|
![]()
| Kevin Brown Person1 #715372 Dr Kevin A. Brown is a scientist in health protection at Public Health Ontario. | 
Areas of Expertise - epidemiology
- statistics
- hospital-acquired infection
- C. difficile
- health services research
Appointments - Associate Professor, Dalla Lana School of Public Health, University of Toronto
Academic Degrees and Accreditations - Doctor of Philosophy (Epidemiology), Dalla Lana School of Public Health, University of Toronto
Master of Science (Biostatistics), University of North Carolina at Chapel Hill PHO Research Interests - Validating medico-administrative and electronic medical record data.
- Identifying facility factors that drive hospital-acquired infection rates.
- Describing patient movement between healthcare facilities and the community.
- Statistical methods for measuring risk factor magnitude and duration.
PHO Research Activities - Measuring the microbial burden of C. difficile spores on hospital surfaces and in the air and its role in onward transmission of C. difficile and using this information to inform infection control practice.
- Understanding how health care facility antibiotic prescribing patterns and interfacility patient movement impacts the incidence and spread of hospital acquired infections in Ontario.
|
+Citations (2) - CitationsAjouter une citationList by: CiterankMapLink[2] Association Between Nursing Home Crowding and COVID-19 Infection and Mortality in Ontario, Canada
En citant: Kevin A. Brown, Aaron Jones, Nick Daneman, Adrienne K. Chan, Kevin L. Schwartz, Gary E. Garber, Andrew P. Costa, Nathan M. Stall
Publication date: 9 November 2020
Publication info: JAMA Intern Med. 2021;181(2):229-236
Cité par: David Price 8:08 PM 16 November 2023 GMT
URL:
DOI: https://doi.org/10.1001/jamainternmed.2020.6466
| | Extrait - [JAMA Internal Medicine 9 November 2020]
Importance: Nursing home residents have been disproportionately affected by coronavirus disease 2019 (COVID-19). Prevention recommendations emphasize frequent testing of health care personnel and residents, but additional strategies are needed.
Objective: To develop a reproducible index of nursing home crowding and determine whether crowding was associated with COVID-19 cases and mortality in the first months of the COVID-19 epidemic.
Design, Setting, and Participants: This population-based retrospective cohort study included more than 78 000 residents across more than 600 nursing homes in Ontario, Canada, and was conducted from March 29 to May 20, 2020.
Exposures: The nursing home crowding index equaled the mean number of residents per bedroom and bathroom.
Main Outcomes and Measures: The cumulative incidence of COVID-19 cases confirmed by a validated nucleic acid amplification assay and mortality per 100 residents; the introduction of COVID-19 into a home (≥1 resident case) was a negative tracer.
Results: Of 623 homes in Ontario, we obtained complete information on 618 homes (99%) housing 78 607 residents (women, 54 160 [68.9%]; age ≥85 years, 42 919 [54.6%]). A total of 5218 residents (6.6%) developed COVID-19 infection, and 1452 (1.8%) died of COVID-19 infection as of May 20, 2020. COVID-19 infection was distributed unevenly across nursing homes; 4496 infections (86%) occurred in 63 homes (10%). The crowding index ranged across homes from 1.3 (mainly single-occupancy rooms) to 4.0 (exclusively quadruple occupancy rooms); 308 homes (50%) had a high crowding index (≥2). Incidence in high crowding index homes was 9.7% vs 4.5% in low crowding index homes (P < .001), while COVID-19 mortality was 2.7% vs 1.3%, respectively (P < .001). The likelihood of COVID-19 introduction did not differ (high = 31.3% vs low = 30.2%; P = .79). After adjustment for regional, nursing home, and resident covariates, the crowding index remained associated with an increased incidence of infection (relative risk [RR] = 1.73, 95% CI, 1.10-2.72) and mortality (RR, 1.69; 95% CI, 0.99-2.87). A propensity score analysis yielded similar conclusions for infection (RR, 2.09; 95% CI, 1.30-3.38) and mortality (RR, 1.83; 95% CI, 1.09-3.08). Simulations suggested that converting all 4-bed rooms to 2-bed rooms would have averted 998 COVID-19 cases (19.1%) and 263 deaths (18.1%).
Conclusions and Relevance: In this cohort of Canadian nursing homes, crowding was common and crowded homes were more likely to experience larger and deadlier COVID-19 outbreaks. |
|
|