COVID-19 Cases Among Facility-Staff by Neighbourhood of Residence and Social and Structural Determinants: An Observational Study (Preprint)

2021 ◽  
Author(s):  
Huiting Ma ◽  
Kristy C.Y. Yiu ◽  
Stefan D. Baral ◽  
Christine Fahim ◽  
Gary Moloney ◽  
...  
Keyword(s):  
Observational Study ◽  
Census Data ◽  
Structural Determinants ◽  
Term Care ◽  
Lorenz Curves ◽  
Gini Coefficients ◽  
Greater Toronto Area ◽  
Social Structural ◽  
Neighbourhood Level ◽  
Facility Staff

BACKGROUND Disproportionate risks of COVID-19 in congregate settings including long-term care homes, retirement homes, and shelters both affect and are affected by SARS-CoV-2 infections among facility-staff. In cities across Canada, there has been a consistent trend of geographic clustering of COVID-19 cases. However, there remain limited data on how COVID-19 among facility-staff reflect urban neighbourhood disparities, particularly stratified by the social and structural determinants of community-level transmission. OBJECTIVE To compare the concentration of cumulative cases by geography and social/structural determinants across three mutually exclusive subgroups in the Greater Toronto Area (population 7.1 million): community, facility-staff, and healthcare workers (HCW) in other settings. METHODS We conducted a retrospective, observational study using surveillance data on laboratory-confirmed COVID-19 cases (January 23 to December 13, 2020; prior to vaccination roll-out). We derived neighbourhood-level social/structural determinants from census data, and generated Lorenz curves and Gini coefficients to visualize and quantify inequalities in cases. RESULTS The hardest-hit neighbourhoods (comprising 20% of the population) accounted for 53.4% of community cases, 48.6% of facility-staff cases, and 42.3% of other HCW cases. Compared with other HCW, cases in facility-staff more closely reflected the distribution of community cases. Cases in facility-staff reflected greater social and structural inequalities (larger Gini coefficients) than other HCW across all determinants. Facility-staff cases were also more likely than community cases to be concentrated in lower income neighbourhoods (Gini 0.24[0.15-0.38] vs 0.14[0.08-0.21] with lower household density (Gini 0.23[0.17-0.29] vs 0.17[0.12-0.22]) and with a greater proportion working in other essential services (Gini 0.29 [0.21-0.40], 0.22[0.17-0.28]). CONCLUSIONS COVID-19 cases among facility-staff largely reflects neighbourhood-level heterogeneity and disparities; even more so than cases in other HCW. Findings signal the importance of interventions prioritized and tailored to home geographies of facility-staff in addition to workplace measures, including prioritization and reach of vaccination at home (neighbourhood-level) and at work.

scholarly journals Increasing concentration of COVID-19 by socioeconomic determinants and geography in Toronto, Canada: an observational study

2021 ◽  
Author(s):  
Sharmistha Mishra ◽  
Huiting Ma ◽  
Gary Moloney ◽  
Kristy CY Yiu ◽  
Dariya Darvin ◽  
...  
Keyword(s):  
Observational Study ◽  
Gini Coefficient ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Occupational Exposures ◽  
Individual Case ◽  
Population Based ◽  
Term Care ◽  
Lorenz Curves ◽  
Over Time

Background: Inequities in the burden of COVID-19 observed across Canada suggest heterogeneity within community transmission. Objectives: To quantify the magnitude of heterogeneity in the wider community (outside of long-term care homes) in Toronto, Canada and assess how the magnitude in concentration evolved over time (January 21 to November 21, 2020). Design: Retrospective, population-based observational study using surveillance data from Ontario's Case and Contact Management system. Setting: Toronto, Canada. Participants: Laboratory-confirmed cases of COVID-19 (N=33,992). Measurements: We generated epidemic curves by SDOH and crude Lorenz curves by neighbourhoods to visualize inequities in the distribution of COVID-19 cases by social determinants of health (SDOH) and estimated the crude Gini coefficient. We examined the correlation between SDOH using Pearson correlation coefficients. Results: The Gini coefficient of cumulative cases by population size was 0.41 (95% CI: 0.36-0.47) and were estimated for: household income (0.20, 95%CI: 0.14-0.28); visible minority (0.21, 95%CI: 0.16-0.28); recent immigration (0.12, 95%CI: 0.09-0.16); suitable housing (0.21, 95%CI: 0.14-0.30); multi-generational households (0.19, 95%CI: 0.15-0.23); and essential workers (0.28, 95% CI: 0.23-0.34). Most SDOH were highly correlated. Locally acquired cases were concentrated in higher income neighbourhoods in the early phase of the epidemic, and then concentrated in lower income neighbourhoods. Mirroring the trajectory of epidemic curves by income, the Lorenz curve shifted over time from below to above the line of equality with a similar pattern across SDOH. Limitations: Study relied on area-based measures of the SDOH and individual case counts of COVID-19. We cannot infer concentration of cases by specific occupational exposures given limitation to broad occupational categories. Conclusion: COVID-19 is increasingly concentrated by SDOH given socioeconomic inequities and structural racism. Primary Funding Source: Canadian Institutes of Health Research.

