Risk Stratification of Nursing Homes to Plan COVID-19 Responses: A Case Study of Victoria, Australia.
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ABSTRACT: Objective
Emergency management responses to coronavirus disease 2019 (COVID-19) in nursing homes lacked preparation and nuance; moving forward, responses must recognize nursing homes are not generic organizations or services, and individually appreciate each's unique nature, strengths, and limitations. The objective of this study was to describe an approach to stratifying nursing homes according to risk for COVID-19 outbreak.Methods
Population-based cross-sectional study of all accredited nursing homes in Victoria (n = 766), accommodating 48,824 permanent residents. We examined each home's facility structure, governance history, socio-economic status, proximity to high-risk industry, and proximity and size of local acute public hospital, stratified by location, size, and organizational structure.Results
Privately owned nursing homes tend to be larger and metropolitan-based, and publicly owned homes regionally based and smaller in size. The details reveal additional nuance, eg, privately owned metropolitan-based medium- to large-sized facilities tended to have more regulatory noncompliance, no board of governance, and fewer Chief Executive Officers with clinical background. In contrast, the smaller, publicly owned, remote facilities perform better on those same metrics.Conclusions
Nursing homes should not be regarded as generic entities, and there is significant underlying heterogeneity. Stratification of nursing homes according to risk level is a viable approach to informing more nuanced policy direction and resource allocation for emergency management responses.
SUBMITTER: Ibrahim JE
PROVIDER: S-EPMC8376849 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo determine nursing home characteristics associated with COVID-19 outbreak, outbreak size and mortality, during the second wave in Victoria, Australia.MethodPopulation-based cross-sectional study of all nursing homes in Victoria between 7 July and 13 November 2020.ResultsThere were one or more resident cases of COVID-19 in 9.7% of nursing homes (74/766). COVID-19 intrusion was more likely in larger metropolitan facilities, privately owned by large chains, with a past history of regulatory non-compliance, located close to high-risk industry. Larger outbreaks were associated with homes in metropolitan areas, accommodating 91 or more residents, with shared rooms, owned by private providers operating many (11 or more) facilities. The highest case-fatality rates were observed in homes owned by not-for-profit providers operating many facilities, located close to high-risk industry.ConclusionStratifying nursing homes according to characteristics associated with morbidity and mortality can inform risk management, prioritising emergency responses and optimising future nursing home operations.
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Project description:BackgroundThe air borne SARS-CoV-2 poses a high threat to the elderly and people with underlying diseases. COVID-19 spread quickly in South German nursing homes and for this reason called for preventive measures by the German government. The aim of this paper is to showcase the testing strategies implemented by the Public Health Department Reutlingen to control the spread of COVID-19 in local nursing homes and to report the results thereof.MethodsThis study reports COVID-19 outbreaks in nursing homes in Reutlingen County and how they were dealt with through extensive testing, contact tracing, isolation and hygiene inspections. The testing strategy consisted of three phases: In phase 1 only suspected cases, in phase 2 all staff and residents, and in phase 3 all suspected cases and their contacts were tested.ResultsNearly all residents (98%) and staff members (92%) of all nursing homes in Reutlingen County were tested for SARS-COV-2. 25 of 37 nursing homes had COVID-19 cases, 5 had 30-81 cases/home. 62% of the 395 nursing homes cases were residents, but less than half of them exhibited symptoms (41%). The cases uncovered in nursing homes represented 26% of all 1529 cases in Reutlingen County during the time of this study.ConclusionsMany COVID-19 cases were discovered through extensive testing, allowing for early interventions. The results shed light on the COVID-19 situation in nursing homes and allowed for individually designed preventive measures. The results also lead to a change in the German legislation. The outbreak management methods of the Public Health Department Reutlingen may also be applicable in other countries.
