从未充分报告的年龄依赖性强制通报数据库中估计传染病的流行情况。

Q1 Mathematics
Marcos Amaku, Marcelo Nascimento Burattini, Eleazar Chaib, Francisco Antonio Bezerra Coutinho, David Greenhalgh, Luis Fernandez Lopez, Eduardo Massad
{"title":"从未充分报告的年龄依赖性强制通报数据库中估计传染病的流行情况。","authors":"Marcos Amaku,&nbsp;Marcelo Nascimento Burattini,&nbsp;Eleazar Chaib,&nbsp;Francisco Antonio Bezerra Coutinho,&nbsp;David Greenhalgh,&nbsp;Luis Fernandez Lopez,&nbsp;Eduardo Massad","doi":"10.1186/s12976-017-0069-2","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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; a prevalence of non-notified cases that varied between 1,433,638 and 1,446,771; and a total prevalence of infections that varied between 1,597,540 and 1,616,153 cases.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":51195,"journal":{"name":"Theoretical Biology and Medical Modelling","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s12976-017-0069-2","citationCount":"7","resultStr":"{\"title\":\"Estimating the prevalence of infectious diseases from under-reported age-dependent compulsorily notification databases.\",\"authors\":\"Marcos Amaku,&nbsp;Marcelo Nascimento Burattini,&nbsp;Eleazar Chaib,&nbsp;Francisco Antonio Bezerra Coutinho,&nbsp;David Greenhalgh,&nbsp;Luis Fernandez Lopez,&nbsp;Eduardo Massad\",\"doi\":\"10.1186/s12976-017-0069-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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; a prevalence of non-notified cases that varied between 1,433,638 and 1,446,771; and a total prevalence of infections that varied between 1,597,540 and 1,616,153 cases.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":51195,\"journal\":{\"name\":\"Theoretical Biology and Medical Modelling\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/s12976-017-0069-2\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Theoretical Biology and Medical Modelling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s12976-017-0069-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theoretical Biology and Medical Modelling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s12976-017-0069-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 7

摘要

背景:国家或地方法律、规范或条例(有时在某些国家)要求医疗提供者向公共卫生当局报告应通报的疾病。然而,报告几乎总是不完整的。这是由多种原因造成的,从未识别患者到导致疾病通报系统最终正式登记的技术或行政步骤失败。报告的比例从9%到99%不等,与所报告的疾病密切相关。方法:在本文中,我们提出了一种近似估计传染病的全部流行率(以及与传播强度相关的任何其他变量或参数)的方法。该模型假设不完全通知发病率,并允许估计未通知的感染人数,并以巴西的丙型肝炎病例为例。该方法的优点是可以通过与经验结果的比较来进行迭代修正。结果:该模型在巴西丙型肝炎病例中的应用导致报告病例的患病率在163,902例和169,382例之间变化;未通报病例的患病率在1,433,638和1,446,771之间变化;感染的总流行率在1,597,540到1,616,153例之间变化。结论:我们的结论是,所提出的模型可用于估计传染病流行状态的实际规模,特别是对于那些通报病例数量只是冰山一角的国家。此外,该方法还可适用于其他情况,例如众所周知的未被报告的犯罪事件(例如强奸)等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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

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

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; a prevalence of non-notified cases that varied between 1,433,638 and 1,446,771; and 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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信