OBJECTIVES: The aim of this study is to identify demographic, clinical and medical care factors associated with mortality in three nursing homes.
METHODS: Two nursing homes were hospital-dependent, had connections with infection prevention and control departments, and had permanent physicians. Third nursing home had no direct connection with general hospital, no infection control practitioner, and no permanent physician. The main outcome was death.
RESULTS: During first 3 months of the outbreak, 224/375 (59.7%) residents were classified "COVID-19 cases" and 57/375 (15.2%) died. Hospital dependent nursing homes had lower COVID-19 case fatality rates in comparison to non-hospital dependent nursing home (15 [6.6%] vs 38 [25.8%], OR 0.20 [0.11-0.38], p = 0.001). During first 3 weeks of the outbreak, mortality in COVID-19 patients decreased if they had daily clinical examination (aOR: 0.09 [0.03-0.35], p = 0.01), 3 vital signs measurements per day (OR: 0.06 [0.01-0.30], p = 0.001) and prophylactic anticoagulation (OR: 0 [0.00-0.24], p = 0.001).
CONCLUSIONS: This study suggests that high mortality rates in some nursing homes during COVID-19 outbreak might be favoured by a lack of medical care management. Increasing human and material resources, encouraging presence of nursing home physicians and establishing connection with general hospitals should be consider to deal with present and future health disasters in nursing homes.
BACKGROUND: Isolation space must be expanded during pandemics involving airborne transmission. Little to no work has been done to establish optimal design strategies and implementation plans to ease surge capacity and expand isolation capacity over long periods in congregate living facilities. The COVID-19 pandemic has an airborne transmission component and requires isolation, which is difficult to accomplish in skilled nursing facilities.
PURPOSE: In this study we designed, implemented, and validated an isolation space at a skilled nursing facility in Lancaster, PA. The overall goal was to minimize disease transmission between residents and staff within the facility.
BASIC PROCEDURES: We created an isolation space by modifying an existing HVAC system of the SNF. We measured pressure on-site and performed computational fluid dynamics and Lagrangian particle-based modeling to test containment and possible transmission extent given the isolation space is considered negative rather than individual rooms.
MAIN FINDINGS: Pressure data shows the isolation space maintained an average (standard deviation) hourly value of -2.3 Pa (0.12 Pa) pressure differential between it and the external hallway connected to the rest of the facility. No transmission of SARS-CoV-2 between residents isolated to the space occurred, nor did any transmission to the staff or other residents occur. The isolation space was successfully implemented and, as of writing, continues to be operational through the pandemic.
OBJECTIVE: A Canadian health authority implemented a multisectoral intervention designed to control severe acute respiratory coronavirus virus 2 (SARS-CoV-2) transmission during long-term care facility (LTCF) outbreaks. The primary objective was to evaluate the effectiveness of the intervention 14 days after implementation.
DESIGN: Quasi-experimental, segmented regression analysis.
INTERVENTION: A series of outbreak measures classified into 4 categories: case and contact management, proactive case detection, rigorous infection control practices and resource prioritization and stewardship.
METHODS: A mixed-effects segmented Poisson regression model was fitted to the incidence rate of coronavirus disease 2019 (COVID-19), calculated every 2 days, within each facility and case type (staff vs residents). For each facility, the outbreak time period was segmented into an early outbreak period (within 14 days of the intervention) and postintervention period (beyond 14 days following the intervention). Model outputs quantified COVID-19 incidence trend and rate changes between these 2 periods. A secondary model was constructed to identify effect modification by case type.
RESULTS: The significant upward trend in COVID-19 incidence rate during the early outbreak period (rate ratio [RR], 1.07; 95% confidence interval [CI], 1.03-1.11; P < .001) reversed during the postintervention period (RR, 0.73; 95% CI, 0.67-0.80; P < .001). The average trend did not differ by case type during the early outbreak period (P > .05) or the postintervention period (P > .05). However, staff had a 70% larger decrease in the average rate of COVID-19 during the postintervention period than residents (RR, 0.30; 95% CI, 0.10-0.88; P < .05).
CONCLUSIONS: Our study provides evidence for the effectiveness of this intervention to reduce the transmission of COVID-19 in LTCFs. This intervention can be adapted and utilized by other jurisdictions to protect the vulnerable individuals in LTCFs.
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.
OBJECTIVE: With an eye toward possible public policy implications, our objective is to identify the socio-economic and demographic factors that drive the large variation in COVID-19 incidence rates observed within relatively compact geographic regions, and to quantify the relative impact of each of these factors. We use international comparisons as a starting point.
METHODS: New York City, consisting of some 175 zip codes, is an ideal arena to pursue the above study given the large variation in case incidence rates across zip codes. We conducted systematic regression studies employing data with zip code granularity. Our model specifications are based on a well-established epidemiologic model that explains the effects of household sizes on R0.
RESULTS: Average household size emerges as the single most important driver behind the large variation in COVID-19 incidence rates. It independently explains 62% of the variation. The percentage of the population above the age of 65 and the percentage below the poverty line are also strongly positively associated with zip code incidence rates. As to ethnic/racial characteristics, the percentages of African Americans, Hispanics and Asians within the population are significantly associated, but the magnitude of the impact is smaller. (The proportion of Asians within a zip code has a negative association.) Contrary to common belief, population density, by itself, does not have a significantly positive impact (other than when a high population is driven by large household sizes).
