Detection of a local Mycobacterium bovis reservoir using cattle surveillance data

The incidence of bovine tuberculosis (TB, caused by Mycobacterium bovis) in cattle has been associated with TB in badgers ( Meles meles) in parts of England. The aim was to identify badger associated M. bovis reservoirs in the Edge Area, between the High and Low Risk Areas for cattle TB. Data from badger TB surveys were sparse. Therefore, a definition for a local M. bovis reservoir potentially shared by cattle and badgers was developed using cattle TB surveillance data. The performance of the definition was estimated through Latent Class Analysis using badger TB survey data. Spatial units (25 km ) in the Edge Area were classified as having a reservoir if they had i) at least one OTF-W (Officially Tuberculosis Free – Withdrawn) incident in a cattle herd not attributed to cattle movement in the previous two years, ii) more OTF-W incidents than Officially Tuberculosis Free – Suspended (OTF-S) incidents in the previous two years and iii) at least one TB incident (OTF-S or OTF-W) in at least three of the previous seven years. Approximately twenty percent of the Edge Area was classified as having a local M. bovis reservoir using the cattle-based definition. Assuming 15% TB prevalence in Edge Area badgers, sensitivity for the local M. bovis reservoir definition varied from 25.7% (95% Credible Interval (CrI) 10.7 to 85.1 %) to 64.8 % (95% CrI 48.1 to 88.0 %). Specificity was 91.9% (CrI 83.6 to 97.4 %). Over ninety percent of the local reservoir was in stable endemic TB areas identified through previous work and its spatial distribution was largely consistent with local veterinary knowledge. Uncertainty in the reservoir spatial distribution was explored through its recalculation in spatial units shifted in different directions. We recommend that the definition is re-evaluated as further data on badger infection with M. bovis becomes available.

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Evaluation of post-mortem diagnostic tests' sensitivity and specificity for bovine tuberculosis using Bayesian latent class analysis

Research in Veterinary Science ◽

10.1016/j.rvsc.2019.04.014 ◽

2019 ◽

Vol 125 ◽

pp. 14-23

Author(s):

Paulo Martins Soares Filho ◽

Alberto Knust Ramalho ◽

André de Moura Silva ◽

Mikael Arrais Hodon ◽

Marina de Azevedo Issa ◽

...

Keyword(s):

Latent Class Analysis ◽

Sensitivity And Specificity ◽

Bovine Tuberculosis ◽

Diagnostic Tests ◽

Latent Class ◽

Post Mortem ◽

Class Analysis ◽

Bayesian Latent Class Analysis

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Heterogeneity in the risk of Mycobacterium bovis infection in European badger (Meles meles) cubs

Epidemiology and Infection ◽

10.1017/s095026881300040x ◽

2013 ◽

Vol 141 (7) ◽

pp. 1458-1466 ◽

Cited By ~ 6

Author(s):

A. J. TOMLINSON ◽

M. A. CHAMBERS ◽

S. P. CARTER ◽

G. J. WILSON ◽

G. C. SMITH ◽

...

Keyword(s):

Mycobacterium Bovis ◽

Bovine Tuberculosis ◽

Control Strategies ◽

Temporal Distribution ◽

Population Level ◽

Meles Meles ◽

Structured Populations ◽

Risk Of Infection ◽

Spatio Temporal ◽

European Badgers

SUMMARYThe behaviour of certain infected individuals within socially structured populations can have a disproportionately large effect on the spatio-temporal distribution of infection. Endemic infection with Mycobacterium bovis in European badgers (Meles meles) in Great Britain and Ireland is an important source of bovine tuberculosis in cattle. Here we quantify the risk of infection in badger cubs in a high-density wild badger population, in relation to the infection status of resident adults. Over a 24-year period, we observed variation in the risk of cub infection, with those born into groups with resident infectious breeding females being over four times as likely to be detected excreting M. bovis than cubs from groups where there was no evidence of infection in adults. We discuss how our findings relate to the persistence of infection at both social group and population level, and the potential implications for disease control strategies.

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Diagnostic Test Accuracy in Childhood Pulmonary Tuberculosis: A Bayesian Latent Class Analysis

American Journal of Epidemiology ◽

10.1093/aje/kww094 ◽

2016 ◽

Vol 184 (9) ◽

pp. 690-700 ◽

Cited By ~ 29

Author(s):

Samuel G. Schumacher ◽

Maarten van Smeden ◽

Nandini Dendukuri ◽

Lawrence Joseph ◽

Mark P. Nicol ◽

...

