Leprosy Case Detection Research Articles

Exploring Active Case Detection Approaches for Leprosy Diagnosis in Varied Endemic Settings: A Comprehensive Scoping Review.

(1) Background: The global burden of leprosy is not shared equally; with the majority of cases being diagnosed in Brazil, India, and Indonesia. Understanding the methods of active case detection (ACD) used in high and low endemic regions is vital for the development of future screening programs. (2) Methods: A systematic search of three databases, PubMed, Embase and Web of Science, was conducted for English language papers, published since the year 2000, which discussed the use of active case detection methods for leprosy screening. The paper utilised the Integrated Screening Action Model (I-SAM) as a tool for the analysis of these methods. (3) Results: 23 papers were identified from 11 different countries. The papers identified 6 different methods of active case detection: Household contact/social contact identification; door-to-door case detection; screening questionnaire distribution; rapid village surveys; school-based screening; and prison-based screening. 15 were located in high endemic regions and 8 of these were located in low endemic regions. (4) Conclusions: For selecting the appropriate methods of active case finding, the leprosy endemicity must be taken into consideration. The findings contribute to policy decision making allowing for more successful future leprosy case detection programs to be designed, ultimately reducing the global burden of the disease, and achieving the WHO's aim of zero leprosy.

Training and Active Case Detection to Prevent Leprosy: Effect on Knowledge, Attitude and Skills of Health Workers on Early Diagnosis of Leprosy in a Leprosy Hotspot District in Ethiopia.

Despite all of the efforts, leprosy continues to affect hundreds of thousands of people every year, including children, showing the ongoing transmission of the disease within the population. The transmission of leprosy can be interrupted through an integrated approach that includes active case-finding, contact tracing and capacity building of health workers. A cross-sectional study design was used to assess the knowledge, attitudes and skills of health workers in the screening and diagnosis of leprosy. One hundred and eighty-one and eighty-eight health care workers participated in the pre-and post-assessment surveys, respectively. Data were collected through interviews and an observational checklist. Frequency tables and graphs were used to describe the study variables, and statistical significance between pre- and post-assessment surveys was declared at p-value < 0.5. The percentages of healthcare workers with good knowledge, positive attitudes and skills were 61.2%, 55.6% and 51.7% in the pre-assessment survey and 77.3%, 56.3% and 75.0%, respectively, in the post-assessment survey. There was a significant improvement in the knowledge and skill scores of participants in the post-assessment survey (p < 0.01). During the campaign, 3780 index contacts were screened; 570 (15.1%) were diagnosed with skin diseases, and 17 new leprosy cases were diagnosed (case detection rate of 45 per 10,000 contacts). Training improved the knowledge and skills of healthcare workers, and a large number of skin diseases were detected through mass screening and active case findings. Providing training for frontline healthcare workers contributed to the detection of more cases and facilitated early detection of leprosy cases.

Temporal trends and spatial analysis of leprosy surveillance indicators in the municipalities of the state of Mato Grosso, 2008-2022.

In 2022, Mato Grosso (MT, Brazil) reported the highest detection rate of new leprosy cases (66.20 per 100,000 inhabitants) among all Brazilian states. Monitoring of leprosy indicators is an important control strategy in hyperendemic areas. We aimed to describe the temporal trends and identify clusters of municipalities according to leprosy surveillance indicators in MT between 2008 and 2022. Data from the Notifiable Diseases Information System were used to analyze new case detection rate of leprosy (NCDR), new case detection rate of leprosy among children aged <15 years (NCD15), and rate of new cases with grade 2 physical disability (G2DR). Spatial scan statistics with pure spatial analysis and spatial autocorrelation maps were used to analyze the spatial patterns. Joinpoint regression was used to estimate the annual percentage change (APC) in these indicators. The NCDR decreased (APC: -20.2%, 95% confidence interval (CI): -38.7% to -7.4%) between 2019 and 2021. The NCD15 also decreased (APC: -19.2%, 95% CI: -36.4% to -10.3%) between 2018 and 2022. Conversely, the G2DR remained stable throughout the study (APC: 3.2%, 95% CI: -0.1% to 6.7%). Global Moran's index (Moran's I) confirmed the existence of spatial dependence among the municipalities for NCDR (Moran's I=0.348), NCD15 (Moran's I=0.269), and G2DR (Moran's I=0.275). Clusters with high NCDR levels included 13 municipalities in the northern and eastern macroregions, while clusters with high G2DR levels included 12 municipalities in the northwestern, northern, and eastern macroregions. The NCDR and NCD15 decreased, but the G2DR remained stable between 2018 and 2022. The coronavirus disease 2019 (COVID-19) pandemic had a potential negative impact on leprosy case detection, highlighting the need to strengthen leprosy surveillance efforts. The identified clusters of MT municipalities can significantly assist in this task.

