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Int J Tuberc Lung Dis. 2016 Aug;20(8):999-1003. doi: 10.5588/ijtld.16.0015.

Connectivity of diagnostic technologies: improving surveillance and accelerating tuberculosis elimination.

Author information

1
Pôle de Microbiologie Médicale, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium; Service de Microbiologie, Département de Biologie Clinique, Cliniques Universitaires Saint-Luc, Brussels, Belgium; European Society for Clinical Microbiology and Infectious Diseases (ESCMID) Study Group for Mycobacterial Infections (ESGMYC), ESCMID, Basel, Switzerland.
2
Foundation for Innovative New Diagnostics, Geneva, Switzerland.
3
Faculty of Health Sciences, Abomey-Calavi University, Cotonou, National Tuberculosis Programme, Cotonou, Benin.
4
TB Supranational Reference Laboratory, Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute, Milan, Italy.
5
Institute for Theoretical Biology, Department of Biology, Humboldt University of Berlin, Berlin, Germany; Epidemiological Modelling of Infectious Diseases, Robert Koch Institute, Berlin, Germany.
6
Unit of Mycobacteriology, Department of Biomedical Sciences, Institute of Tropical Medicine, Belgium.
7
European Society for Clinical Microbiology and Infectious Diseases (ESCMID) Study Group for Mycobacterial Infections (ESGMYC), ESCMID, Basel, Switzerland; Université Paris Diderot, Institut National de la Santé et de la Recherche Médicale, Unité mixte de recherche 1137, Infection, Antimicrobiens, Modélisation, Evolution, Paris, Bactériologie, Assistance Publique-Hôpitaux de Paris, Hôpital Lariboisière, Paris, France.
8
Aurum Institute, Johannesburg, South Africa.
9
Yale School of Public Health, Yale University, New Haven, Connecticut, USA.
10
Pôle de Microbiologie Médicale, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium; Service de Microbiologie, Département de Biologie Clinique, Cliniques Universitaires Saint-Luc, Brussels, Belgium.
11
Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Centre for Operations Research and Econometrics, Université Catholique de Louvain, Belgium.
12
Massachusetts General Hospital, Boston, Massachusetts, USA.
13
Interactive Health Solutions, Karachi, Pakistan.
14
Sungkyunkwan University, Seoul, South Korea.
15
Harvard Medical School Center for Global Health Delivery, Dubai, United Arab Emirates.
16
Interactive Research and Development, Karachi, Pakistan.
17
TB Centre, London School of Hygiene & Tropical Medicine, London, UK.
18
Institute for Biocomputation and Physics of Complex Systems (BIFI), Department of Theoretical Physics, Faculty of Sciences, University of Zaragoza, Zaragoza, Spain.
19
UNITAID, Geneva, Switzerland.
20
McGill International TB Centre & McGill Global Health Programs, McGill University, Montreal, Quebec, Canada.
21
University Hospital Southampton NHS Foundation Trust, Southampton, UK.
22
Management Sciences for Health, Gauteng, South Africa.
23
Karolinska Institutet, Stockholm, Sweden, Université de Namur, Namur, Belgium.
24
Global Connectivity LLC, Somerville, Massachusetts, USA.
25
International Union Against Tuberculosis and Lung Disease, France.
26
Stop TB Partnership, Geneva, Switzerland.

Abstract

In regard to tuberculosis (TB) and other major global epidemics, the use of new diagnostic tests is increasing dramatically, including in resource-limited countries. Although there has never been as much digital information generated, this data source has not been exploited to its full potential. In this opinion paper, we discuss lessons learned from the global scale-up of these laboratory devices and the pathway to tapping the potential of laboratory-generated information in the field of TB by using connectivity. Responding to the demand for connectivity, innovative third-party players have proposed solutions that have been widely adopted by field users of the Xpert(®) MTB/RIF assay. The experience associated with the utilisation of these systems, which facilitate the monitoring of wide laboratory networks, stressed the need for a more global and comprehensive approach to diagnostic connectivity. In addition to facilitating the reporting of test results, the mobility of digital information allows the sharing of information generated in programme settings. When they become easily accessible, these data can be used to improve patient care, disease surveillance and drug discovery. They should therefore be considered as a public health good. We list several examples of concrete initiatives that should allow data sources to be combined to improve the understanding of the epidemic, support the operational response and, finally, accelerate TB elimination. With the many opportunities that the pooling of data associated with the TB epidemic can provide, pooling of this information at an international level has become an absolute priority.

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