112 Impact of socio-demographic factors and community remoteness on RSV hospitalization rates in young children in British Columbia: A population-based retrospective cohort study
Bibliographic record
Abstract
Abstract Background Respiratory syncytial virus (RSV) infection is a leading cause of hospital admissions in young paediatric patients. Infants in remote communities may be disproportionately affected by severe infections, leading to higher RSV-related hospitalization rates, but data are lacking on contributing factors. Objectives We aimed to determine the contribution of social factors on the risk of RSV-related hospital admission in children residing in remote communities in British Columbia (BC). Design/Methods This population-based retrospective cohort study included all children born in BC from 2013 to 2023, registered in the provincial health service plan, followed up until their 2nd birthday or April 1st, 2024, whichever came first. Data were obtained from the BC Covid-19 Cohort. RSV hospital admissions were defined using ICD-10 codes (J12.1, J20.5, J21.0 and B97.4), with incidence rates (IR) calculated per person-years. The child’s community health service area was used to assign one of four remoteness categories (remote, rural, urban, metropolitan) defined by the BC Ministry of Health based on Statistics Canada’s Index of Remoteness. Area-level socio-economic factors from the 2016 Canadian Census included household size, neighbourhood income, and the BC-Canadian Index of Multiple Deprivation (CMID). Mixed-effects Poisson regression was used to model the risk of RSV hospitalization by level of remoteness after adjustment for sex, co-morbidities, prematurity and socio-economic factors. Results Of 431,157 children, 4,861 (1.1%) were hospitalized for RSV, including 55 (1.7%) from remote communities. IRs for RSV admissions were significantly higher in remote communities compared to metropolitan areas [8.5 (6.4-11.1) versus 5.0 (4.8-5.2) per 1000 person years, respectively]. The proportions of PICU stays and the need for air transport were also highest in remote communities (Table 1). Children from remote communities had poorer scores on several socio-economic dimensions compared to metropolitan communities, particularly for neighbourhood income, economic dependency and situational vulnerability (p<0.0001 by chi-square; Table 1). After adjusting for all socio-economic factors, a 38% increased RSV hospitalization risk remained in remote communities. Conclusion While socio-economic factors affect RSV hospitalization risk across all geographic areas, the impact is disproportionately higher for children born in remote communities. This study emphasizes the importance of socio-economic factors and reveals unidentified remoteness-related factors that need to be explored to guide interventions to eliminate the high RSV burden in these communities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".