Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases

Detalhes bibliográficos
Autor(a) principal: Amaku, Marcos
Data de Publicação: 2017
Outros Autores: Burattini, Marcelo Nascimento [UNIFESP], Chaib, Eleazar, Bezerra Coutinho, Francisco Antonio, Greenhalgh, David, Lopez, Luis Fernandez, Massad, Eduardo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNIFESP
Texto Completo: https://repositorio.unifesp.br/handle/11600/54002
http://dx.doi.org/10.1186/s12976-017-0069-2
Resumo: Background: National or local laws, norms or regulations (sometimes and in some countries) require medical providers to report notifiable diseases to public health authorities. Reporting, however, is almost always incomplete. This is due to a variety of reasons, ranging from not recognizing the diseased to failures in the technical or administrative steps leading to the final official register in the disease notification system. The reported fraction varies from 9 to 99% and is strongly associated with the disease being reported. Methods: In this paper we propose a method to approximately estimate the full prevalence (and any other variable or parameter related to transmission intensity) of infectious diseases. The model assumes incomplete notification of incidence and allows the estimation of the non-notified number of infections and it is illustrated by the case of hepatitis C in Brazil. The method has the advantage that it can be corrected iteratively by comparing its findings with empirical results. Results: The application of the model for the case of hepatitis C in Brazil resulted in a prevalence of notified cases that varied between 163,902 and 169,382 cases
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spelling Amaku, MarcosBurattini, Marcelo Nascimento [UNIFESP]Chaib, EleazarBezerra Coutinho, Francisco AntonioGreenhalgh, DavidLopez, Luis FernandezMassad, Eduardo2020-07-02T18:52:19Z2020-07-02T18:52:19Z2017Theoretical Biology And Medical Modelling. London, v. 14, p. -, 2017.1742-4682https://repositorio.unifesp.br/handle/11600/54002http://dx.doi.org/10.1186/s12976-017-0069-2WOS000417868000001.pdf10.1186/s12976-017-0069-2WOS:000417868000001Background: National or local laws, norms or regulations (sometimes and in some countries) require medical providers to report notifiable diseases to public health authorities. Reporting, however, is almost always incomplete. This is due to a variety of reasons, ranging from not recognizing the diseased to failures in the technical or administrative steps leading to the final official register in the disease notification system. The reported fraction varies from 9 to 99% and is strongly associated with the disease being reported. Methods: In this paper we propose a method to approximately estimate the full prevalence (and any other variable or parameter related to transmission intensity) of infectious diseases. The model assumes incomplete notification of incidence and allows the estimation of the non-notified number of infections and it is illustrated by the case of hepatitis C in Brazil. The method has the advantage that it can be corrected iteratively by comparing its findings with empirical results. Results: The application of the model for the case of hepatitis C in Brazil resulted in a prevalence of notified cases that varied between 163,902 and 169,382 casesa prevalence of non-notified cases that varied between 1,433,638 and 1,446,771and a total prevalence of infections that varied between 1,597,540 and 1,616,153 cases. Conclusions: We conclude that the model proposed can be useful for estimation of the actual magnitude of endemic states of infectious diseases, particularly for those where the number of notified cases is only the tip of the iceberg. In addition, the method can be applied to other situations, such as the well-known underreported incidence of criminality (for example rape), among others.LIM01-HCFMUSPCNPqBrazilian Ministry of Health [TED 27/2015]FAPESPLeverhulme Trust from a Leverhulme Research Fellowship [RF-2015-88]British Council, Malaysia from the Dengue Tech Challenge [DTC 16022]Science Without Borders Program for a Special Visiting Fellowship (CNPq) [30098/2014-7]Univ Sao Paulo, Fac Med, Hosp Clin LIM01, Sao Paulo, SP, BrazilUniv Fed Sao Paulo, Hosp Sao Paulo, Escola Paulista Med, Sao Paulo, SP, BrazilUniv Strathclyde, Dept Math & Stat, Glasgow, Lanark, ScotlandFlorida Int Univ, Ctr Internet Augmented Res & Assessment, Miami, FL 33199 USALondon Sch Hyg & Trop Med, London, EnglandUniv Fed Sao Paulo, Hosp Sao Paulo, Escola Paulista Med, Sao Paulo, SP, BrazilCNPqBrazilian Ministry of Health [TED 27/2015]CNPq [30098/2014-7]Web of Science-engBiomed Central LtdTheoretical Biology And Medical ModellingHepatitis CMathematical modelsNotifications system incidencePrevalenceEstimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databasesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleLondon14info:eu-repo/semantics/openAccessreponame:Repositório Institucional da UNIFESPinstname:Universidade Federal de São Paulo (UNIFESP)instacron:UNIFESP11600/540022022-02-03 11:55:37.478metadata only accessoai:repositorio.unifesp.br:11600/54002Repositório InstitucionalPUBhttp://www.repositorio.unifesp.br/oai/requestopendoar:34652023-05-25T12:16:23.185215Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)false
