PEP4LEP study protocol: integrated skin screening and SDR-PEP administration for leprosy prevention: comparing the effectiveness and feasibility of a community-based intervention to a health centre-based intervention in Ethiopia, Mozambique and Tanzania

Mshana S, Richardus JH, Kasang C, Mieras L. Case detection delay in leprosy: Testing tool reliability and measurement consistency in Ethiopia, Mozambique, and Tanzania

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.

TRIAL REGISTRATION

This trial is registered with The Netherlands Trial Register (NTR), now available via International Clinical Trial Registry Platform (ICTRP) with registration number NL7294 (NTR7503), as well as with The Pan African Clinical Trials Registry (PACTR) with registration number PACTR202303742093429.

Measuring leprosy case detection delay and associated factors in Indonesia: a community-based study

BACKGROUND

Leprosy is a public health burden in Indonesia with a high number of new cases every year and a high proportion of disability among new cases. Case detection delay (CDD) can contribute to ongoing transmission and increased disability chances among leprosy patients. This study aimed to establish the CDD of leprosy and the factors associated with detection delay in Indonesia.

METHOD

Community-based study with a cross-sectional design. Data were collected through interviews about sociodemographic and behavioral factors, anticipated stigma, and duration of CDD. Leprosy classification and case detection methods were obtained from health service records. A random sample was taken of 126 leprosy patients registered between 1st October 2020 and 31st March 2022 in the Tegal regency in the Central Java Province. Data were analysed by descriptive and analytical statistics using multiple linear regression.

RESULTS

The mean CDD, patient delay, and health system delay were 13.0 months, 9.7 months, and 3.2 months, respectively. Factors associated with longer CDD are younger age (below 35 years), male, found through passive case detection, and not having a family member with leprosy. Factors associated with longer patient delay were being younger (below 35 years), being male, not having a family member with leprosy, and anticipated stigma of leprosy. It was not possible to reliably identify factors associated with health system delay.

CONCLUSION

CDD in leprosy should be reduced in Indonesia. The Indonesian National Leprosy Control Program (NLCP) is advised to adopt an integrated intervention programme combining active case detection with targeted health education to reduce CDD and thereby preventing disabilities in people affected by leprosy.

Establishing a standard method for analysing case detection delay in leprosy using a Bayesian modelling approach

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.

Implementation approaches for leprosy prevention with single-dose rifampicin: A support tool for decision making

Background

In the past 15 years, the decline in annually detected leprosy patients has stagnated. To reduce the transmission of Mycobacterium leprae, the World Health Organization recommends single-dose rifampicin (SDR) as post-exposure prophylaxis (PEP) for contacts of leprosy patients. Various approaches to administer SDR-PEP have been piloted. However, requirements and criteria to select the most suitable approach were missing. The aims of this study were to develop an evidence-informed decision tool to support leprosy programme managers in selecting an SDR-PEP implementation approach, and to assess its user-friendliness among stakeholders without SDR-PEP experience.

Methodology

The development process comprised two phases. First, a draft tool was developed based on a literature review and semi-structured interviews with experts from various countries, organisations and institutes. This led to: an overview of existing SDR-PEP approaches and their characteristics; understanding the requirements and best circumstances for these approaches; and, identification of relevant criteria to select an approach. In the second phase the tool’s usability and applicability was assessed, through interviews and a focus group discussion with intended, inexperienced users; leprosy programme managers and non-governmental organization (NGO) staff.

Principal findings

Five SDR-PEP implementation approaches were identified. The levels of endemicity and stigma, and the accessibility of an area were identified as most relevant criteria to select an approach. There was an information gap on cost-effectiveness, while successful implementation depends on availability of resources. Five basic requirements, irrespective of the approach, were identified: stakeholder support; availability of medication; compliant health system; trained health staff; and health education. Two added benefits of the tool were identified: its potential value for advocacy and for training.

Conclusion

An evidence-informed SDR-PEP decision tool to support the selection of implementation approaches for leprosy prevention was developed. While the tool was evaluated by potential users, more research is needed to further improve the tool, especially health-economic studies, to ensure efficient and cost-effective implementation of SDR-PEP.