Challenges Experienced and Observed during the Implementation of Leprosy Strategies, Sidama Region, Southern Ethiopia: An inductive thematic analysis of qualitative study among health professionals who working with leprosy programs.

Prompt diagnosis and treatment of leprosy are crucial for preventing the disease's spread as well as for avoiding negative medical and social effects and reducing the disease's burden. The likelihood of nerve damage and subsequent disability rises as the length of the diagnostic delay. We aimed to explore the challenges of health professionals faced regarding their involvement in early leprosy case detection strategies. The study employed a qualitative, descriptive and phenomenological explorative research design to answer the research questions. By the use of non-probability purposive sampling, research participants were identified. During the study, in-depth interviews were conducted to gather information regarding the experiences of health workers (medical doctors, public health officers, clinical nurses, health centre heads and regional and Woreda district health office technical and programme experts) and health extension workers. To analyse the qualitative data, inductive thematic analysis techniques were used. For analysis, open code software version 4.0 was used. The data transcription, coding, display, reduction (theme) and interpretation of the discovered results were the processes undertaken for the analysis. The findings of the study revealed that leprosy prevention and control programmes are still problematic. Themes that emerged from the data gleaned from the health workers included: lack of the existence of practice-oriented training, Integration of TB and leprosy training, lack of focus or other competing health priorities, Inadequate supportive supervision of health facilities, Multiple tasks for health workers, poor coordination and communications, lack of motivation in health workers, disruption in treatment, and Importance of training related to leprosy. Strengthening comprehensive leprosy training for health workers, carrying out efficient and thorough contact tracing, enhancing monitoring, supervision, assessment and surveillance, boosting managerial skills, lobbying political commitment, and motivating healthcare workers may help in early detection of leprosy cases strategies.

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

BackgroundLeprosy 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.MethodCommunity-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.ResultsThe 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.ConclusionCDD 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.

Usefulness of outreach clinics on active case detection of leprosy in a high endemic area in Sri Lanka

Though Sri Lanka reports low endemicity and a lesser number of cases detected annually, leprosy patients below 14 years of age are rising. Therefore, active case finding is essential. A skin clinic was conducted in the District Hospital (DH), Lunawa of Colombo District where higher numbers of cases had been reported in the past. The people were alerted on the clinic through public health staff to identify new cases. Out of the 54 persons who attended the clinic, one was clinically diagnosed as having multibacillary leprosy and another subsequently detected among the five suspected patients who were referred for skin biopsy, giving a yield of active case finding of 0.37 per 10 000 persons screened (95% CI: 0.45, 1.26). This high yield of the disease indicates that active case finding is a possible strategy for high endemic areas, which could be enhanced with a combination of outreach programs like household surveys or awareness on leprosy at institutions like schools.

The collaboration of ‘Active case finding campaign’ with the \'Leprosy case detection campaign\': An important step towards tuberculosis elimination

The collaboration of ‘Active case finding campaign’ with the \'Leprosy case detection campaign\': An important step towards tuberculosis elimination

Reaching those at risk: Active case detection of leprosy and contact tracing at Kokosa, a hot spot district in Ethiopia.

