

Methods: We predicted strain features using whole genome sequencing obtained from 2885 IPD isolates obtained through the Center for Disease Control and Prevention's Active Bacterial Core surveillance (ABCs), which has a surveillance population of approximately 34.5 million individuals distributed among 10 states. Phylogenetic analysis was provided for serotypes accounting for ≥27 isolates.

Results: Thirteen-valent pneumococcal conjugate vaccine (PCV13) serotypes together with 6C accounted for 23 of 105 (21.9%) of isolates from children aged <5 years and 820 of 2780 (29.5%) isolates from those aged ≥5 years. The most common serotypes from adult IPD isolates were serotypes 3 (413/2780 [14.9%]), 22F (291/2780 [10.5%]), and 9N (191/2780 [6.9%]). Among child IPD isolates, serotypes 15BC (18/105 [17.1%]), 3 (11/105 [10.5%]), and 33F (10/105 [9.5%]) were most common. Serotypes 4, 12F, 20, and 7F had the highest proportions of isolates that formed related clusters together with the highest proportions of isolates from persons experiencing homelessness (PEH). Among 84 isolates from long-term care facilities, 2 instances of highly related isolate pairs from co-residents were identified.

Conclusions: Non-PCV13 serotypes accounted for >70% of IPD in ABCs; however, PCV13 serotype 3 is the most common IPD serotype overall. Serotypes most common among PEH were more often associated with temporally related clusters identified both among PEH and among persons not reportedly experiencing homelessness.

Keywords: antimicrobial resistance; clonal complexes; pneumococcal serotypes; temporally related isolate clusters.

Figure 1.

Active Bacterial Core surveillance serotype distribution among individuals aged <5 years. The primary clonal complex (blue) indicated for each serotype corresponds to the single most commonly occurring clonal complex listed in Supplementary Table 1. Serotype “15D” is a putative newly discovered serotype highly related to serotypes 15A and 15F, based upon a unique serologic profile and cps locus composition (B. Beall, unpublished data).

Figure 2.

A, Active Bacterial Core surveillance (ABCs) serotype distribution among individuals aged ≥5 years. The primary clonal complex (CC; blue) indicated for each serotype corresponds to the single most commonly occurring CC listed in Supplementary Table 1. B, ABCs serotype distribution among persons experiencing homelessness. The primary CC (blue) indicated for each serotype corresponds to the single most commonly occurring CC listed in Supplementary Table 1. C, Numbers of isolates within each serotype sharing ≤10 single-nucleotide polymorphisms with at least 1 other isolate within entire sampling of serotype (90%–100% of all isolates within each serotype). Number is percentage of isolates within total isolate comparison. Abbreviations: PEH, people experiencing homelessness; PNEH, people not experiencing homelessness.

Figure 3.

Phylogenetic analysis of serotype 4 isolates. The tree with the highest log likelihood (−73 581.17) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying neighbor-joining and BioNJ algorithms to a matrix of pairwise distances estimated using the maximum composite likelihood approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 100 nucleotide sequences. There was a total of 12 968 positions in the final dataset. Isolates from people experiencing homelessness (PEH) are indicated in red font. Isolates sharing ≤5 single-nucleotide polymorphisms (SNPs) with neighboring isolates are shaded. Predicted antimicrobial resistance is shown below each isolate (ery, erythromycin resistant; cli, clindamycin resistant; cot, cotrimoxazole resistant; cotI, intermediately cotrimoxazole resistant; tet, tetracycline resistant [predictive pipeline features for each resistance provided for each isolate in Supplementary Table 1]). ABCs sites are color coded in lines below the tree with county also indicated for each isolate as coded below. The relevant counties are indicated below each of the 5 relevant Active Bacterial Core surveillance (ABCs) sites with total number of year 2018 isolates indicated from people not experiencing homelessness (PNEH) and PEH and within each county. The ABCs sites include the 5 indicated Colorado (CO) Denver area counties and the 3 indicated California (CA) San Francisco Bay area counties. The entire states of New Mexico (NM) and Minnesota are included in ABCs as well as the 6-county Maryland area. Relative locations of the relevant (red font) CO, CA, and NM counties are indicated at right.

Figure 4.

Phylogenetic analysis of serotype 12F isolates. The tree with the highest log likelihood (−73 581.74) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying neighbor-joining and BioNJ algorithms to a matrix of pairwise distances estimated using the maximum composite likelihood approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 94 nucleotide sequences. There was a total of 12 659 positions in the final dataset. Figure features and abbreviations are as described for Figure 3. Active Bacterial Core surveillance (ABCs) surveillance areas for Colorado, California, New Mexico, Minnesota, and Maryland are described in the Figure 3 legend. ABCs areas also include Connecticut (entire state) and selected counties of Tennessee, Georgia, Oregon, and New York [3].

Figure 5.

Phylogenetic analysis of serotype 20 isolates. The tree with the highest log likelihood (−51780.06) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying neighbor-joining and BioNJ algorithms to a matrix of pairwise distances estimated using the maximum composite likelihood approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 99 nucleotide sequences. There was a total of 10 234 positions in the final dataset. Figure features and abbreviations are as described for Figures 3 and 4.

Figure 6.

Phylogenetic analysis of serotype 7F isolates. The tree with the highest log likelihood (−56 624.18) is shown. Initial tree(s) for the heuristic search were obtained automatically by applying neighbor-joining and BioNJ algorithms to a matrix of pairwise distances estimated using the maximum composite likelihood approach, and then selecting the topology with superior log likelihood value. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The analysis involved 34 nucleotide sequences. There was a total of 11 050 positions in the final dataset. Figure features and abbreviations are as described for Figures 3 and 4.

Figure 7.

Combined minimum inhibitory concentration phenotype distributions for penicillin, erythromycin, and clindamycin within each serotype for year 2018 Active Bacterial Core surveillance pneumococcal isolates predicted from bioinformatics pipeline data. Cumulative data from each isolate are included in Supplementary Table 1. Abbreviations: cliR, clindamycin-resistance; eryR, erythromycin-resistance; pen, penicillin-resistance.