ArticleBMC infectious diseases2026
MRSA transmission in hospitals across Alberta, Canada: a comparative study combining unidentified colonized cases upon admission.
Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMethicillin-resistant Staphylococcus aureus (MRSA) is a prevalent bacterium in medical settings. It can result in bloodstream infections and other severe illnesses, and patients may have a high risk of dying from these conditions. This study aimed to examine MRSA transmission in hospitals across Alberta and how undetected colonized patients on admission affect MRSA spread.
methodsWe used a Bayesian compartmental model to simulate MRSA spread across 106 acute care hospitals in Alberta. The model assumes that MRSA spreads through interactions between susceptible individuals and MRSA patients, including both hospital-acquired (HA) and community-acquired (CA) MRSA cases. Data from Edmonton, Calgary, rural Alberta and all regions in Alberta were used to fit the model. We also assumed that a small percentage of patients were colonized upon admission but were not promptly identified in hospitals, and we tested the model assumptions. Transmission rates were estimated using a Bayesian framework with Markov chain Monte Carlo (MCMC) algorithms. We compared transmission rates across several regions in Alberta and assessed the effect of MRSA prevalence at hospital admission on MRSA transmission.
resultsWhen the model fit the data in hospitals in all areas of Alberta, the average number of susceptible people colonized due to patients with HA-MRSA colonization, patients with HA-MRSA infections, patients with CA-MRSA colonization, and patients with CA-MRSA infections per contact per month are around 0.03 (95% CI: (0.001, 0.101)), 0.08 (95% CI: (0.002, 0.278)), 0.01 (95% CI: (0.000, 0.033)) and 0.05 (95% CI: (0.001, 0.182)), respectively. Assuming 0.8 colonized cases per 1000 admissions, the average number of susceptible people who become colonized due to patients with HA-MRSA infections per contact per month in Edmonton, Calgary and rural hospitals are 0.05 (95% CI: (0.001, 0.174)), 0.43 (95% CI: (0.018, 1.152)) and 0.22 (95% CI: (0.007, 0.722)), respectively. Assuming more unidentified colonized cases in hospitals, transmission rates between susceptible people and infected patients increase marginally.
conclusionMRSA transmission rates appear to be marginally higher in Calgary hospitals compared to Edmonton, and rural hospitals seem to have lower transmission rates than in Calgary but higher than in Edmonton, with 95% credible intervals (CIs) overlapping. Our model also suggests that infected patients have a higher probability of transmitting MRSA to susceptible people in most Alberta hospitals.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.