Leprosy is a chronic mycobacterial disease of public health importance. It is one of the leading causes of permanent physical disability. The prevalence of leprosy in Ethiopia has remained stagnant over the last decades. The aim of the study was to identify new leprosy cases and trace household contacts at risk of developing leprosy by active case detection. The study area was Kokosa district, West Arsi zone, Oromia region, Ethiopia. A prospective longitudinal study was conducted from June 2016-September 2018 at Kokosa district. Ethical approvals were obtained from all relevant institutions. Health extension workers screened households by house-to-house visits. Blood samples were collected and the level of anti-PGL-I IgM measured at two-time points. More than 183,000 people living in Kokosa district were screened. Dermatologists and clinical nurses with special training on leprosy confirmed the new cases, and their household contacts were included in the study. Of the 91 new cases diagnosed and started treatment, 71 were recruited into our study. Sixty-two percent were males and 80.3% were multibacillary cases. A family history of leprosy was found in 29.6% of the patients with cohabitation ranging from 10 to 30 years. Eight new leprosy cases were diagnosed among the 308 household contacts and put on multi-drug therapy. The New Case Detection Rate increased from 28.3/100,000 to 48.3/100,000 between 2015/2016 and 2016/2017. Seventy one percent of leprosy patients and 81% of the household contacts' level of anti-PGL-I IgM decreased after treatment. In conclusion,the results of the study showed the importance of active case detection and household contact tracing. It enhances early case finding, and promotes early treatment, thereby interrupting transmission and preventing potential disability from leprosy.

The leprosy case detection delay (CDD) questionnaire: Indonesian translation, cross-cultural adaptation, and evaluation

The leprosy case detection delay (CDD) questionnaire: Indonesian translation, cross-cultural adaptation, and evaluation

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

BackgroundLeprosy 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.MethodsTwo 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.ResultsFor 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.ConclusionsThe 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.Graphical

Clinico-Epidemiological profile of new leprosy cases detected in leprosy case detection campaign in North Maharashtra during 2018-2020.

Leprosy is a leading cause of disability in India. The percentage of disability and deformity can be reduced by diagnosing leprosy at an early stage. In order to detect the hidden leprosy cases, leprosy case detection campaigns, on line with Pulse Polio Campaign have been introduced specifically for high endemic districts, by the Central Leprosy Division. Records of cases from 2018 to 2020 were evaluated retrospectively to study the trend of new cases. The present study denotes the presence of hidden undiagnosed cases in the community and will require an intensification of leprosy control activities through contact tracing and active case detection. Continued quality surveillance is required for early detection, timely management, and prevention of the spread of the disease.

Analysis of socioeconomic condition and bacillary index with respect to the development of Hansen's disease.

Leprosy is a chronic granulomatous infection caused by Mycobacterium leprae or Mycobacterium lepromatosis and mainly affects the skin and peripheral nerves. Although treatable, its early intervention can significantly reduce the occurrence of disability. India accounts for more than half of new cases globally. This study was undertaken to better understand the clinical traits of newly diagnosed cases in a tertiary facility of Western Uttar Pradesh, and a few from Madhya Pradesh and Uttarakhand. The observational prospective study was carried out on all the newly diagnosed leprosy cases who visited the Outpatient Department of ICMR-National JALMA Institute for Leprosy and Other Mycobacterial Diseases, Agra, during October 2019-December 2022. After obtaining answers to a prestructured questionnaire with their consent, participants were enrolled in the study and underwent clinical examination and a slit-skin smear test. A total of 56 cases were investigated, and among them, 20 (35.7%) and 36 (64.3%) women and men, respectively, had positive contact with persons affected by leprosy either within family, friends, or neighbors. It is observed that due to the delayed detection of leprosy cases, paucibacillary (PB) patients converted into multibacillary (MB) patients, and the number of MB cases is much higher compared to PB cases. Leprosy instances continue to spread frequently from sick to healthy people indicating continued transmission of leprosy in society. Multidrug therapy in the management of leprosy cases is effective; however, early diagnosis of PB cases is still a challenge and needs to be addressed on priority.

