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Summary: Background: Expansion of antimicrobial resistance monitoring and epidemiological surveillance are key components of the WHO strategy towards zero leprosy. The inability to grow Mycobacterium leprae in vitro precludes routine phenotypic drug susceptibility testing, and only limited molecular tests are available. We evaluated a culture-free targeted deep sequencing assay, for mycobacterial identification, genotyping based on 18 canonical SNPs and 11 core variable-number tandem-repeat (VNTR) markers, and detection of rifampicin, dapsone and fluoroquinolone resistance-associated mutations in rpoB/ctpC/ctpI, folP1, gyrA/gyrB, respectively, and hypermutation-associated mutations in nth. Methods: The limit of detection (LOD) was determined using DNA of M. leprae reference strains and from 246 skin biopsies and 74 slit skin smears of leprosy patients, with genome copies quantified by RLEP qPCR. Sequencing results were evaluated versus whole genome sequencing (WGS) data of 14 strains, and versus VNTR-fragment length analysis (FLA) results of 89 clinical specimens. Findings: The LOD for sequencing success ranged between 80 and 3000 genome copies, depending on the sample type. The LOD for minority variants was 10%. All SNPs detected in targets by WGS were identified except in a clinical sample where WGS revealed two dapsone resistance-conferring mutations instead of one by Deeplex Myc-Lep, due to partial duplication of the sulfamide-binding domain in folP1. SNPs detected uniquely by Deeplex Myc-Lep were missed by WGS due to insufficient coverage. Concordance with VNTR-FLA results was 99.4% (926/932 alleles). Interpretation: Deeplex Myc-Lep may help improve the diagnosis and surveillance of leprosy. Gene domain duplication is an original putative drug resistance-related genetic adaptation in M. leprae. Funding: EDCTP2 programme supported by the European Union (grant number RIA2017NIM-1847 -PEOPLE). EDCTP, R2Stop: Effect:Hope, The Mission To End Leprosy, the Flemish Fonds Wetenschappelijk Onderzoek.

Objectives: To identify patterns of spatial clustering of leprosy., Design: We performed a baseline survey for a trial on post-exposure prophylaxis for leprosy in Comoros and Madagascar. We screened 64 villages, door-to-door, and recorded results of screening, demographic data and geographic coordinates. To identify clusters, we fitted a purely spatial Poisson model using Kulldorff's spatial scan statistic. We used a regular Poisson model to assess the risk of contracting leprosy at the individual level as a function of distance to the nearest known leprosy patient., Results: We identified 455 leprosy patients; 200 (44.0%) belonged to 2735 households included in a cluster. Thirty-eight percent of leprosy patients versus 10% of the total population live ≤25 m from another leprosy patient. Risk ratios for being diagnosed with leprosy were 7.3, 2.4, 1.8, 1.4 and 1.7, for those at the same household, at 1-<25 m, 25-<50 m, 50-<75 m and 75-<100 m as/from a leprosy patient, respectively, compared to those living at ≥100 m., Conclusions: We documented significant clustering of leprosy beyond household level, although 56% of cases were not part of a cluster. Control measures need to be extended beyond the household, and social networks should be further explored., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)