scholarly journals What factors influence older people’s intention to enrol in nursing homes? A cross-sectional observational study in Shanghai, China

BMJ Open ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. e021741 ◽  
Author(s):  
Mengyun Luo ◽  
Yajiong Xue ◽  
Shunxing Zhang ◽  
Yuanyuan Dong ◽  
Dandan Mo ◽  
...  
Keyword(s):  
Nursing Homes ◽  
Observational Study ◽  
Rural Areas ◽  
Structural Equation Modelling ◽  
Structural Equation ◽  
Value Added ◽  
Subjective Norm ◽  
Cross Sectional ◽  
Term Care ◽  
Equation Modelling

ObjectivesGiven the increasing need of long-term care and the low occupancy rate of nursing homes in Shanghai, this study attempts to explore what factors influence older people’s intention to enrol in nursing homes.DesignA cross-sectional observational study based on the theory of reasoned action was conducted. Survey data were collected from subjects during face-to-face interviews. Structural equation modelling was employed for data analysis.SettingThis study was conducted in six community health service centres in Shanghai, China. Two service centres were selected in urban, suburban and rural areas, respectively.ParticipantsA total of 641 Shanghai residents aged over 60 were surveyed.ResultsStructural equation modelling analysis showed that the research model fits the data well (χ2/df=2.948, Comparative Fit Index=0.972 and root mean squared error of approximation =0.055). Attitude (β=0.41, p<0.01), subjective norm (β=0.28, p<0.01) and value-added service (β=0.16, p<0.01) were directly associated with enrolment intention, explaining 32% of variance in intention. Attitude was significantly influenced by loneliness (β=−0.08, p<0.05), self-efficacy (β=0.32, p<0.01) and stigma (β=−0.24, p<0.01), while subjective norm was significantly influenced by life satisfaction (β=−0.15, p<0.01) and stigma (β=−0.43, p<0.01).ConclusionsThis study advances knowledge regarding the influencing factors of older people’s intention to enrol in nursing homes. It suggests that Chinese older persons’ perceived stigma has the strongest indirect effect on their intention to enrol in nursing homes. This is unique to the Chinese context and has practical implications for eldercare in China and other Asian countries with similar sociocultural contexts.

Long-term care placement: The transitional support needs and preferences of spousal dementia caregivers

Dementia ◽  
2021 ◽  
pp. 147130122110564
Author(s):  
Deborah Brooks ◽  
Elizabeth Beattie ◽  
Elaine Fielding ◽  
Katy Wyles ◽  
Helen Edwards
Keyword(s):  
Long Term Care ◽  
Intervention Development ◽  
Care Facility ◽  
Spousal Caregivers ◽  
Support Needs ◽  
Structured Interviews ◽  
Term Care ◽  
Long Term Care Facility ◽  
Facility Staff