Treinamento em hanseníase por simulação: construção e validação de cenário a agentes comunitários de saúde

ABSTRACT Objectives: To build and validate a clinical simulation scenario designed to instruct community health workers (CHWs) in active leprosy case detection. Methods: Methodological study involving the development of a simulated clinical scenario and content validation by experts. The Content Validity Index (CVI) was used to determine the level of agreement among the judging commitee, and a descriptive analysis of their recommendations was performed. Results: A simulated scenario with a simulated participant was developed — a simulation characterized by low complexity, moderate physical/environmental fidelity, moderate to high psychological fidelity, and high conceptual fidelity, lasting 50 minutes and capable of training up to 10 CHWs simultaneously. The scenario was validated by 14 experts, with a CVI exceeding 80% for all components. Conclusions: The validated clinical simulation possesses attributes that make it highly reproducible in various national health contexts, thereby contributing to the global “Towards Zero Leprosy” strategy.

Lipid biomarkerek HPLC-HRMS vizsgálata történeti embertani minták tbc diagnosztikája során

Tuberculosis (TB) is not only an infectious disease but one of the top 10 causes of death, spreading mainly with aerosol transmission and accompanying the history of humankind for several millennia. TB is caused in humans and animals by members of the Mycobacterium tuberculosis complex. For better understanding of the disease and the evolutional background of its causative agent, involvement of palaeopathological investigations is surpassingly important. Traditionally, palaeopathology is using a broad variety of markers, which are observable by macroscopic investigations. These markers are mainly related to different extra-pulmonary forms of TB. However, these manifestations develop only in a few cases. Moreover, many markers are not pathognomonic of TB. Therefore, to avoid underestimation of TB prevalence in paleopathological studies, the diagnosis on archaeological material requires a multidisciplinary approach. For better estimation of TB incidence in past populations, an array of specific biomarkers can be brought into play to confirm initial, macromorphology-based skeletal diagnoses, namely aDNA and lipid biomarkers. The three lipid biomarker groups, which are mainly involved in such investigations are the mycolic acids (MAs), the mycocerosic acids (MCs) and the C27 mycolipenic acid (ML). These unique lipids can be located in the lipid-rich mycobacterial cell wall. The application of lipid-based TB diagnostic approach has been proved to be robust and reliable through many examples. A variety of analytical methods have been employed for mycobacterial lipid biomarker profiling. Fluorescence HPLC is well-developed for the analysis of mycolic acids and phthiocerols. Furthermore, one isolated case of direct mass spectrometric detection of M. tuberculosis free mycolic acids has been also introduced. Our aim was to establish a lipid-biomarker-based HPLC-MS method for TB diagnosis in historical human samples, as this instrumentation is available in many laboratories, has the potential of a quick and sensitive and at the same time an affordable measurement protocol. We successfully developed and optimised a method, which is capable to separate and detect MAs and MCs. Moreover, we optimised the sample pre-treatment process. We started to build an MA and MC lipid profile library, which can serve as a comparison to diagnose TB. For the verification of new methods and the estimation of reliability of new markers in macroscopic analysis, palaeopathologists usually use well-documented collections of skeletons and mummies from the pre-antibiotic era. For this purpose, we chose to test our method on the Vác Mummy Collection. In the case of four out of six mummified individuals, MC profiles of characteristic M. tuberculosis MCs were recorded. The HPLC-ESI-MS method, developed for the detection of MCs, opens a new avenue for the detection of ancient mycobacterial disease, encompassing both tuberculosis, leprosy and joint cases.

