Estimated numbers of homeless and homeless mentally ill people in north east Westminster by using capture-recapture analysis

Abstract

Capture-recapture techniques can overcome problems of ascertainment in estimating populations of homeless and homeless mentally ill people. Prevalences of mental illness derived from surveys that do not correct for ascertainment are likely to be falsely inflated while at the same time underestimating the total size of the homeless mentally ill population. Population estimates derived from capture-recapture techniques may usefully provide a good basis for including homeless populations in capitation calculations for allocating funds within health services.

Does capture‐recapture analysis provide more reliable estimates of the incidence and prevalence of leg ulcers in the community?

“…[6][7][8][9][10][11] The simplest case involves two captures or lists, which must be assumed independent. If n 1 individuals from a given population appear on the first list, n 2 on the second list and n 12 appear on both lists, then mathematical considerations lead to an estimate of the total population of N=(n 1 n 2 )/n 12 -the so-called Petersen estimator.…”

“…The method is called capture-recapture analysis, and is derived from animal abundance studies in which animals are captured, tagged, released, then recaptured. 5 The method is increasingly Article applied to studies of human populations, [6][7][8][9][10][11] although there is no evidence that this method of analysis has been used in the f ield of leg ulcer research. In order to obtain estimates of the number of leg ulcer cases in a New Zealand population, the Auckland Leg Ulcer CrossSectional Study was conducted.…”

Problem drug use prevalence estimation revisited: heterogeneity in capture–recapture and the role of external evidence

“…In our case study, results were more sensitive to incorporation of a variable representing instability of housing (a marker of chaotic life‐style). Similarly, Fisher and colleagues 43 showed that mental health problems were an important factor when estimating prevalence of homelessness. It is important, therefore, to ensure that data sources collect rich information regarding characteristics that might influence ‘catchability’, to aid future prevalence estimation.…”

The Need for a Global Health Disaster Network

“…More powerful estimations of the morbidity and the number of homeless j people should be available using epidemiological tech-j niques such as capture-recapture. 5 " 6 Monitoring data on j morbidity and other problems needs to flow up the system through the telecommunications infrastructure.…”