Rob van Hest Capture-recapture Methods in Surveillance - RePub ...

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Introduction Underreporting of tuberculosis in England Since 1987, a rise in notifications of tuberculosis has been observed in England. 1 This increase is believed to be real, reflecting an increase in diagnoses of tuberculosis, rather than an artefact due to improved reporting. 2 Nevertheless, between 7% and 27% of cases of tuberculosis have been estimated not to be notified in the United Kingdom (UK). 3 In 1999, a revised national routine surveillance system for tuberculosis, Enhanced Tuberculosis Surveillance, was introduced to improve the completeness of reporting as well as the information on reported cases. 4 The aim of this study was to estimate the annual incidence of tuberculosis in England and assess the completeness of reporting between 1999 and 2002 using record-linkage and capture-recapture methodology. The accuracy and completeness of surveillance data can be increased through record-linkage between datasets of cases reported from different sources. 5-8 This is carried out routinely for cases reported in Enhanced Tuberculosis Surveillance by linking notifications with reports of Mycobacterium tuberculosis isolates from the reference laboratories in the UK Mycobacterial Network (MycobNet). The number of cases missed can then be estimated using the overlap between the two data sources through capturerecapture analysis. 9 The preferred capture-recapture method entails log-linear modelling of at least three linked data sources. 10-13 The completeness of the different data sources can be assessed by comparison with the case-ascertainment, i.e. the total number of patients observed in at least one data source, or the estimated total number of cases. Capturerecapture analysis has been used to evaluate surveillance systems of various infectious diseases in the UK. 14-16 The same methodology has been applied to tuberculosis surveillance in studies in both the UK and elsewhere. 17-20 Methods Case definition and data sources For the purpose of estimating the number of unobserved tuberculosis cases we defined as eligible for inclusion those active tuberculosis cases first reported to one or more of three data sources in the four years, 1 January 1999 to 31 December 2002. The three data sources were: 1. Tuberculosis (Notification). cases notified through Enhanced Tuberculosis Surveillance 2. Cases with Mycobacterium tuberculosis complex isolates reported to MycobNet (Laboratory). 3. Cases admitted to National Health Service hospitals with a first or secondary hospital discharge code of tuberculosis (International Classification of Disease (ICD-10) code A15-A19) provided from Hospital Episode Statistics (Hospital). Two other data sources used for cross-validation will be mentioned later. An interval of more than one year between entries in each of the data sources was considered as a separate episode of disease. To correct for delays in case reporting and myco- 111
Chapter 8 bacteriological confirmation, records three months before and after the study period were also examined. Record-linkage Duplicate entries within each of the three data sources were excluded. Hospital records were linked to the previously linked Notification and Laboratory records. Record-linkage software developed by the Centre for Infections establishes a likelihood of association between two records based on a core set of identifiers (date of birth, age, full postcode and sex of the patient and proximity of date of notification, initial mycobacterial isolate or hospital admission). It allows for visual inspection of available additional information on geographical location, site of disease, ethnicity and smear, culture or histopathology results (when performed). All cases with incomplete or missing information on both the date of birth and age were labelled as “insufficient identifiers” and excluded. The software allocates an a priori determined maximum number of points to each core identifier for complete agreement, reflecting the perceived relative importance of that identifier. Record-pairs with full agreement of all core identifiers are automatically assigned as true links. Points are deducted proportionally to the presumed loss of information for increasing deviation from perfect linkage of each identifier to generate an aggregate score, reflecting the likelihood of association between two patient records. All categories of candidate-links other than automatically assigned links were visually inspected and either accepted or rejected. Linked cases were allocated to the year of first known date of notification, culture-confirmation or hospital admission. False-positive records and correction All laboratory-confirmed cases reported through MycobNet were assumed true tuberculosis cases, as previously found in a local capture-recapture study in England. 17 Notification and Hospital records not linked with Laboratory could potentially include three groups of false-positive records: 1. Cases ultimately diagnosed with an infection with Mycobacteria Other Than Tuberculosis (MOTT) 2. Cases with a final diagnosis other than tuberculosis or MOTT infection. 3. Cases misclassified or miscoded. The proportion of unlinked Hospital cases attributable to MOTT infection was estimated by linking Hospital data from 2003 with a MOTT database which began in that same year and used to correct the number of unlinked Hospital cases in all years under study using a formula explained below, assuming the annual proportion is similar. In order to estimate the proportion of cases with a final diagnosis other than tuberculosis or MOTT infection Notification cases not known to Laboratory were linked with Treatment Outcome Monitoring data, containing data on Notification cases with a final diagnosis other than tuberculosis. At the time of this study Treatment Outcome Monitoring data were only available for 2001. The proportion of false-positive 112