Trends and geographical variation in leprosy case detection and disability in Nepal, 2010–2021

Objective Although elimination of leprosy was achieved in Nepal at national level in 2009, around 3000 new cases are still detected every year and 5% of these cases have Grade 2 disability (G2D). This study aims to describe the geographical distribution of leprosy new case detection (NCD) and G2D from 2010 to 2021 in two leprosy endemic provinces in Nepal. Methods We collected the geolocations and leprosy-related data of patients registered from 2010 to 2021 in Provinces 1 and 7. The geographical distribution of NCD and G2D was analysed in Quantum Geographic Information Systems (QGIS) at district, municipality and ward level, and we calculated the trends in Eye Hand Foot (EHF) impairment scores among cases with disabilities. Results From 2010 to 2021, a decrease in NCD and G2D cases was identified in Province 1, and an increase in NCD and G2D cases in Province 7. Geographical variations were visible between wards within highly endemic districts in both provinces. The mean EHF score in cases with disability increased from 1.7 in 2017 to 2.5 in 2020 in Province 1 and fluctuated between 2.3 and 4.5 in Province 7. Conclusions This study shows that the leprosy problem is still current in Nepal. Geographic variations in case detection and disability indicators are seen best when mapping at ward level. Leprosy programme managers can use the maps to develop long-term strategies at district, municipality or ward level that include intensified active case finding, preventive treatment and disability services, while considering costs and efficient use of resources.

Economic evaluation of a leprosy innovation project in Northern Nigeria: cost-effectiveness analysis

BackgroundThe state of leprosy in Nigeria and the realities of post elimination era underscore the need for evidence- based cost-effective approach to early case detection for enhanced control and elimination of leprosy. This study evaluated the operational cost-effectiveness of a community delivered Legacy Innovative Project implemented to enhance leprosy case detection in northern Nigeria.MethodsData were collected from an explorative cross-sectional study, undertaken in a practice setting among endemic communities in three states in northern Nigeria. Primary and secondary data were collected from the project, routine records and programme annual reports. Costs and effects were measured from both providers’ and patients’ perspectives, and outcome expressed as cost per new case detected. Incremental estimates of costs and effects of the project compared to routine practice were used to obtain the cost-effectiveness result, as incremental cost-effectiveness ratio (ICER). All costs were converted to the US Dollar at 2018exchange rate (N350 = US$1.00). Univariate sensitivity analysis was performed to evaluate uncertainties around the ICER.ResultsThe Project overall detected a total of 347 newly confirmed leprosy cases at a total annual cost of US$49,337.19, averaging US$142.18 per new case detected. Key cost drivers included routine meetings, which accounted for 28% of total expenditure, while Social Mobilization and Training/Workshop accounted for17% respectively. Findings were similar across the states. Overall, the Project dominated routine practice with ICER of US$(-17.73) per additional/new case detected, as a very cost-effective strategy. Sensitivity analysis reinforced the cost-effectiveness result.ConclusionsThe Legacy Innovative Project demonstrated a more efficient and cost-saving approach to leprosy case detection. Findings present important information to policy and programmes for enhanced control and elimination of leprosy in related settings..

Social Determinants and Leprosy in High Endemic Regions of Myanmar: an Ecological Study between 2016 and 2019

Leprosy has been a public health problem in Myanmar for many centuries. This study aims to explore the situation of leprosy and the association between leprosy and social determinants at the township level in seven endemic regions in Myanmar. The objectives of the study are to (i) describe the incidence and severity of leprosy and the disability due to leprosy in Myanmar between 2016 and 2019, and (ii) determine the correlation between leprosy incidence and social determinants in Myanmar in 2019. We used annual surveillance data of leprosy cases between 2016 and 2019 from the National Leprosy Control Program, Myanmar, and social determinant variables from the 2019 General Administration Department Census Report of Myanmar. An ecological cross-sectional study was conducted. Univariable and multivariable analyses applying zero-inflated negative binomial regression models were used. A geographic information system mapping was used to visualize leprosy cases, disease severity, and disability due to leprosy between 2016 and 2019. The number of all leprosy indicators changing pattern was seen obvious between regions. The eastern region showed relatively an increase in detection of new cases in 2019 compared with years 2017 and 2018. The increase in the detection of multibacillary leprosy cases was also observed in the eastern region during this period. Yet, the detection of Grade-II disability cases across regions remained relatively stable throughout study years. The number of tuberculosis cases per 1,000 population was significantly correlated with leprosy incidence at the township level (risk ratio 1.27, 95% confidence interval 1.04–1.55). These findings highlight the importance of enhancing active case finding campaigns in high-endemic regions, especially the eastern states of Myanmar. Integration of leprosy and tuberculosis case-finding programmes is likely to help leverage resources and maximize efforts to cope with leprosy problems in Myanmar.