Keyword(s):

Pulmonary Tuberculosis ◽

Latent Class Analysis ◽

Chest Radiography ◽

Latent Class ◽

Credible Interval ◽

Smear Microscopy ◽

Test Accuracy ◽

Class Analysis ◽

Antituberculosis Treatment ◽

Bayesian Latent Class Analysis

AbstractEvaluation of tests for the diagnosis of childhood pulmonary tuberculosis (CPTB) is complicated by the absence of an accurate reference test. We present a Bayesian latent class analysis in which we evaluated the accuracy of 5 diagnostic tests for CPTB. We used data from a study of 749 hospitalized South African children suspected to have CPTB from 2009 to 2014. The following tests were used: mycobacterial culture, smear microscopy, Xpert MTB/RIF (Cepheid Inc.), tuberculin skin test (TST), and chest radiography. We estimated the prevalence of CPTB to be 27% (95% credible interval (CrI): 21, 35). The sensitivities of culture, Xpert, and smear microscopy were estimated to be 60% (95% CrI: 46, 76), 49% (95% CrI: 38, 62), and 22% (95% CrI: 16, 30), respectively; specificities of these tests were estimated in accordance with prior information and were close to 100%. Chest radiography was estimated to have a sensitivity of 64% (95% CrI: 55, 73) and a specificity of 78% (95% CrI: 73, 83). Sensitivity of the TST was estimated to be 75% (95% CrI: 61, 84), and it decreased substantially among children who were malnourished and infected with human immunodeficiency virus (56%). The specificity of the TST was 69% (95% CrI: 63%, 76%). Furthermore, it was estimated that 46% (95% CrI: 42, 49) of CPTB-negative cases and 93% (95% CrI: 82; 98) of CPTB-positive cases received antituberculosis treatment, which indicates substantial overtreatment and limited undertreatment.

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Evaluating diagnostic tests for bovine tuberculosis in the southern part of Germany: A latent class analysis

PLoS ONE ◽

10.1371/journal.pone.0179847 ◽

2017 ◽

Vol 12 (6) ◽

pp. e0179847 ◽

Cited By ~ 11

Author(s):

Valerie-Beau Pucken ◽

Gabriela Knubben-Schweizer ◽

Dörte Döpfer ◽

Andreas Groll ◽

Angela Hafner-Marx ◽

...

Keyword(s):

Latent Class Analysis ◽

Bovine Tuberculosis ◽

Diagnostic Tests ◽

Latent Class ◽

Class Analysis

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Performance of a Noninvasive Test for Detecting Mycobacterium bovis Shedding in European Badger (Meles meles) Populations

Journal of Clinical Microbiology ◽

10.1128/jcm.00762-15 ◽

2015 ◽

Vol 53 (7) ◽

pp. 2316-2323 ◽

Cited By ~ 11

Author(s):

Hayley C. King ◽

Andrew Murphy ◽

Phillip James ◽

Emma Travis ◽

David Porter ◽

...

Keyword(s):

Mycobacterium Bovis ◽

Bovine Tuberculosis ◽

Meles Meles ◽

Control Measures ◽

Disease Spread ◽

Economic Losses ◽

Noninvasive Test ◽

Content Type ◽

Additional Information ◽

European Badger

The incidence ofMycobacterium bovis, the causative agent of bovine tuberculosis, in cattle herds in the United Kingdom is increasing, resulting in substantial economic losses. The European badger (Meles meles) is implicated as a wildlife reservoir and is the subject of control measures aimed at reducing the incidence of infection in cattle populations. Understanding the epidemiology ofM. bovisin badger populations is essential for directing control interventions and understanding disease spread; however, accurate diagnosis in live animals is challenging and currently uses invasive methods. Here we present a noninvasive diagnostic procedure and sampling regimen using field sampling of latrines and detection ofM. boviswith quantitative PCR tests, the results of which strongly correlate with the results of immunoassays in the field at the social group level. This method allowsM. bovisinfections in badger populations to be monitored without trapping and provides additional information on the quantities of bacterial DNA shed. Therefore, our approach may provide valuable insights into the epidemiology of bovine tuberculosis in badger populations and inform disease control interventions.

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