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Capture-recapture Methods in Survei
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Colofon Capture-recapture methods i
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Promotiecommissie Promotor: Prof.dr
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Contents Page 1 Introduction 9 2 Me
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Chapter 1 1.1 Assessing completenes
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Chapter 1 94% among AIDS patients w
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Table 1.1 Objectives, methods, data
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Researchers Objective Method Data-s
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Chapter 1 source capture-recapture
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Chapter 1 32. Bradley BL, Kerr KM,
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2 Methodology of capture-recapture
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Methodology of capture-recapture an
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Chapter 3 3.1 Application of captur
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Table 3.1 Published capture-recaptu
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Disease Authors Objective Method Da
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Chapter 3 3.3 References 1. Hook EB
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Chapter 3 52. Reintjes R, Termorshu
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Chapter 4 Abstract The aim of this
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Chapter 4 Methods Nearly all Dutch
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Chapter 4 Table 4.2 The number of m
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Chapter 4 diagnosis. Other patients
Page 61 and 62: Chapter 4 stratify the population i
Page 63 and 64: Chapter 4 25. Lambeth, Southwark an
Page 65 and 66: Chapter 5 Abstract To estimate inci
Page 67 and 68: Chapter 5 patients. Capture-recaptu
Page 69 and 70: Chapter 5 Figure 5.1 Four regions o
Page 71 and 72: Chapter 5 Hospital records From 385
Page 73 and 74: Chapter 5 Table 5.1 Epidemiological
Page 75 and 76: Table 5.2 Number and proportion of
Page 77 and 78: Chapter 5 cautious about the associ
Page 79 and 80: Chapter 5 Incidence of community-ac
Page 81 and 82: Chapter 6 Abstract The aim of this
Page 83 and 84: Chapter 6 3. Hospitalised patients
Page 85 and 86: Chapter 6 Record-linkage of all 537
Page 87 and 88: Chapter 6 Figure 6.1 Schematic view
Page 89 and 90: Chapter 6 Table 6.2 Total and strat
Page 91 and 92: Chapter 6 administrative discrepanc
Page 93 and 94: Chapter 6 the patients, and complet
Page 96 and 97: 7 Undetected burden of tuberculosis
Page 98 and 99: Introduction Underreporting of tube
Page 100 and 101: Underreporting of tuberculosis in t
Page 102 and 103: Table 7.1 Total and subset numbers
Page 104 and 105: Table 7.2 Capture-recapture estimat
Page 106 and 107: Underreporting of tuberculosis in t
Page 108: Underreporting of tuberculosis in t
Page 111: Chapter 8 Abstract In 1999 the Enha
Page 115 and 116: Chapter 8 Results Table 8.1 shows t
Page 117 and 118: Table 8.3 Annual and overall observ
Page 119 and 120: Table 8.4 Annual and overall estima
Page 121 and 122: Chapter 8 interaction however, i.e.
Page 123 and 124: Chapter 8 shows that observed under
Page 126 and 127: 9 Estimating the coverage of tuberc
Page 128 and 129: Introduction Estimating targeted mo
Page 130 and 131: Estimating targeted mobile tubercul
Page 136 and 137: References Estimating targeted mobi
Page 138 and 139: 10 Estimating infectious diseases i
Page 140 and 141: Introduction Estimating infectious
Page 142 and 143: Estimating infectious disease incid
Page 144 and 145: Study Disease and number of patient
Page 146 and 147: 4. Gallay A, Vaillant V, Bouvet P,
Page 148 and 149: Table 10.3 Comparison of the variou
Page 150 and 151: Discussion Estimating infectious di
Page 156: Estimating infectious disease incid
Page 159 and 160: Chapter 11 The aim of this thesis i
Page 161 and 162: Chapter 11 overestimation of the nu
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Chapter 11 clinicians to the Public
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Chapter 11 operation with the chest
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Chapter 11 of the proportion of fal
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Chapter 11 Question 3: What is the
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Chapter 11 11.2 Some findings of th
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Chapter 11 • To improve timelines
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Summary Summary Surveillance is an
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Summary linkage of notification and
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Samenvatting Samenvatting Surveilla
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Samenvatting subgroepen binnen de b
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Acknowledgements Acknowledgements W
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Curriculum vitae Rob van Hest was b
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Publications This thesis Van Hest N
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