@article{Meller_S-2022_201802,
title = {Expert considerations and consensus for using dogs to detect human SARS-CoV-2-infections},
author = {Meller, S. and Al Khatri, M. and Alhammadi, H. and Álvarez, G. and Alvergnat, G. and Alves, L. and Callewaert, C. and Caraguel, C. and Carancci, P. and Chaber, A. and Charalambous, M. and Desquilbet, L. and Ebbers, J. and Grandjean, D. and Guest, C. and Guyot, H. and Hielm-Björkman, A. and Hopkins, A. and Kreienbrock, L. and Logan, J. and Lorenzo, H. and de Cassia, R. and Mancilla-Tapia, J. and Mardones, F. and Mutesa, L. and Nsanzimana, S. and Otto, C. and Salgado-Caxito, M. and de los Santos, F. and da Silva, J. and Schalke, E. and Schoneberg, C. and Soares, A. and Twele, F. and Vidal-Martínez, V. and Zapata, A. and Zimin-Veselkoff, N. and Volk, H.},
month = {dec},
year = {2022},
abstract = {The respiratory coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) quickly developed into a pandemic. Even though laboratory diagnostic tests and vaccines were consequently developed, the exploration of rapidly deployable, more reliable tools for addressing the current and future pandemics was vital. Toward this goal, researchers worldwide evaluated the use of medical detection dogs as a rapid, reliable and cost-effective screening method for SARS-CoV-2 infections. The ability of dogs to distinguish diseases by their high-resolution sense of smell is based on the volatile organic compound (VOC)-hypothesis. Numerous infectious and non-infectious diseases change metabolic processes releasing characteristic VOC-patterns in the form of an “olfactory fingerprint”. Many studies have shown that dogs can detect metabolic disorders, such as cancerand hypoglycemia, predict epileptic seizures, or even distinguish various pathogens. Approximately 78% of the 27 SARS-CoV-2-canine detection studies reviewed by Meller et al. yielded &gt; 80% sensitivity and approximately 60% of studies yielded &gt; 95% of specificity, highlighting the potential of the dog as a “diagnostic system” and its recommendation for certain settings. Despite these promising results, all studies published up to now differed in numerous design features. They were mostly designed as pilot studies and case-control selection of patients was mostly favored over a more preferable cross-sectional (“cohort”) selection [study quality assessment was conducted and presented by Meller et al.]. The aim of this comprehensive review summary is to provide a general overview of the divergent aspects that may impact canine disease detection and to provide recommendations for future deployment of medical detection dogs (see also summary inTable 1). Specific emphasis is placed on the choice of dogs, training paradigms, safety aspects, sample characteristics, pre-screen processing (e.g., inactivation), and screening-population and its environment related aspects, respectively (see alsoFigure 1andSupplementary Figure 1), providing an outlook and proposals for the future standardization in the use of dogs for disease detection. Ultimately, this report provides a blueprint for the potential use of medical detection dogs in future epidemics and pandemics.},
volume = {9},
journal = {Frontiers in Medicine},
publisher = {Frontiers Media},
url = {https://doi.org/10.3389/fmed.2022.1015620},
}
