Related Experiment Video
Updated: Jun 8, 2026

DNA Fingerprinting of Mycobacterium leprae Strains Using Variable Number Tandem Repeat (VNTR) - Fragment Length Analysis (FLA)
Published on: July 15, 2011
An analysis of relapsed leprosy cases.
1Department of Dermatology and Venereology, Medical, India.
Leprosy relapse rates increased annually, with paucibacillary leprosy cases being more susceptible than multibacillary ones. Treatment duration and type did not prevent leprosy relapse, suggesting inherent factors may be involved.
Area of Science:
- Dermatology
- Infectious Diseases
- Epidemiology
Background:
- Leprosy remains a public health concern, with relapses impacting disease control efforts.
- Understanding relapse patterns is crucial for refining treatment strategies and improving patient outcomes.
Purpose of the Study:
- To analyze the characteristics and trends of relapsed leprosy cases over a five-year period.
- To identify factors influencing leprosy relapse, including clinical presentation and treatment regimens.
Main Methods:
- Retrospective analysis of leprosy cases registered at an urban dermatology center.
- Evaluation of clinical features, treatment types, and treatment duration for relapsed cases.
Main Results:
- A 3.88% relapse rate was observed over the five-year study period.
- Paucibacillary leprosy cases exhibited a higher susceptibility to relapse (5.4%) compared to multibacillary cases (2.15%).
- Relapse rates showed a year-on-year increase, and prolonged treatment did not prevent relapses.
Conclusions:
- Leprosy relapse may be an inherent characteristic of certain cases, independent of treatment factors.
- Further research into host factors and genetic predispositions is warranted to understand leprosy relapse.
- Current treatment strategies may require re-evaluation to address inherent relapse mechanisms in leprosy.
More Related Videos
10:32Optimized Protocols for Mycobacterium leprae Strain Management: Frozen Stock Preservation and Maintenance in Athymic Nude Mice
Published on: March 23, 2014
10:46A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015