Estimating Homelessness in the Netherlands Using a Capture-Recapture Approach

Coumans, A.M.; Cruyff, Maarten; Heijden, P.G.M. van der; Wolf, Judith; Schmeets, Hans

doi:10.1007/s11205-015-1171-7

Cited by 29 publications

(29 citation statements)

References 41 publications

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“…These factors might account for the improvements in the social exclusion indicators among the participants in the present study. However, despite these positive results, between 2009 and 2012 the estimated size of the homeless population in the Netherlands increased, which was largely due to the financial crisis (Coumans et al 2015 ). It is estimated that in 2015 a total of 31,000 people were homeless in the Netherlands (Statistics Netherlands 2016 ).…”

Section: Discussionmentioning

confidence: 99%

Changes in Social Exclusion Indicators and Psychological Distress Among Homeless People Over a 2.5-Year Period

et al. 2016

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Although homelessness is inherently associated with social exclusion, homeless individuals are rarely included in conventional studies on social exclusion. Use of longitudinal survey data from a cohort study on homeless people in four major Dutch cities (n = 378) allowed to examine: changes in indicators of social exclusion among homeless people over a 2.5-year period after reporting to the social relief system, and associations between changes in indicators of social exclusion and changes in psychological distress. Multinomial logistic regression analysis was applied to investigate the associations between changes in indicators of social exclusion and changes in psychological distress. Improvements were found in various indicators of social exclusion, whereas financial debts showed no significant improvement. Changes in unmet care needs, health insurance, social support from family and relatedness to others were related to changes in psychological distress. This study demonstrated improvements in various indicators of social exclusion among homeless people over a period of 2.5 years, and sheds light on the concept of social exclusion in relation to homelessness.

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Section: Discussionmentioning

confidence: 99%

Changes in Social Exclusion Indicators and Psychological Distress Among Homeless People Over a 2.5-Year Period

et al. 2016

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“…In the Netherlands (pop. 17.1 million), over the last few years, the homeless population has grown from an estimated 17,800 in 2009 up to 39,300 in 2018 (Dutch Bureau of Statistics), and is defined by living conditions: people who sleep in a homeless shelter, at a family member's or friend's house without the possibility of staying there for a long time, or in the streets (Coumans, Cruyff, Van der Heijden, Wolf, & Schmeets, 2017). Compared to the general population, homeless people suffer more often from addictions, physical and mental health problems and intellectual disability, and the all-cause standardised mortality ratio is nearly twelve times higher for females and nearly eight times for males (Aldridge et al, 2018;Fazel, Geddes, & Kushel, 2014;Van Straaten et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Self-perceived health problems and unmet care needs of homeless people in the Netherlands : the need for pro-active integrated care

Verheul¹,

Laere²,

Muijsenbergh³

et al. 2020

JSI

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“…() and International Working Group for Disease Monitoring and Forecasting () for details. However, it is important to note that the parameters that are associated with the log‐linear models are not well interpretable for practitioners (Coumans et al ., ). Otis et al .…”

Section: Introductionmentioning

confidence: 99%

“…Interested readers are referred to Fienberg (1972a,b), Bishop et al (1975) and International Working Group for Disease Monitoring and Forecasting (1995) for details. However, it is important to note that the parameters that are associated with the log-linear models are not well interpretable for practitioners (Coumans et al, 2017). Otis et al (1978) proposed an alternative model, which is popularly known as M tb , which accounts for the list dependence with respect to behavioural response variation.…”

Section: Introductionmentioning

confidence: 99%

On the Estimation of Population Size from a Dependent Triple-Record System

Chatterjee

Bhuyan

2019

Journal of the Royal Statistical Society Series A: Statistics in Society

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Summary Population size estimation based on a capture–recapture experiment under a triple‐record system is an interesting problem in various fields including epidemiology and population studies. In many real life scenarios, there is inherent dependence between capture and recapture attempts. We propose a novel model that successfully incorporates the possible dependence and the associated parameters have nice interpretations. We provide estimation methodology for the population size and the associated model parameters based on the maximum likelihood method. The model proposed is applied to analyse real data sets from public health and census coverage evaluation studies. The performance of the estimate proposed is evaluated through extensive simulation study and the results are compared with existing competitors. The results exhibit superiority of the model over the existing competitors both in real data analysis and in a simulation study.

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Estimating Homelessness in the Netherlands Using a Capture-Recapture Approach

Cited by 29 publications

References 41 publications

Changes in Social Exclusion Indicators and Psychological Distress Among Homeless People Over a 2.5-Year Period

Changes in Social Exclusion Indicators and Psychological Distress Among Homeless People Over a 2.5-Year Period

Self-perceived health problems and unmet care needs of homeless people in the Netherlands : the need for pro-active integrated care

On the Estimation of Population Size from a Dependent Triple-Record System

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