Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data

Birgit Nikolay, Henrik Salje, Katharine Sturm-Ramirez, Eduardo Azziz-Baumgartner, Nusrat Homaira, Makhdum Ahmed, A Danielle Iuliano, Repon C Paul, Mahmudur Rahman, M Jahangir Hossain, Stephen P Luby, Simon Cauchemez and Emily S Gurley

PLOS Medicine, 2017, vol. 14, issue 1, 1-18

Abstract: 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. 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. Henrik Salje and colleagues propose a framework to examine the capacity of hospital-based surveillance data to detect public health threats in Bangladesh.Why Was This Study Done?: What Did the Researchers Do and Find?: What Do These Findings Mean?:

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pmed00:1002218

DOI: 10.1371/journal.pmed.1002218

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