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

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Table 7.1 Total and subset numbers of cases of tuberculosis identified by investigated sources and source-specific observed sensitivities Observed cases Physician notification system Laboratory Hospital discharge records n (%) Frequency Sensitivity Frequency Sensitivity Frequency Sensitivity Total 657 557 84.8 285 43.4 406 61.8 Sex Male* 377 (58) 322 85.4 168 44.6 226 59.9 Female* 278 (42) 235 84.5 115 41.4 180 64.7 Area of origin Low TB prevalence countries 486 (74) 401 82.5 198 40.7 319 65.6 High TB prevalence countries 171 (26) 156 91.2 87 50.9 87 50.9 Location of TB Pulmonary TB † 434 (66) 387 89.2 250 57.6 268 61.7 Extra-pulmonary TB † 211 (32) 158 74.9 52 24.6 193 91.5 Age
Chapter 7 82.5%), for pulmonary tuberculosis than for non-pulmonary tuberculosis (89.2% vs. 74.9%), for tuberculosis patients aged < 60 than for older patients (87.7% vs. 80.9%) and for persons from the Turin metropolitan area than from the rest of the Piedmont Region (94.5% vs. 83.4%). The sensitivity of hospital discharge records was 61.8%, ranging from 50.9% for persons from HTBCs to more than 90% for non-pulmonary cases. The laboratory source had the lowest overall sensitivity (43.3%) and the highest sensitivity levels for this source were for confirmed (59.7%) and pulmonary tuberculosis cases (57.6%). Capture-recapture models The estimates for each log-linear model are shown in Table 7.2. The selected model allowed for capture dependency between the surveillance and laboratory sources, and did not take into account heterogeneity (deviance 27.6; standard error (SE) 10). Three models with appealing goodness-of-fit criteria were rejected because their estimates were unstable, as reflected by the high standard error. The selected model estimated 47 (95%CI 31-71) tuberculosis patients unknown to all three sources, resulting in an estimated total of 704 (95%CI 688-728) incident cases of tuberculosis in the Piedmont Region in 2001. We then estimated the number of tuberculosis cases in various subsets (Table 7.3), using the same log-linear model for all grouping variables. The total number of microbiologically confirmed cases was estimated, using three sources, at 500 (95%CI 490–517). The number of probable tuberculosis cases, which by case-definition cannot be captured by the laboratory source, was estimated, using two sources, at 237 (95%CI 214- 273). The 95%CI of the total number of tuberculosis cases estimated by geographic origin, location of tuberculosis, age group, and bacteriological status overlapped with the 95%CI of the non-stratified estimate. Estimated source-specific sensitivity and incidence The overall estimated ascertainment of tuberculosis cases (i.e. cases recorded in at least one of the registers examined) was 93.3%. Although notification of diagnosis and treatment of tuberculosis is mandatory, the estimated sensitivity of the ‘physician notification system’ system was 79.1% (95%CI 76.5-80.1%) (Table 7.3). The system performed better in the Turin metropolitan area (sensitivity 92.1%). The analysis showed that persons aged ≥ 60 years (sensitivity 74.8%) and non-pulmonary cases (sensitivity, 74.2%) are relatively underreported or underdetected. The system was more likely to capture cases in persons from HTBCs (sensitivity 86.1%) than in those from LTBCs (sensitivity 76.8%). The estimated overall annual tuberculosis incidence rate was 16.7/100 000, with 11.9 cases per 100 000 population microbiologically confirmed. The incidence estimates varied widely according to the population subset being investigated. The estimated annual incidence rate was 12.6/100 000 among persons from LTBCs and 214.1/100 000 among immigrants from HTBCs. The estimated annual tuberculosis rate in the Turin metropolitan area (32.1/100 000) was nearly three times higher than in the rest of the Piedmont Region (11/100 000). The estimated annual incidence of pulmonary tuberculosis (10.8/100 000) was twice that of non-pulmonary (5.0/100 000), as was that 102
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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
Page 51 and 52: Chapter 3 52. Reintjes R, Termorshu
Page 53 and 54: Chapter 4 Abstract The aim of this
Page 55 and 56: Chapter 4 Methods Nearly all Dutch
Page 57 and 58: Chapter 4 Table 4.2 The number of m
Page 59 and 60: 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 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 and 112: Chapter 8 Abstract In 1999 the Enha
Page 113 and 114: Chapter 8 bacteriological confirmat
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
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Estimating infectious disease incid
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Chapter 11 The aim of this thesis i
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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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