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

BackgroundLeprosy 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.MethodsThis 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.FindingsThe 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.ConclusionsBeing 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.

Delayed detection of leprosy cases: A systematic review of healthcare-related factors.

In new leprosy cases, grade 2 disability (G2D) is still a public health burden worldwide. It is often associated with the delayed leprosy diagnoses that healthcare systems should play a crucial role in preventing. The aim of this systematic review was to identify healthcare factors related to delays in case detection in leprosy. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) was used as a guideline in this research. The study protocol was registered in the PROSPERO (International Prospective Register of Systematic Reviews) with reference code CRD42020189274. Data was collected from five electronic databases: Embase, Medline All Ovid, Web of Science, Cochrane CENTRAL, and the WHO Global Health Library. After applying the selection criteria for original empirical studies, and after removing duplicates, we included 20 papers from 4313 records. They had been conducted in ten countries and published between January 1, 2000, and January 31, 2021. We identified three categories of healthcare factors related to delayed case. 1) Structural factors, such as i) financial and logistic issues, and geographical circumstances (which we classified as barriers); ii) Health service organization and management including the level of decentralization (classified as facilitators). 2) Health service factors, such as problems or shortages involving referral centers, healthcare personnel, and case-detection methods. 3) Intermediate factors, such as misdiagnosis, higher numbers of consultations before diagnosis, and inappropriate healthcare services visited by people with leprosy. Delays in leprosy case detection are due mainly to misdiagnosis. It is crucial to improve the training and capacity of healthcare staff. To avoid misdiagnosis and reduce detection delays, national leprosy control programs should ensure the sustainability of leprosy control within integrated health services.

Epidemiological trends of leprosy and case detection delay in East Hararghe Zone, Ethiopia: A baseline survey

Objectives Leprosy is a chronic infectious disease caused by Mycobacterium leprae and one of the world’s most neglected tropical diseases. The post-exposure prophylaxis for leprosy study (PEP4LEP) compares two integrated skin-screening approaches combined with single dose rifampicin administration to contacts of leprosy patients. The aim of this baseline survey was to describe the epidemiological trends of leprosy and estimate case detection delay in the Ethiopian study districts before the start of the intervention. Methods The study was conducted in three districts of East Hararghe zone, Oromia Region, Ethiopia. We applied descriptive retrospective study design to describe epidemiological trends of leprosy between 2010 and 2019. Fifty patients diagnosed in the six months prior to their inclusion in the study were interviewed to establish the case detection delay at baseline. The healthcare delivery system and National Leprosy Control Program are also described. Results Trends in the number of new leprosy patients detected decreased slightly over the past ten years, although the number of new child cases increased overall, suggesting ongoing transmission. The mean case detection delay was 22.4 months (95% CI: 18.6–26.3), while the median was 19.5 months. The mean patient and health system delay were 19.6 months (95% CI: 15.8–23.4) and 2.6 months (95% CI: 1.5–3.6), respectively. Conclusion Considerable leprosy case detection delays were found in the PEP4LEP study districts in Ethiopia. Efforts to reduce delay and interrupt the transmission should focus on integrating prevention and active case finding, contact tracing and providing post-exposure prophylaxis to contacts of leprosy patients.