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Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data
BACKGROUND: The International Health Regulations outline core requirements to ensure the detection of public health threats of international concern. Assessing the capacity of surveillance systems to detect these threats is crucial for evaluating a country’s ability to meet these requirements. METHO...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5240927/ https://www.ncbi.nlm.nih.gov/pubmed/28095468 http://dx.doi.org/10.1371/journal.pmed.1002218 |
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author | Nikolay, Birgit Salje, Henrik Sturm-Ramirez, Katharine Azziz-Baumgartner, Eduardo Homaira, Nusrat Ahmed, Makhdum Iuliano, A. Danielle Paul, Repon C. Rahman, Mahmudur Hossain, M. Jahangir Luby, Stephen P. Cauchemez, Simon Gurley, Emily S. |
author_facet | Nikolay, Birgit Salje, Henrik Sturm-Ramirez, Katharine Azziz-Baumgartner, Eduardo Homaira, Nusrat Ahmed, Makhdum Iuliano, A. Danielle Paul, Repon C. Rahman, Mahmudur Hossain, M. Jahangir Luby, Stephen P. Cauchemez, Simon Gurley, Emily S. |
author_sort | Nikolay, Birgit |
collection | PubMed |
description | BACKGROUND: The International Health Regulations outline core requirements to ensure the detection of public health threats of international concern. Assessing the capacity of surveillance systems to detect these threats is crucial for evaluating a country’s ability to meet these requirements. METHODS AND FINDINGS: We propose a framework to evaluate the sensitivity and representativeness of hospital-based surveillance and apply it to severe neurological infectious diseases and fatal respiratory infectious diseases in Bangladesh. We identified cases in selected communities within surveillance hospital catchment areas using key informant and house-to-house surveys and ascertained where cases had sought care. We estimated the probability of surveillance detecting different sized outbreaks by distance from the surveillance hospital and compared characteristics of cases identified in the community and cases attending surveillance hospitals. We estimated that surveillance detected 26% (95% CI 18%–33%) of severe neurological disease cases and 18% (95% CI 16%–21%) of fatal respiratory disease cases residing at 10 km distance from a surveillance hospital. Detection probabilities decreased markedly with distance. The probability of detecting small outbreaks (three cases) dropped below 50% at distances greater than 26 km for severe neurological disease and at distances greater than 7 km for fatal respiratory disease. Characteristics of cases attending surveillance hospitals were largely representative of all cases; however, neurological disease cases aged <5 y or from the lowest socioeconomic group and fatal respiratory disease cases aged ≥60 y were underrepresented. Our estimates of outbreak detection rely on suspected cases that attend a surveillance hospital receiving laboratory confirmation of disease and being reported to the surveillance system. The extent to which this occurs will depend on disease characteristics (e.g., severity and symptom specificity) and surveillance resources. CONCLUSION: We present a new approach to evaluating the sensitivity and representativeness of hospital-based surveillance, making it possible to predict its ability to detect emerging threats. |
format | Online Article Text |
id | pubmed-5240927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-52409272017-02-06 Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data Nikolay, Birgit Salje, Henrik Sturm-Ramirez, Katharine Azziz-Baumgartner, Eduardo Homaira, Nusrat Ahmed, Makhdum Iuliano, A. Danielle Paul, Repon C. Rahman, Mahmudur Hossain, M. Jahangir Luby, Stephen P. Cauchemez, Simon Gurley, Emily S. PLoS Med Research Article BACKGROUND: The International Health Regulations outline core requirements to ensure the detection of public health threats of international concern. Assessing the capacity of surveillance systems to detect these threats is crucial for evaluating a country’s ability to meet these requirements. METHODS AND FINDINGS: We propose a framework to evaluate the sensitivity and representativeness of hospital-based surveillance and apply it to severe neurological infectious diseases and fatal respiratory infectious diseases in Bangladesh. We identified cases in selected communities within surveillance hospital catchment areas using key informant and house-to-house surveys and ascertained where cases had sought care. We estimated the probability of surveillance detecting different sized outbreaks by distance from the surveillance hospital and compared characteristics of cases identified in the community and cases attending surveillance hospitals. We estimated that surveillance detected 26% (95% CI 18%–33%) of severe neurological disease cases and 18% (95% CI 16%–21%) of fatal respiratory disease cases residing at 10 km distance from a surveillance hospital. Detection probabilities decreased markedly with distance. The probability of detecting small outbreaks (three cases) dropped below 50% at distances greater than 26 km for severe neurological disease and at distances greater than 7 km for fatal respiratory disease. Characteristics of cases attending surveillance hospitals were largely representative of all cases; however, neurological disease cases aged <5 y or from the lowest socioeconomic group and fatal respiratory disease cases aged ≥60 y were underrepresented. Our estimates of outbreak detection rely on suspected cases that attend a surveillance hospital receiving laboratory confirmation of disease and being reported to the surveillance system. The extent to which this occurs will depend on disease characteristics (e.g., severity and symptom specificity) and surveillance resources. CONCLUSION: We present a new approach to evaluating the sensitivity and representativeness of hospital-based surveillance, making it possible to predict its ability to detect emerging threats. Public Library of Science 2017-01-17 /pmc/articles/PMC5240927/ /pubmed/28095468 http://dx.doi.org/10.1371/journal.pmed.1002218 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Nikolay, Birgit Salje, Henrik Sturm-Ramirez, Katharine Azziz-Baumgartner, Eduardo Homaira, Nusrat Ahmed, Makhdum Iuliano, A. Danielle Paul, Repon C. Rahman, Mahmudur Hossain, M. Jahangir Luby, Stephen P. Cauchemez, Simon Gurley, Emily S. Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data |
title | Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data |
title_full | Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data |
title_fullStr | Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data |
title_full_unstemmed | Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data |
title_short | Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data |
title_sort | evaluating hospital-based surveillance for outbreak detection in bangladesh: analysis of healthcare utilization data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5240927/ https://www.ncbi.nlm.nih.gov/pubmed/28095468 http://dx.doi.org/10.1371/journal.pmed.1002218 |
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