CONCLUSION: Our findings support implemented and proposed policies to quarantine patients and separate infected individuals from families or dormitories; they also support newly revised nursing home admission policies.
Coronavirus disease 2019 (COVID-19) remains a serious threat for long-term care facilities, and frequent screening of employees and residents places a substantial burden on those facilities. We report our successful multimodal prevention measures without frequent testing, which resulted in no cases within 20 nursing home units over the first 6 months of the pandemic.
Aims: For everyone with a positive test for SARS-CoV-2 in Norway, we studied whether age, sex, comorbidity, continent of birth and nursing home residency were risk factors for hospitalization, invasive mechanical ventilation treatment and death. Methods: Data for everyone who had tested positive for SARS-CoV-2 in Norway by end of June 2020 (N = 8569) were linked at the individual level to hospitalization, receipt of invasive mechanical ventilation treatment and death measured to end of July 2020. Underlying comorbidity was proxied by hospital-based in- or outpatient treatment during the two months before the SARS-CoV-2 test. Multivariable generalized linear models were used to assess risk ratios (RRs). Results: Risk of hospitalization was particularly high for elderly (for those aged 90 and above: RR 9.5; 95% confidence interval (CI) 7.1-12.7; comparison group aged below 50), Norwegian residents born in Asia, Africa or Latin-America (RR 2.1; 95% CI 1.9-2.4; comparison group born in Norway), patients with underlying comorbidity (RR 1.6; 95% CI 1.4-1.8) and men (RR 1.3; 95% CI 1.2-1.5). Men and residents born in Africa, Asia and Latin-America were also at higher risk of receiving ventilation treatment and dying, but the mortality risk was especially high for the elderly (for those aged 90 and above: RR 607.9; 95% CI 145.5-2540.1; comparison group aged below 50) and residents in nursing homes (RR 4.2; 95% CI 3.1-5.7). Conclusions: High age was the most important predictor of severe disease and death if infected with SARS-CoV-2, and nursing home residents were at particularly high risk of death.
OBJECTIVES: To assess changes in the mobility of staff between nursing homes in Ontario, Canada, before and after enactment of public policy restricting staff from working at multiple homes.
DESIGN: Pre-post observational study.
SETTING: and Participants: 623 nursing homes in Ontario, Canada, between March 2020 and June 2020.
METHODS: We used GPS location data from mobile devices to approximate connectivity between all 623 nursing homes in Ontario during the 7 weeks before (March 1-April 21) and after (April 22-June 13) the policy restricting staff movement was implemented. We constructed a network diagram visualizing connectivity between nursing homes in Ontario and calculated the number of homes that had a connection with another nursing home and the average number of connections per home in each period. We calculated the relative difference in these mobility metrics between the 2 time periods and compared within-home changes using McNemar test and the Wilcoxon rank-sum test.
RESULTS: In the period preceding restrictions, 266 (42.7%) nursing homes had a connection with at least 1 other home, compared with 79 (12.7%) homes during the period after restrictions, a drop of 70.3% (P < .001). Including all homes, the average number of connections in the before period was 3.90 compared to 0.77 in the after period, a drop of 80.3% (P < .001). In both periods, mobility between nursing homes was higher in homes located in larger communities, those with higher bed counts, and those part of a large chain.
CONCLUSIONS AND IMPLICATIONS: Mobility between nursing homes in Ontario fell sharply after an emergency order by the Ontario government limiting long-term care staff to a single home, though some mobility persisted. Reducing this residual mobility should be a focus of efforts to reduce risk within the long-term care sector during the COVID-19 pandemic.
We conducted environmental sampling at long-term care facilities to determine the extent of surface contamination with SARS-CoV-2 virus. Medical equipment used throughout the facility was determined to be contaminated.
The aim of this study is to identify demographic, clinical and medical care factors associated with mortality in three nursing homes.
METHODS:
Two nursing homes were hospital-dependent, had connections with infection prevention and control departments, and had permanent physicians. Third nursing home had no direct connection with general hospital, no infection control practitioner, and no permanent physician. The main outcome was death.
RESULTS:
During first 3 months of the outbreak, 224/375 (59.7%) residents were classified "COVID-19 cases" and 57/375 (15.2%) died. Hospital dependent nursing homes had lower COVID-19 case fatality rates in comparison to non-hospital dependent nursing home (15 [6.6%] vs 38 [25.8%], OR 0.20 [0.11-0.38], p = 0.001). During first 3 weeks of the outbreak, mortality in COVID-19 patients decreased if they had daily clinical examination (aOR: 0.09 [0.03-0.35], p = 0.01), 3 vital signs measurements per day (OR: 0.06 [0.01-0.30], p = 0.001) and prophylactic anticoagulation (OR: 0 [0.00-0.24], p = 0.001).
CONCLUSIONS:
This study suggests that high mortality rates in some nursing homes during COVID-19 outbreak might be favoured by a lack of medical care management. Increasing human and material resources, encouraging presence of nursing home physicians and establishing connection with general hospitals should be consider to deal with present and future health disasters in nursing homes.