Background and objectives Many spousal caregivers experience stress, depression, loneliness, guilt and grief when placing a partner with dementia into long-term care. However, there is little research about their transitional support experiences, needs and preferences. This study aimed to gain a deeper understanding of these issues from spousal caregiver and long-term care facility staff perspectives, to inform subsequent support and intervention development. Research design and methods Semi-structured interviews and small group discussions were held separately with spousal caregivers ( n = 9) and care facility staff ( n = 11). Criterion and variation sampling aimed to ensure a range of experiences and perspectives. The ‘Framework’ approach was utilised for data analysis. Interpretation was with respect to underpinning models of stress-grief process in dementia caregiving. Findings A range of informational, psychoeducational and psychosocial supports were identified to help spousal caregivers cope better with the stressors and losses experienced throughout the transition from home to long-term care. Improved education about disease progression, information relating to long-term care provision, peer support and dementia-specific grief counselling were deemed important. Opportunities for better support within care facilities were also identified. Support should be tailored to individual needs and preferences. Discussion and implications The findings suggest a supportive care framework be developed, encompassing the trajectory from assessment for and admission into long-term care to end-of-life and post-bereavement support. Spousal caregivers should have their support needs assessed by trained health or social care professionals and be offered a range of support options as appropriate.

Evaluation of extent and amount of heterogeneous variance for milk yield in Uruguayan Holsteins

2001 ◽  
Vol 72 (2) ◽  
pp. 259-268 ◽  
Author(s):  
J. I. Urioste ◽  
D. Gianola ◽  
R. Rekaya ◽  
W. F. Fikse ◽  
K. A. Weigel
Keyword(s):  
Milk Yield ◽  
Phenotypic Variance ◽  
Simple Method ◽  
Factors Affecting ◽  
Lorenz Curves ◽  
Gini Coefficients ◽  
Adjustment Procedure ◽  
Contemporary Group ◽  
Lactation Length ◽  
Log Linear

AbstractThe extent and amount of heterogeneous phenotypic variance for milk yield in the Uruguayan Holstein population were evaluated and a simple method of accounting for heterogeneity was developed. Lactation records (159 169) collected between 1989 and 1998 by two recording schemes were used to form 8955 herd-year-season-parity-lactation length contemporary groups. A log-linear model was used to identify factors affecting heterogeneity of phenotypic variance. The model included effects of production level, contemporary group size, recording scheme, herd, season of calving, parity number, calving year period and length of lactation and accounted for 50% of the variation in log variances. Estimates from this model were used in a Bayesian manner, to obtain posterior mean estimates of within-contemporary-group variances, which were then used to standardize records to a baseline variance. Effects of the adjustment were assessed by comparing coefficients of variation before and after correction, by correlation and regression between mean and standard deviations, and by using Gini coefficients and Lorenz curves. The adjustment procedure reduced heteroscedasticity primarily by decreasing the frequency of low-variance contemporary groups. Lorenz curves and Gini coefficients indicated that the largest impact of the standardization procedure was related to the size of the contemporary group. Some differences in the effect of the correction were found between recording schemes. The method for adjusting records is simple and easy to adapt to current genetic evaluation procedures.

scholarly journals Heterogeneity in testing, diagnosis and outcome in SARS-CoV-2 infection across outbreak settings in the Greater Toronto Area, Canada: an observational study

CMAJ Open ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. E627-E636
Author(s):  
Linwei Wang ◽  
Huiting Ma ◽  
Kristy C.Y. Yiu ◽  
Andrew Calzavara ◽  
David Landsman ◽  
...  
Keyword(s):  
Observational Study ◽  
Greater Toronto Area

Spatially varying relationships between immigration measures and property crime Types in Vancouver Census Tracts, 2016

2020 ◽  
Vol 60 (5) ◽  
pp. 1342-1367
Author(s):  
Martin A Andresen ◽  
Olivia K Ha
Keyword(s):  
Census Data ◽  
Local Level ◽  
Property Crime ◽  
Census Tracts ◽  
Estimated Parameters ◽  
Neighbourhood Level ◽  
Significant Spatial Variation ◽  
Crime Types ◽  
Spatially Varying ◽  
Crime Classification

Abstract We empirically test for spatial heterogeneity or local effects of multiple immigration measures on various property crime classification across Vancouver census tracts, 2016. Using spatially referenced property crime data and census data, we use geographically weighted regression to investigate the neighbourhood-level effects of immigration on crime. We find that estimated parameters vary across space, but these local immigration effects do not always vary significantly at the local level. Overall, significant spatial variation in the effects of immigration on property crime is present. These are important for policy and theory. The identification of varied spatial patterns of immigration effects on crime may help explain some of the inconsistent/disparate results found in neighbourhood-level studies on immigration and crime.

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