1
|
Fromsa A, Willgert K, Srinivasan S, Mekonnen G, Bedada W, Gumi B, Lakew M, Tadesse B, Bayissa B, Sirak A, Girma Abdela M, Gebre S, Chibssa T, Veerasami M, Vordermeier HM, Bakker D, Berg S, Ameni G, Juleff N, de Jong MCM, Wood J, Conlan A, Kapur V. BCG vaccination reduces bovine tuberculosis transmission, improving prospects for elimination. Science 2024; 383:eadl3962. [PMID: 38547287 DOI: 10.1126/science.adl3962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 01/24/2024] [Indexed: 04/02/2024]
Abstract
Bacillus Calmette-Guérin (BCG) is a routinely used vaccine for protecting children against Mycobacterium tuberculosis that comprises attenuated Mycobacterium bovis. BCG can also be used to protect livestock against M. bovis; however, its effectiveness has not been quantified for this use. We performed a natural transmission experiment to directly estimate the rate of transmission to and from vaccinated and unvaccinated calves over a 1-year exposure period. The results show a higher indirect efficacy of BCG to reduce transmission from vaccinated animals that subsequently become infected [74%; 95% credible interval (CrI): 46 to 98%] compared with direct protection against infection (58%; 95% CrI: 34 to 73%) and an estimated total efficacy of 89% (95% CrI: 74 to 96%). A mechanistic transmission model of bovine tuberculosis (bTB) spread within the Ethiopian dairy sector was developed and showed how the prospects for elimination may be enabled by routine BCG vaccination of cattle.
Collapse
Affiliation(s)
- Abebe Fromsa
- Aklilu Lemma Institutes of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
- College of Veterinary Medicine and Agriculture, Addis Ababa University, Bishoftu, Ethiopia
| | - Katriina Willgert
- Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, UK
| | - Sreenidhi Srinivasan
- Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Department of Animal Science, The Pennsylvania State University, University Park, PA, USA
- The Global Health Initiative, Henry Ford Health, Detroit, MI, USA
| | | | | | - Balako Gumi
- Aklilu Lemma Institutes of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
| | | | | | - Berecha Bayissa
- Aklilu Lemma Institutes of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
| | | | - Musse Girma Abdela
- Aklilu Lemma Institutes of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
| | | | | | | | | | - Douwe Bakker
- Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Technical Consultant and Independent Researcher, Lelystad, Netherlands
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad Complutense, Madrid, Spain
| | - Stefan Berg
- Animal and Plant Health Agency, Weybridge, UK
| | - Gobena Ameni
- Aklilu Lemma Institutes of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
- Department of Veterinary Medicine, College of Agriculture and Veterinary Medicine, United Arab Emirates University, United Arab Emirates
| | - Nick Juleff
- The Bill & Melinda Gates Foundation Seattle, WA, USA
| | - Mart C M de Jong
- Quantitative Veterinary Epidemiology Group, Wageningen UR, The Netherlands
| | - James Wood
- Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, UK
| | - Andrew Conlan
- Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, UK
| | - Vivek Kapur
- Huck Institutes of Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Department of Animal Science, The Pennsylvania State University, University Park, PA, USA
| |
Collapse
|
2
|
Friedrich S, Friede T. On the role of benchmarking data sets and simulations in method comparison studies. Biom J 2024; 66:e2200212. [PMID: 36810737 DOI: 10.1002/bimj.202200212] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 01/26/2023] [Accepted: 02/01/2023] [Indexed: 02/24/2023]
Abstract
Method comparisons are essential to provide recommendations and guidance for applied researchers, who often have to choose from a plethora of available approaches. While many comparisons exist in the literature, these are often not neutral but favor a novel method. Apart from the choice of design and a proper reporting of the findings, there are different approaches concerning the underlying data for such method comparison studies. Most manuscripts on statistical methodology rely on simulation studies and provide a single real-world data set as an example to motivate and illustrate the methodology investigated. In the context of supervised learning, in contrast, methods are often evaluated using so-called benchmarking data sets, that is, real-world data that serve as gold standard in the community. Simulation studies, on the other hand, are much less common in this context. The aim of this paper is to investigate differences and similarities between these approaches, to discuss their advantages and disadvantages, and ultimately to develop new approaches to the evaluation of methods picking the best of both worlds. To this aim, we borrow ideas from different contexts such as mixed methods research and Clinical Scenario Evaluation.
Collapse
Affiliation(s)
- Sarah Friedrich
- Institute of Mathematics, University of Augsburg, Augsburg, Germany
- Centre for Advanced Analytics and Predictive Sciences, University of Augsburg, Augsburg, Germany
| | - Tim Friede
- Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee, Göttingen, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Göttingen, Göttingen, Germany
| |
Collapse
|