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Project description:BackgroundA cornerstone of Australia's ability to control COVID-19 has been effective border control with an extensive supervised quarantine programme. However, a rapid recrudescence of COVID-19 was observed in the state of Victoria in June, 2020. We aim to describe the genomic findings that located the source of this second wave and show the role of genomic epidemiology in the successful elimination of COVID-19 for a second time in Australia.MethodsIn this observational, genomic epidemiological study, we did genomic sequencing of all laboratory-confirmed cases of COVID-19 diagnosed in Victoria, Australia between Jan 25, 2020, and Jan 31, 2021. We did phylogenetic analyses, genomic cluster discovery, and integrated results with epidemiological data (detailed information on demographics, risk factors, and exposure) collected via interview by the Victorian Government Department of Health. Genomic transmission networks were used to group multiple genomic clusters when epidemiological and genomic data suggested they arose from a single importation event and diversified within Victoria. To identify transmission of emergent lineages between Victoria and other states or territories in Australia, all publicly available SARS-CoV-2 sequences uploaded before Feb 11, 2021, were obtained from the national sequence sharing programme AusTrakka, and epidemiological data were obtained from the submitting laboratories. We did phylodynamic analyses to estimate the growth rate, doubling time, and number of days from the first local infection to the collection of the first sequenced genome for the dominant local cluster, and compared our growth estimates to previously published estimates from a similar growth phase of lineage B.1.1.7 (also known as the Alpha variant) in the UK.FindingsBetween Jan 25, 2020, and Jan 31, 2021, there were 20 451 laboratory-confirmed cases of COVID-19 in Victoria, Australia, of which 15 431 were submitted for sequencing, and 11 711 met all quality control metrics and were included in our analysis. We identified 595 genomic clusters, with a median of five cases per cluster (IQR 2-11). Overall, samples from 11 503 (98·2%) of 11 711 cases clustered with another sample in Victoria, either within a genomic cluster or transmission network. Genomic analysis revealed that 10 426 cases, including 10 416 (98·4%) of 10 584 locally acquired cases, diagnosed during the second wave (between June and October, 2020) were derived from a single incursion from hotel quarantine, with the outbreak lineage (transmission network G, lineage D.2) rapidly detected in other Australian states and territories. Phylodynamic analyses indicated that the epidemic growth rate of the outbreak lineage in Victoria during the initial growth phase (samples collected between June 4 and July 9, 2020; 47·4 putative transmission events, per branch, per year [1/years; 95% credible interval 26·0-85·0]), was similar to that of other reported variants, such as B.1.1.7 in the UK (mean approximately 71·5 1/years). Strict interventions were implemented, and the outbreak lineage has not been detected in Australia since Oct 29, 2020. Subsequent cases represented independent international or interstate introductions, with limited local spread.InterpretationOur study highlights how rapid escalation of clonal outbreaks can occur from a single incursion. However, strict quarantine measures and decisive public health responses to emergent cases are effective, even with high epidemic growth rates. Real-time genomic surveillance can alter the way in which public health agencies view and respond to COVID-19 outbreaks.FundingThe Victorian Government, the National Health and Medical Research Council Australia, and the Medical Research Future Fund.
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Project description:ImportanceStaff absences and departures at nursing homes may put residents at risk and present operational challenges.ObjectiveTo quantify changes in nursing home facility staffing during and after a severe COVID-19 outbreak.Design setting and participantsIn this cohort study, daily staffing payroll data were used to construct weekly measures of facility staffing, absences, departures, and use of overtime and contract staff among US nursing homes experiencing a severe COVID-19 outbreak that started between June 14, 2020, and January 1, 2021. Facility outbreaks were identified using COVID-19 case data. An event-study design with facility and week fixed effects was used to investigate the association of severe outbreaks with staffing measures.ExposuresWeeks since the beginning of a severe COVID-19 outbreak (4 weeks prior to 16 weeks after).Main outcomes and measuresTotal weekly staffing hours, staff counts, staff absences, departures, new hires, overtime and contract staff hours measured for all nursing staff and separately by staff type (registered nurses, licensed practical nurses, certified nursing assistants), facility self-reported staff shortages, and resident deaths.ResultsOf the included 2967 nursing homes experiencing severe COVID-19 outbreaks, severe outbreaks were associated with a statistically significant drop in nursing staffing levels owing to elevated absences and departures. Four weeks after an outbreak's start, around when average new cases peaked, staffing hours were 2.6% (95% CI, 2.1%-3.2%) of the mean below preoutbreak levels, despite facilities taking substantial measures to bolster staffing through increased hiring and the use of contract staff and overtime. Because these measures were mostly temporary, staffing declined further in later weeks; 16 weeks after an outbreak's start, staffing hours were 5.5% (95% CI, 4.5%-6.5%) of the mean below preoutbreak levels. Staffing declines were greatest among certified nursing assistants, primarily owing to smaller increases in new hires of this staff type compared with licensed practical nurses and registered nurses.Conclusions and relevanceIn this cohort study of nursing homes experiencing severe COVID-19 outbreaks, facilities experienced considerable staffing challenges during and after outbreaks. These results suggest the need for policy action to ensure facilities' abilities to maintain adequate staffing levels during and after infectious disease outbreaks.
