Les facteurs institutionnels associés aux infections et à la mortalité COVID-19 en centre d’hébergement pendant la première vague : une analyse de 17 CHSLD à Montréal

Background: In the midst of the COVID-19 pandemic, the population of long-term care residents has been the hardest hit by infections and deaths all around the world. Yet, these same individuals have been excluded from vast segments of the scientific literature. This thesis describes the evolution of outbreaks in 17 public long-term care facilities (“CHSLD”) in Montreal, some of which were severely affected and others were relatively spared during the first wave (February 23 to July 12, 2020), in search of risk factors associated with COVID-19 cases and deaths.  Methods: Institutional-level data on the 17 CHSLDs were collected from relevant administrative departments within the establishment (CIUSSS Centre-Sud-de-l'Île-de-Montréal), and individual-level data was obtained from the chart reviews of 1,197 first wave COVID-19 patients. For the ARIMA analysis, time series were built using the crude incidence rates among CHSLD residents and in the city of Montreal, in order to assess the impact of two interventions – introduction of the mask-wearing policy and generalized testing among residents and staff. For the analysis of facility-level infection rates, negative binomial regression models were built to estimate the effects of several institutional risk factors on incident cases. As for the excess mortality analysis, excess death and relative mortality were estimated using one-sample t-tests and rate ratio tests to compare 2020 deaths with average deaths in the previous four years (2016-2019), for the period of February to July. Lastly, for the survival analysis of the retrospective cohort, mixed-effects logistic regression models were used to identify institutional factors and treatments associated with 30-day mortality after a COVID-19 diagnosis, while controlling for individual risk factors.  Results: In the ARIMA time series analysis, each additional case per 100,000 per day in Montreal was associated with a 0.051 (95%CI 0.044 to 0.058) increase in CHSLD daily incidence a week later, among at-risk residents. In addition, while controlling for community transmission, increased testing intensity was associated with a 11.8 (95%CI -15.1 to -8.5) decrease in CHSLD daily incidence two weeks later, among at-risk residents.  In the negative binomial regression model for facility-level COVID-19 infections, poor performance on ministry audits (IRR 3.0  95%CI 1.1 to 7.8), severe shortage of auxiliary nurses (IRR 3.2 95%CI 1.4 to 7.2) and lower average autonomy scores (IRR 2.1 95%CI 1.4 to 3.1) were associated with incident cases, while the presence of a COVID-19 unit or “red zone” (IRR 0.56 95%CI 0.34 to 0.92) was inversely associated with infections.  For the 17 CHSLDs, excess deaths from February to July 2020 was 428 (95%CI 409 to 447). Compared to the same period in the previous four years, 2020 mortality during the first wave was 2.3 (IRR 95%CI 2.1 to 2.5) times higher. For a subset of 12 facilities that experienced substantial outbreaks, excess deaths in 2020 varied from 5.2 to 41.9 deaths per 100 beds, with significant excess mortality between 1.9 and 3.8, relative to previous years.  According to the mortality analysis by mixed-effects logistic regression, individual risk factors associated with 30-day mortality after a COVID-19 diagnosis were age (OR 1.58  95%CI 1.35 to 1.85 per additional 10 years), male sex (OR 2.37  95%CI 1.70 to 3.32), loss of autonomy (OR 1.12  95%CI 1.05 to 1.20 per unit increase of Iso-SMAF profile), C-level (OR 3.43  95%CI 1.57 to 7.51) or D-level (OR 3.61 95%CI 1.47 to 8.89) medical intervention compared to A-level, as well as being diagnosed with a neurocognitive disorder (OR 1.54 95%CI 1.04 to 2.29) or congestive heart failure (OR 2.36 95%CI 1.45 to 3.85). Treatment with thromboprophylaxis (OR 0.42 95%CI 0.29 to 0.63) and diagnosis after April 20, 2020 (OR 0.46 95%CI 0.33 to 0.65) were associated with 30-day survival. As for institutional risk factors, severe shortage of auxiliary nurses (OR 1.91 95%CI 1.14 to 3.21) and facility size (OR 1.77  95%CI 1.17 to 2.68 per 100 beds) increased the odds of dying within 30 days.  Conclusion: This study identified several modifiable risk factors at the institutional level associated with COVID-19 infections and deaths, including testing strategies, adherence to ministry directives for infection prevention, auxiliary nurse shortages, and number of beds per facility. Future policies and regulations targeting long-term care facilities will need to tackle these critical issues, for this pandemic and beyond.

Keyphrases: COVID-19, SRAS-CoV-2, SARS-CoV-2, CHSLD, Infection, Long-term care, Nursing home, Geriatrics, Death