Imperial College London
Alternate

ProfessorMaria-GloriaBasanez

Faculty of Medicine, School of Public Health

Professor of Neglected Tropical Diseases
 
 
 
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Contact

 

+44 (0)20 7594 3295m.basanez Website

 
 
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Location

 

503School of Public HealthWhite City Campus

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Summary

 

Publications

Citation

BibTex format

@article{Sykes:2022:10.1016/j.onehlt.2021.100359,
author = {Sykes, AL and Larrieu, E and Poggio, TV and Cespedes, MG and Mujica, GB and Basanez, M-G and Prada, JM},
doi = {10.1016/j.onehlt.2021.100359},
journal = {One Health},
pages = {1--7},
title = {Modelling diagnostics for echinococcus granulosus surveillance in sheep using latent class analysis: Argentina as a case study},
url = {http://dx.doi.org/10.1016/j.onehlt.2021.100359},
volume = {14},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Echinococcus granulosus sensu lato is a globally prevalent zoonotic parasitic cestode leading to cystic echinococcosis (CE) in both humans and sheep with both medical and financial impacts, whose reduction requires the application of a One Health approach to its control. Regarding the animal health component of this approach, lack of accurate and practical diagnostics in livestock impedes the assessment of disease burden and the implementation and evaluation of control strategies. We use of a Bayesian Latent Class Analysis (LCA) model to estimate ovine CE prevalence in sheep samples from the Río Negro province of Argentina accounting for uncertainty in the diagnostics. We use model outputs to evaluate the performance of a novel recombinant B8/2 antigen B subunit (rEgAgB8/2) indirect enzyme-linked immunosorbent assay (ELISA) for detecting E. granulosus in sheep. Necropsy (as a partial gold standard), western blot (WB) and ELISA diagnostic data were collected from 79 sheep within two Río Negro slaughterhouses, and used to estimate individual infection status (assigned as a latent variable within the model). Using the model outputs, the performance of the novel ELISA at both individual and flock levels was evaluated, respectively, using a receiver operating characteristic (ROC) curve, and simulating a range of sample sizes and prevalence levels within hypothetical flocks. The estimated (mean) prevalence of ovine CE was 27.5% (95%Bayesian credible interval (95%BCI): 13.8%–58.9%) within the sample population. At the individual level, the ELISA had a mean sensitivity and specificity of 55% (95%BCI: 46%–68%) and 68% (95%BCI: 63%–92%), respectively, at an optimal optical density (OD) threshold of 0.378. At the flock level, the ELISA had an 80% probability of correctly classifying infection at an optimal cut-off threshold of 0.496. These results suggest that the novel ELISA could play a useful role as a flock-level diagnostic for CE surveillan
AU  - Sykes,AL
AU  - Larrieu,E
AU  - Poggio,TV
AU  - Cespedes,MG
AU  - Mujica,GB
AU  - Basanez,M-G
AU  - Prada,JM
DO  - 10.1016/j.onehlt.2021.100359
EP  - 7
PY  - 2022///
SN  - 2352-7714
SP  - 1
TI  - Modelling diagnostics for echinococcus granulosus surveillance in sheep using latent class analysis: Argentina as a case study
T2  - One Health
UR  - http://dx.doi.org/10.1016/j.onehlt.2021.100359
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000731774300001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.sciencedirect.com/science/article/pii/S235277142100149X?via%3Dihub
UR  - http://hdl.handle.net/10044/1/93493
VL  - 14
ER  -
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