| S-EPMC9308062 | biostudies-literature
Project description:BackgroundDespite widespread adoption of surveillance testing for coronavirus disease 2019 (Covid-19) among staff members in skilled nursing facilities, evidence is limited regarding its relationship with outcomes among facility residents.MethodsUsing data obtained from 2020 to 2022, we performed a retrospective cohort study of testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among staff members in 13,424 skilled nursing facilities during three pandemic periods: before vaccine approval, before the B.1.1.529 (omicron) variant wave, and during the omicron wave. We assessed staff testing volumes during weeks without Covid-19 cases relative to other skilled nursing facilities in the same county, along with Covid-19 cases and deaths among residents during potential outbreaks (defined as the occurrence of a case after 2 weeks with no cases). We reported adjusted differences in outcomes between high-testing facilities (90th percentile of test volume) and low-testing facilities (10th percentile). The two primary outcomes were the weekly cumulative number of Covid-19 cases and related deaths among residents during potential outbreaks.ResultsDuring the overall study period, 519.7 cases of Covid-19 per 100 potential outbreaks were reported among residents of high-testing facilities as compared with 591.2 cases among residents of low-testing facilities (adjusted difference, -71.5; 95% confidence interval [CI], -91.3 to -51.6). During the same period, 42.7 deaths per 100 potential outbreaks occurred in high-testing facilities as compared with 49.8 deaths in low-testing facilities (adjusted difference, -7.1; 95% CI, -11.0 to -3.2). Before vaccine availability, high- and low-testing facilities had 759.9 cases and 1060.2 cases, respectively, per 100 potential outbreaks (adjusted difference, -300.3; 95% CI, -377.1 to -223.5), along with 125.2 and 166.8 deaths (adjusted difference, -41.6; 95% CI, -57.8 to -25.5). Before the omicron wave, the numbers of cases and deaths were similar in high- and low-testing facilities; during the omicron wave, high-testing facilities had fewer cases among residents, but deaths were similar in the two groups.ConclusionsGreater surveillance testing of staff members at skilled nursing facilities was associated with clinically meaningful reductions in Covid-19 cases and deaths among residents, particularly before vaccine availability.
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Project description:In this multi-centric cross-sectional survey conducted in nursing homes of the French Alps, from 1 March to 31 May 2020, we analyze the relationship between the occurrence of an outbreak of COVID 19 among residents and staff members. Out of 225 eligible nursing homes, 74 (32.8%) completed the survey. Among 5891 residents, the incidence of confirmed or probable COVID-19 was 8.2% (95CI, 7.5% to 8.9%), and 22 (29.7%) facilities had an outbreak with at least 3 cases. Among the 4652 staff members, the incidence of confirmed or probable COVID-19 was 6.3% (95CI, 5.6% to 7.1%). A strong positive correlation existed between residents and staff members for both numbers of cases (r2 = 0.77, p < 0.001) and the incidence (r2 = 0.76, p < 0.001). In univariate analyses, cases among the staff were the only factor associated with the occurrence of an outbreak among residents (OR = 11.2 (95CI, 2.25 to 53.6)). In bivariate analysis, this relationship was not influenced by any nursing home characteristics, nor the action they implemented to mitigate the COVID-19 crisis. Staff members were, therefore, likely to be a source of contamination and spread of COVID-19 among nursing home residents during the first wave of the pandemic.
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Project description:During 2020, Victoria was the Australian state hardest hit by COVID-19, but was successful in controlling its second wave through aggressive policy interventions. We calibrated a detailed compartmental model of Victoria's second wave to multiple geographically-structured epidemic time-series indicators. We achieved a good fit overall and for individual health services through a combination of time-varying processes, including case detection, population mobility, school closures, physical distancing and face covering usage. Estimates of the risk of death in those aged ≥75 and of hospitalisation were higher than international estimates, reflecting concentration of cases in high-risk settings. We estimated significant effects for each of the calibrated time-varying processes, with estimates for the individual-level effect of physical distancing of 37.4% (95%CrI 7.2-56.4%) and of face coverings of 45.9% (95%CrI 32.9-55.6%). That the multi-faceted interventions led to the dramatic reversal in the epidemic trajectory is supported by our results, with face coverings likely particularly important.
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