The chance of contacts of leprosy patients developing leprosy can be reduced by providing a single dose of rifampicin. The implementation of this type of post-exposure prophylaxis can be done in various ways. This study led to the development of the SDR-PEP decision support tool to select the most suitable approach. It was developed in two phases; first, a tool was drafted based on a literature review and expert interviews, this was followed by phase 2 in which interviews and a focus group discussion with intended users of the tool were held. Five SDR-PEP implementation approaches that have been developed so far were identified. Apart from the characteristics of these approaches, the tool lists five basic requirements for the successful implementation of any approach, and criteria that help to select the best approach in a given context. A flowchart supports the selection process. The study found that the tool can also be used for lobby and advocacy, to clarify SDR-PEP implementation and the choice for an approach, and in training on SDR-PEP implementation. Information about costs and cost-effectiveness of the approaches is limited. Further research will help to continue to improve the tool.

Prolonged delays in leprosy case detection in a leprosy hot spot setting in Eastern Ethiopia

Background

Leprosy or Hansen’s disease is known to cause disability and disfigurement. A delay in case detection of leprosy patients can lead to severe outcomes. In Ethiopia, the disability rates caused by leprosy among new cases are relatively high compared to other endemic countries. This suggests the existence of hidden leprosy cases in the community and a delay in timely detection. To reduce disability rates, it is crucial to identify the factors associated with this delay. This study aimed to determine the extent of delay in case detection among leprosy cases in Eastern Ethiopia.

Methods

This cross-sectional explorative study was conducted in January and February 2019 among 100 leprosy patients diagnosed ≤6 months prior to inclusion. A structured questionnaire was used to collect data, including the initial onset of symptoms, and the reasons for delayed diagnosis. Descriptive statistics, including percentages and medians, were used to describe the case detection delay. Logistic regression analysis was carried out to evaluate the predictors of delay in case detection of >12 months.

Findings

The median age of patients was 35 years, with a range of 7 to 72 years. The majority were male (80%) and rural residents (90%). The median delay in case detection was 12 months (interquartile range 10–36 months) among the included patients. The mean delay in case detection was 22 months, with a maximum delay of 96 months. The overall prevalence of disability among the study population was 42% (12% grade I and 30% grade II). Fear of stigma (p = 0.018) and experiencing painless symptoms (p = 0.018) were highly associated with a delay in case detection of >12 months.

Conclusions

Being afraid of stigma and having painless symptoms, which are often misinterpreted as non-alarming at the onset of the disease, were associated with a delay in case detection. This study showed the need to increase knowledge on early symptoms of leprosy among affected communities. Furthermore, it is important to support initiatives that reduce leprosy related stigma and promote health worker training in leprosy control activities.

Leprosy, also called Hansen’s disease, is a chronic infectious disease that may result in devastating disabilities. The disability rate among new leprosy patients in Ethiopia is high compared to other countries. A delay in case detection is a major factor contributing to the development of disability. Late diagnosis also fosters ongoing transmission, increasing the incidence of the disease. We aimed to determine the extent of the detection delay and find the reasons for this delay in eastern Ethiopian districts, endemic for leprosy. One hundred leprosy patients who recently started multi-drug therapy were included in the study. The median detection delay was one year among all patients. About half of the patients had sought treatment from health institutions within one year after the onset of their first symptoms. Longer delays among leprosy patients were associated with a fear of stigma and painless symptoms at an early stage of the disease. This indicates that it is vital to improve community knowledge of leprosy symptoms and to take initiatives that reduce stigma. This should improve health-seeking behaviour and may prevent the development of disability as well as halt transmission.

Advances in the Diagnosis of Leprosy

Leprosy is a public health issue, and early detection is critical to avert disability. Despite the global attempt to eradicate this disease as a public health problem, it remains an important cause of global neurological disability. India, Brazil and Indonesia share more than 70% of the cases. The reduction of new cases is a priority in the WHO global strategy 2021-2030 which aims to reduce disease transmission in the community by diagnosing cases and identifying subclinical infection. The clinical manifestations of leprosy range from a few to several lesions. The identification remains difficult due to the limited sensitivity of traditional approaches based on bacillary counts of skin smears and histology. To aid in the diagnosis of this disease, molecular biology, and biotechnological technologies have been applied, each with its own set of benefits and downsides despite providing an essential tool to validate the clinical diagnosis of leprosy. Because of this, it is strongly recognized that specific, inexpensive point of care technologies should be developed, particularly to identify asymptomatic M. leprae infections or leprosy nearer to the suspected cases seeking medical attention. Thus, this review will provide an overview of the advancements in leprosy diagnosis over the world. The purpose of this review is to improve our understanding of the outcomes of current tests and technologies used in leprosy diagnosis and to emphasize critical aspects concerning the detection of leprosy bacilli.