dc.title.en.fl_str_mv Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases
title Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases
spellingShingle Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases
Amaku, Marcos
Hepatitis C
Mathematical models
Notifications system incidence
Prevalence
title_short Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases
title_full Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases
title_fullStr Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases
title_full_unstemmed Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases
title_sort Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases
author Amaku, Marcos
author_facet Amaku, Marcos
Burattini, Marcelo Nascimento [UNIFESP]
Chaib, Eleazar
Bezerra Coutinho, Francisco Antonio
Greenhalgh, David
Lopez, Luis Fernandez
Massad, Eduardo
author_role author
author2 Burattini, Marcelo Nascimento [UNIFESP]
Chaib, Eleazar
Bezerra Coutinho, Francisco Antonio
Greenhalgh, David
Lopez, Luis Fernandez
Massad, Eduardo
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Amaku, Marcos
Burattini, Marcelo Nascimento [UNIFESP]
Chaib, Eleazar
Bezerra Coutinho, Francisco Antonio
Greenhalgh, David
Lopez, Luis Fernandez
Massad, Eduardo
dc.subject.eng.fl_str_mv Hepatitis C
Mathematical models
Notifications system incidence
Prevalence
topic Hepatitis C
Mathematical models
Notifications system incidence
Prevalence
description Background: National or local laws, norms or regulations (sometimes and in some countries) require medical providers to report notifiable diseases to public health authorities. Reporting, however, is almost always incomplete. This is due to a variety of reasons, ranging from not recognizing the diseased to failures in the technical or administrative steps leading to the final official register in the disease notification system. The reported fraction varies from 9 to 99% and is strongly associated with the disease being reported. Methods: In this paper we propose a method to approximately estimate the full prevalence (and any other variable or parameter related to transmission intensity) of infectious diseases. The model assumes incomplete notification of incidence and allows the estimation of the non-notified number of infections and it is illustrated by the case of hepatitis C in Brazil. The method has the advantage that it can be corrected iteratively by comparing its findings with empirical results. Results: The application of the model for the case of hepatitis C in Brazil resulted in a prevalence of notified cases that varied between 163,902 and 169,382 cases
publishDate 2017
dc.date.issued.fl_str_mv 2017
dc.date.accessioned.fl_str_mv 2020-07-02T18:52:19Z
dc.date.available.fl_str_mv 2020-07-02T18:52:19Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.citation.fl_str_mv Theoretical Biology And Medical Modelling. London, v. 14, p. -, 2017.
dc.identifier.uri.fl_str_mv https://repositorio.unifesp.br/handle/11600/54002
http://dx.doi.org/10.1186/s12976-017-0069-2
dc.identifier.issn.none.fl_str_mv 1742-4682
dc.identifier.file.none.fl_str_mv WOS000417868000001.pdf
dc.identifier.doi.none.fl_str_mv 10.1186/s12976-017-0069-2
dc.identifier.wos.none.fl_str_mv WOS:000417868000001
identifier_str_mv Theoretical Biology And Medical Modelling. London, v. 14, p. -, 2017.
1742-4682
WOS000417868000001.pdf
10.1186/s12976-017-0069-2
WOS:000417868000001
url https://repositorio.unifesp.br/handle/11600/54002
http://dx.doi.org/10.1186/s12976-017-0069-2
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.none.fl_str_mv Theoretical Biology And Medical Modelling
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv -
dc.coverage.none.fl_str_mv London
dc.publisher.none.fl_str_mv Biomed Central Ltd
publisher.none.fl_str_mv Biomed Central Ltd
dc.source.none.fl_str_mv reponame:Repositório Institucional da UNIFESP
instname:Universidade Federal de São Paulo (UNIFESP)
instacron:UNIFESP
instname_str Universidade Federal de São Paulo (UNIFESP)
instacron_str UNIFESP
institution UNIFESP
reponame_str Repositório Institucional da UNIFESP
collection Repositório Institucional da UNIFESP
repository.name.fl_str_mv Repositório Institucional da UNIFESP - Universidade Federal de São Paulo (UNIFESP)
repository.mail.fl_str_mv
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