A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences

• Autor(a) principal: Ramos, Pedro Alexandre Fernandes Lima
• Data de Publicação: 2020
• Outros Autores: Sousa, Inês, Santana, Rui, Morgan, William H., Gordon, Keith, Crewe, Julie, Rocha-Sousa, Amandio, Macedo, António Filipe
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/1822/72735
• topic: Capture-recapture; Prevalence; Vision impairment; Ophthalmology; Optometry; Ciências Médicas::Medicina Clínica; Science & Technology

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.