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Background: Case detection delay (CDD) in leprosy is defined as the period between the onset of the first signs and symptoms and the time of diagnosis. A tool, consisting of a questionnaire and a detailed guide for researchers, which includes photos of typical skin signs and notes on establishing the timing of events, was developed to determine this period of delay in months in recently diagnosed leprosy patients. The aims of the study were to determine the reliability and consistency of this CDD assessment tool. Methods: This study was conducted in Ethiopia, Mozambique and Tanzania. Two types of consistency were considered: over time (test-retest reliability) and across different researchers (interrater reliability). A CDD questionnaire was administered to 167 leprosy patients who were diagnosed within 6 months prior to their inclusion. One month later, the same or another researcher re-administered the CDD questionnaire to the same patients. Both test-retest and interrater reliability were assessed using the intraclass correlation coefficient (ICC), where a value greater than or equal to 0.7 is considered acceptable. Results: In this study, 10 participants (6.0%) were under 15 years of age, and 56 (33.5%) were women. In the test-retest assessment, the mean CDD from the first and second interviews was 23.7 months (95% CI 14.4–34.8) and 24.0 months (95% CI 14.8–33.2), respectively. The ICC for test-retest reliability was 0.99 (95% CI 0.994–0.997). For the interrater reliability assessment, the first and second interviews revealed a mean CDD of 24.7 months (95% CI 18.2–31.1) and 24.6 months (95% CI 18.7–30.5), respectively, with an ICC of 0.90 (95% CI 0.85–0.94). A standard error of measurement of 0.46 months was found in the test-retest and 1.03 months in the interrater measurement. Most answers given by participants during the first and second interviews were matching (≥86%). Most non-matching answers were in the 0–2 month delay category (≥46%). Conclusion: The tool, including a questionnaire to determine the CDD of newly diagnosed leprosy patients, was validated in three African countries. The test-retest and interrater measurements demonstrated that the instrument is reliable and measures consistently. The tool can be used in routine leprosy programmes as well as in research settings. Author summary: Leprosy is an ancient infectious disease that still affects up to 200,000 new patients yearly worldwide, with an estimated three to four million people living with permanent disability. A delay in case detection is a major factor contributing to the development of disability. Case detection delay is defined as the interval between the onset of the disease's initial signs and symptoms and the time of diagnosis, comprising a 'patient delay' and a 'health-system delay'. The case detection delay tool was first designed in the cultural context of the East Hararghe Zone, Ethiopia, as part of the PEP4LEP project. Subsequently, it was standardised to enable cultural adaptation to other regions and countries. The aims of this study were to determine the reliability and consistency of this case detection delay (CDD) assessment tool. The studied tool was validated in Ethiopia, Mozambique and Tanzania. The test-retest and interrater measurements demonstrated that the instrument is reliable and measures consistently. The tool can be used in routine leprosy programmes, active case detection projects, and in studies such as the PEP4LEP project. The tool is available in English, Oromiffa (Afaan Oromo), Portuguese, and Swahili via the international leprosy knowledge centre Infolep: https://www.leprosy-information.org/resource/case-detection-delay-questionnaire [ABSTRACT FROM AUTHOR]

Background: Leprosy is an infectious disease caused by Mycobacterium leprae and remains a source of preventable disability if left undetected. Case detection delay is an important epidemiological indicator for progress in interrupting transmission and preventing disability in a community. However, no standard method exists to effectively analyse and interpret this type of data. In this study, we aim to evaluate the characteristics of leprosy case detection delay data and select an appropriate model for the variability of detection delays based on the best fitting distribution type. Methods: Two sets of leprosy case detection delay data were evaluated: a cohort of 181 patients from the post exposure prophylaxis for leprosy (PEP4LEP) study in high endemic districts of Ethiopia, Mozambique, and Tanzania; and self-reported delays from 87 individuals in 8 low endemic countries collected as part of a systematic literature review. Bayesian models were fit to each dataset to assess which probability distribution (log-normal, gamma or Weibull) best describes variation in observed case detection delays using leave-one-out cross-validation, and to estimate the effects of individual factors. Results: For both datasets, detection delays were best described with a log-normal distribution