A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences
Main Author: | |
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Publication Date: | 2020 |
Other Authors: | , , , , , , |
Format: | Other |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10362/98694 |
Summary: | 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. |
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A review of capture-recapture methods and its possibilities in ophthalmology and vision sciencesCapture-recaptureOphthalmologyOptometryPrevalenceVision impairmentEpidemiologyOphthalmologySDG 3 - Good Health and Well-beingEpidemiological 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.Escola Nacional de Saúde Pública (ENSP)Comprehensive Health Research Centre (CHRC) - Pólo ENSPCentro de Investigação em Saúde Pública (CISP/PHRC)RUNRamos, Pedro LimaSousa, InêsSantana, RuiMorgan, William H.Gordon, KeithCrewe, JulieRocha-Sousa, AmândioMacedo, Antonio Filipe2020-06-02T01:06:53Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/otherapplication/pdfhttp://hdl.handle.net/10362/98694eng0928-6586PURE: 18401073https://doi.org/10.1080/09286586.2020.1749286info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:45:46Zoai:run.unl.pt:10362/98694Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:17:10.266535Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences |
title |
A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences |
spellingShingle |
A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences Ramos, Pedro Lima Capture-recapture Ophthalmology Optometry Prevalence Vision impairment Epidemiology Ophthalmology SDG 3 - Good Health and Well-being |
title_short |
A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences |
title_full |
A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences |
title_fullStr |
A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences |
title_full_unstemmed |
A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences |
title_sort |
A review of capture-recapture methods and its possibilities in ophthalmology and vision sciences |
author |
Ramos, Pedro Lima |
author_facet |
Ramos, Pedro Lima Sousa, Inês Santana, Rui Morgan, William H. Gordon, Keith Crewe, Julie Rocha-Sousa, Amândio Macedo, Antonio Filipe |
author_role |
author |
author2 |
Sousa, Inês Santana, Rui Morgan, William H. Gordon, Keith Crewe, Julie Rocha-Sousa, Amândio Macedo, Antonio Filipe |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Escola Nacional de Saúde Pública (ENSP) Comprehensive Health Research Centre (CHRC) - Pólo ENSP Centro de Investigação em Saúde Pública (CISP/PHRC) RUN |
dc.contributor.author.fl_str_mv |
Ramos, Pedro Lima Sousa, Inês Santana, Rui Morgan, William H. Gordon, Keith Crewe, Julie Rocha-Sousa, Amândio Macedo, Antonio Filipe |
dc.subject.por.fl_str_mv |
Capture-recapture Ophthalmology Optometry Prevalence Vision impairment Epidemiology Ophthalmology SDG 3 - Good Health and Well-being |
topic |
Capture-recapture Ophthalmology Optometry Prevalence Vision impairment Epidemiology Ophthalmology SDG 3 - Good Health and Well-being |
description |
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. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-06-02T01:06:53Z 2020 2020-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/other |
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other |
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publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/98694 |
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http://hdl.handle.net/10362/98694 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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0928-6586 PURE: 18401073 https://doi.org/10.1080/09286586.2020.1749286 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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