title: Evaluating Hospital-Based Surveillance for Outbreak Detection in Bangladesh: Analysis of Healthcare Utilization Data.
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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.|Centre National de la Recherche Scientifique, URA3012, Paris, France.|Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France.
authors.forename: Birgit
authors.initials: B
authors.lastname: Nikolay
authors.affiliation: Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.|Centre National de la Recherche Scientifique, URA3012, Paris, France.|Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France.|Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
authors.forename: Henrik
authors.initials: H
authors.lastname: Salje
authors.affiliation: Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.|Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh.
authors.forename: Katharine
authors.initials: K
authors.lastname: Sturm-Ramirez
authors.affiliation: Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Azziz-Baumgartner
authors.affiliation: Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh.|Discipline of Paediatrics, School of Women's and Children's Health, University of New South Wales, Sydney, New South Wales, Australia.
authors.forename: Nusrat
authors.initials: N
authors.lastname: Homaira
authors.affiliation: School of Public Health, University of Texas Health Science Center, Houston, Texas, United States of America.|Department of Lymphoma and Myeloma, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
authors.forename: Makhdum
authors.identifier: http://orcid.org/0000-0002-0772-8710
authors.initials: M
authors.lastname: Ahmed
authors.affiliation: Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
authors.forename: A Danielle
authors.initials: AD
authors.lastname: Iuliano
authors.affiliation: Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh.|School of Public Health and Community Medicine, University of New South Wales Australia, Sydney, New South Wales, Australia.
authors.forename: Repon C
authors.initials: RC
authors.lastname: Paul
authors.affiliation: Institute of Epidemiology, Disease Control and Research, Dhaka, Bangladesh.
authors.forename: Mahmudur
authors.identifier: http://orcid.org/0000-0002-3698-4852
authors.initials: M
authors.lastname: Rahman
authors.affiliation: Medical Research Council Unit The Gambia, Banjul, The Gambia.
authors.forename: M Jahangir
authors.initials: MJ
authors.lastname: Hossain
authors.affiliation: Infectious Diseases Division, Stanford University, Stanford, California, United States of America.
authors.forename: Stephen P
authors.identifier: http://orcid.org/0000-0001-5385-899X
authors.initials: SP
authors.lastname: Luby
authors.affiliation: Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.|Centre National de la Recherche Scientifique, URA3012, Paris, France.|Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France.
authors.forename: Simon
authors.initials: S
authors.lastname: Cauchemez
authors.affiliation: Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh.
authors.forename: Emily S
authors.initials: ES
authors.lastname: Gurley
mesh_terms: D001459:Bangladesh / Q000453:epidemiology; D002494:Central Nervous System Infections / Q000453:epidemiology; D004196:Disease Outbreaks / Q000517:prevention & control; D006760:Hospitalization / Q000706:statistics & numerical data; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D011159:Population Surveillance / Q000379:methods*; D012141:Respiratory Tract Infections / Q000453:epidemiology; D012680:Sensitivity and Specificity