A Review of Capture-recapture Methods and Its Possibilities in Ophthalmology and Vision Sciences

Abstract

Epidemiological information is expected to be used to develop key aspects of eye care such as to control and minimise the impact of diseases, to allocate resources, to monitor public health actions, to determine the best treatment options and to forecast the consequence of diseases in populations. Epidemiological studies are expected to provide information about the prevalence and/or incidence of eye diseases or conditions. To determine prevalence is necessary to perform a cross-sectional screening of the population at risk to ascertain the number of cases. The aim of this review is to describe and evaluate capture-recapture methods (or models) to ascertaining the number of individuals with a disease (e.g. diabetic retinopathy) or condition (e.g. vision impairment) in the population. The review covers the fundamental aspects of capture-recapture methods that would enable non-experts in epidemiology to use it in ophthalmic studies. The review provides information about theoretical aspects of the method with examples of studies in ophthalmology in which it has been used. We also provide a problem/solution approach for limitations arising from the lists obtained from registers or other reliable sources. We concluded that capture-recapture models can be considered reliable to estimate the total number of cases with eye conditions using incomplete information from registers. Accordingly, the method may be used to maintain updated epidemiological information about eye conditions helping to tackle the lack of surveillance information in many regions of the globe.

Cross-sectional study investigating the prevalence and causes of vision impairment in Northwest Portugal using capture–recapture

“…41 A review of the method with an intuitive link to a video ( https://www.youtube.com/watch?v=aiSKgIc_8vk ) is given in a review by Bird and King 42 and in our previous publication. 28 …”

“…41 A review of the method with an intuitive link to a video (https://www.youtube.com/ watch?v=aiSK-gIc_8vk) is given in a review by Bird and King 42 and in our previous publication. 28 After choosing the best possible model for our data we obtained an estimate of the size of the hidden population and consequently we estimate of the number of individuals with VI. The same procedure was used to compute category specific prevalence according to age and sex.…”

“…[25][26][27] For a detailed description on how to use CR methods we recommend reading our review about the method. 28 Due to the lack of information about the prevalence of VI in Portugal, we conducted a study with CR methods using data from different sources. The aim of this study was to estimate the prevalence and the main causes of VI in Portugal using CR methods.…”

A cross-sectional study investigating the prevalence and causes of vision impairment in Northwest Portugal using capture-recapture

“…The final estimate for E ( n 000 ) is given by the best model that should pass the Qui-square goodness of fit test and should be the one with the lowest value of AIC. [43] A review of the method with an intuitive link to a video (https://www.youtube.com/watch?v=aiSKgIc_8vk) is given in a review by Bird and King (2018)[44] and in our previous publication[30].…”

“…CR methods is a methodology that can overcome the problem of cases that are never captured by, for example, registers for the visual impaired [27][28][29]. For a detailed description on how to use CR methods we recommend reading our review about the method [30]. Due the lack of information about the prevalence of VI in Portugal, we conducted a study with CR methods using data from different sources.…”