Increased Severity of Multidrug-Resistant <i>Shigella sonnei</i> Infections in People Experiencing Homelessness
Bibliographic record
Abstract
BACKGROUND: Shigella sonnei has caused sexually transmitted enteric infections in men who have sex with men (MSM) in Vancouver. We recently observed a high rate of multidrug-resistant (MDR) S. sonnei bacteremia among persons experiencing homelessness (PEH). We aimed to describe the wider epidemiology, clinical outcomes, and genomics of S. sonnei infections over time. METHODS: A retrospective review of 163 patients with S. sonnei infections was undertaken from 2015 to 2022. We collected demographic, clinical, and microbiological data over 2 time periods: historical (2015-2020) and recent (2021-2022). Severe shigellosis definition included hospitalization, bacteremia, or death. Whole-genome sequencing was performed to identify genotype, infer relatedness, and predict antimicrobial resistance. RESULTS: S. sonnei infections increased from 8.3 (historical period) to 56.5 (recent period) cases/year. Over time, the primary population characteristics associated with shigellosis shifted from MSM (45; 98%) to PEH (86; 77%). The population intersection between MSM and PEH historically and recently was similar and occurred in 3 (6%) and 10 (9%) of patients, respectively. Severe shigellosis was significantly higher in the recent versus historical period (69 [61%] vs 7 [14%]; P < .001). A dominant clone of MDR S. sonnei, 3.6.1.1.2 (CipR.MSM5), emerged with resistance to all first- and second-line agents, yet with susceptibility to ceftriaxone. CONCLUSIONS: We observed a substantial increase in severe shigellosis and shift from sexually transmitted S. sonnei infections in MSM to likely environmental transmission among PEH. More severe disease associated with the 3.6.1.1.2 clone of MDR S. sonnei in PEH could be a result of underlying vulnerabilities of the affected population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".