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

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Underreporting of Legionnaires’ disease in the Netherlands notification but the notified and ascertained incidence rates in region South were higher than in the rest of the Netherlands (P < 0.0001). Capture-recapture analysis Internal validity analysis by two-source capture-recapture analysis on Notification and Hospital and on Laboratory and Hospital both estimate 865 Legionnaires’ disease patients through Chapman’s Nearly Unbiased Estimator. The considerable lower capturerecapture estimate obtained with Notification and Laboratory (523 Legionnaires’ disease patients) indicates a larger positive association between this pair than between the other pairs, resulting in an estimate more biased downwards. The best-fitting three-source log-linear capture-recapture model was the saturated model, i.e. the model including all two-variable associations and assuming absent three-way interaction, which yielded an estimate of 1253 Legionnaires’ disease patients (95% confidence interval (CI) 1019-1715). Estimated under-notification was 70.2%. To acknowledge the geographical differences capture-recapture analysis stratified by region was performed. For all regions apart from region East a more parsimonious model, containing only one two-way interaction (between Notification and Laboratory), was selected as best-fitting model, with totals of 78, 327 and 277 Legionnaires’ disease patients and incidence rates of 2.33, 2.75 and 3.56 per 100 000 inhabitants for region North, West and South respectively. For region East a saturated model was selected that estimated an unexpectedly high number of 650 Legionnaires’ disease patients with a wide 95%CI of 283-2382 patients. As an alternative to the stratified capture-recapture analysis we specified a loglinear covariate (region) capture-recapture model. The covariate model that served as a starting point contained, apart from the main effects for Region and the three registers, the Region-Notification, Region-Laboratory, Region-Hospital, Notification-Laboratory, Notification-Hospital, Laboratory-Hospital two-variable terms. In this model we allow for regional differences in the number of cases in the three registers, but not for interaction with other effects per stratum, as the association between the registers is assumed equal across regions. This model fits the data reasonably well (G 2 = 22.1; df = 9; P = 0.009) and estimates 932 Legionnaires’ disease patients with a narrower CI of 851-1106, reducing statistical uncertainty. Inspection of the misfit for individual cells showed a large adjusted residual for Legionnaires’ disease patients only known to Laboratory in region East. After including a separate parameter for this single cell we obtain a good fitting model (G 2 = 5.7; df = 8; P = 0.686). The estimated number of Legionnaires’ disease patients was 886 (95%CI 827-1022), similar to the two internal validity estimates with least assumed interdependence. The estimated register-specific coverage rate of Notification, Laboratory and Hospital was 42.1% (373/886), 29.5% (261/886) and 74.9% (663/886) respectively. The estimated under-notification was 57.9%. The estimated average annual incidence rate of Legionnaires’ disease was 2.77/100 000. 71
Chapter 5 Table 5.1 Epidemiological characteristics of 447 Legionnaires’ disease patients* Age category 72 Male (N = 319) Female (N = 128) Total (N = 447) 0-19 years 0.3% (1/318) 4.7% (6/128) 1.6% (7/446) 20-39 years 11.9% (38/318) 18.0% (23/128) 13.7% (61/446) 40-59 years 55.3% (176/318) 43.8% (56/128) 52.0% (232/446) 60-79 years 28.9% (92/318) 30.5% (39/128) 29.4% (131/446) > 80 years 3.5% (11/318) 3.1% (4/128) 3.4% (15/446) Seasonal pattern: month of disease onset Jan-Feb 7.8% (25/319) 10.2% (13/128) 8.5% (38/447) Mar-Apr 11.0% (35/319) 10.9% (14/128) 11.0% (49/447) May-Jun 19.4% (62/319) 14.1% (18/128) 17.9% (80/447) Jul-Aug 26.6% (85/319) 25.0% (32/128) 26.2% (117/447) Sep-Oct 21.9% (70/319) 31.3% (40/128) 24.6% (110/447) Nov-Dec 13.2% (42/319) 8.6% (11/128) 11.9% (53/447) Travel abroad during incubation period † Travel abroad: yes Countries involved: 53% (169/319) 50% (64/128) 52% (233/447) Turkey 20% (33) 30% (19) 22% (52) France 23% (39) 8% (5) 19% (44) Spain 12% (21) 13% (8) 12% (29) Italy 8% (14) 11% (7) 9% (21) Germany 7% (12) 9% (6) 8% (18) Portugal 2% (4) 2% (1) 2% (5) Greece 2% (4) 2% (1) 2% (5) Belgium 3% (5) 0% 2% (5) Rest Europe 11% (18) 13% (8) 11% (26) America's 5% (9) 6% (4) 6% (13) Asia 3% (5) 2% (1) 3% (6) Africa 0% 3% (2) 1% (2) Unknown Legionella species 3% (5) 3% (2) 3% (7) L. pneumophila serogroup 1 61.2% (170/278) 54.5% (60/110) 59.3% (230/388) L. pneumophila serogroups 2-12 2.5% (7/278) 1.8% (2/110) 2.7% (9/388) L. non-pneumophila 3.2% (9/278) 0.9% (1/110) 2.6% (10/388) unknown 31.7% (88/278) 42.7% (47/110) 34.8% (135/388) Laboratory confirmation ‡ At least two confirming tests 22.0% (61/277) 17.3% (19/110) 20.7% (80/387) One confirming test 56.0% (155/277) 56.4% (62/110) 56.1% (217/387) Only probable test 22.0% (61/277) 26.4% (29/110) 23.3% (90/387) * From 448 patients sufficient data was available for analysis; sometimes one or two variables are missing; † Rest of Europe: Austria, Croatia, Cyprus, England, Hungary, Ireland, Luxemburg, Moldavia, Poland, Slovakia, Switzerland, Czech Republic, Yugoslavia; America's: Netherlands Antilles, Brazil, Canada, Dominican Republic,
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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
Page 21 and 22: Chapter 1 32. Bradley BL, Kerr KM,
Page 24 and 25: 2 Methodology of capture-recapture
Page 26 and 27: Methodology of capture-recapture an
Page 36: Methodology of capture-recapture an
Page 39 and 40: Chapter 3 3.1 Application of captur
Page 41 and 42: Table 3.1 Published capture-recaptu
Page 43 and 44: Disease Authors Objective Method Da
Page 49 and 50: 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: Chapter 5 Hospital records From 385
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 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.
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Chapter 8 shows that observed under
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9 Estimating the coverage of tuberc
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Introduction Estimating targeted mo
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Estimating targeted mobile tubercul
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References Estimating targeted mobi
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10 Estimating infectious diseases i
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Introduction Estimating infectious
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Estimating infectious disease incid
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Study Disease and number of patient
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4. Gallay A, Vaillant V, Bouvet P,
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Table 10.3 Comparison of the variou
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Discussion Estimating infectious di
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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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