combined with covariates age, sex and leprosy subtype [expected log predictive density (ELPD) for the joint model: −1123.9]. Patients with multibacillary (MB) leprosy experienced longer delays compared to paucibacillary (PB) leprosy, with a relative difference of 1.57 [95% Bayesian credible interval (BCI): 1.14–2.15]. Those in the PEP4LEP cohort had 1.51 (95% BCI: 1.08–2.13) times longer case detection delay compared to the self-reported patient delays in the systematic review. Conclusions: The log-normal model presented here could be used to compare leprosy case detection delay datasets, including PEP4LEP where the primary outcome measure is reduction in case detection delay. We recommend the application of this modelling approach to test different probability distributions and covariate effects in studies with similar outcomes in the field of leprosy and other skin-NTDs. [ABSTRACT FROM AUTHOR]

Introduction: Leprosy, or Hansen's disease, remains a cause of preventable disability. Early detection, treatment and prevention are key to reducing transmission. Post-exposure prophylaxis with single-dose rifampicin (SDR-PEP) reduces the risk of developing leprosy when administered to screened contacts of patients. This has been adopted in the WHO leprosy guidelines. The PEP4LEP study aims to determine the most effective and feasible method of screening people at risk of developing leprosy and administering chemoprophylaxis to contribute to interrupting transmission., Methods and Analysis: PEP4LEP is a cluster-randomised implementation trial comparing two interventions of integrated skin screening combined with SDR-PEP distribution to contacts of patients with leprosy in Ethiopia, Mozambique and Tanzania. One intervention is community-based, using skin camps to screen approximately 100 community contacts per leprosy patient, and to administer SDR-PEP when eligible. The other intervention is health centre-based, inviting household contacts of leprosy patients to be screened in a local health centre and subsequently receive SDR-PEP when eligible. The mobile health (mHealth) tool SkinApp will support health workers' capacity in integrated skin screening. The effectiveness of both interventions will be compared by assessing the rate of patients with leprosy detected and case detection delay in months, as well as feasibility in terms of cost-effectiveness and acceptability., Ethics and Dissemination: Ethical approval was obtained from the national ethical committees of Ethiopia (MoSHE), Mozambique (CNBS) and Tanzania (NIMR/MoHCDEC). Study results will be published open access in peer-reviewed journals, providing evidence for the implementation of innovative leprosy screening methods and chemoprophylaxis to policymakers., Trial Registration Number: NL7294 (NTR7503)., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Introduction: It is acknowledged that longer delays between first symptoms and diagnosis result in increased impairment in newly detected leprosy patients. However, it is unclear whether detection delay in relation to impairment can be used as a general or absolute performance indicator of leprosy control programmes. It is unknown whether similar delays always result in similar proportions of impairment. Therefore, the present study examined the quantitative relationship between delay and impairment in two different patient populations., Methods: Patients from two study cohorts (BANDS and AMFES) who reported voluntarily were included in the analysis. Data on detection delay, WHO impairment status, type of leprosy, age and sex were analysed using descriptive statistics and multivariate logistic regression analysis to identify significant risk factors for impairment and to quantify the relationship between detection delay and impairment status at intake., Results: Detection delay was an independent risk factor for impairment at presentation in multivariate analysis. The AMFES cohort reported more impairment at detection than BANDS. In multivariate analysis, this difference was significant among PB patients (51% in AMFES versus 15% in BANDS), but not in MB patients (56% in AMFES versus 45% in BANDS). In fact, for every delay category PB patients from AMFES had much higher proportions of impairment than PB BANDS patients. Impairment rates in MB patients from AMFES were higher in every delay category, but the differences between the two cohorts were much smaller compared to PB patients., Conclusions: Our analysis confirms earlier findings that with longer delays, the risk of impairment at presentation increases. With the same reported delay, however, the proportion impaired can vary considerably between different patient populations, in particular for PB leprosy. Delay can therefore not simply be used as a general or absolute performance indicator for programme evaluation. Achieving short delays remains important in general, but understanding and addressing the underlying mechanisms of delay specific to a patient population adds substantially to the effectiveness of leprosy control.