INTRODUCTION

Nepal has long been a leprosy-endemic country and continues to be recognized as one of the global priority countries for targeted leprosy control activities [1]. While the elimination status of leprosy (1 case per 10,000 population) has been obtained in Nepal since 2009, there continue to be some areas in the country with a higher prevalence rate than the WHO elimination level guidelines [2]. Sixteen districts in Nepal have a reported prevalence rate (PR) greater than 1, while many other districts are just under a PR of 1 [3]. New case detection rates (per 100,000 population) have also increased from seven (2020/21 AD) to nine (2022/23 BS) and the national PR level is 0.8, which is barely below the elimination rate [4].

The continued identification of severe forms of leprosy, along with the increasing rate of G2D cases in Nepal, points to a persistent delay in diagnosis [5]. There is a tendency for delayed health-seeking behavior among people in the rural hill regions of Nepal, with a reported delay of up to 29.8 months after the onset of symptoms [6]. The extended period between becoming contagious and receiving active treatment provides ample opportunity for transmission, greatly impeding the country’s efforts to eliminate leprosy.

Leprosy is a chronic infectious disease with the primary risk for contraction being prolonged close contact with an untreated, infectious person [7]. Passive case detection and multi-drug therapy (MDT) alone have not been enough to stop leprosy transmission. To effectively prevent transmission, more proactive case detection strategies and contact tracing are needed. A large consortium of experts has established and trialed essential data collection for contact tracing in multiple countries [1,8]. Early case detection and limited contact tracing coverage remain key challenges for the Nepal Leprosy Control Program [2].

The Global Partnership for Zero Leprosy highlights that leprosy tends to be concentrated in specific areas (hot spots) rather than isolated cases. They recommend using leprosy mapping and spatial analysis (i.e., using data to locate the prominent or pocket areas of leprosy) to identify high-risk areas and guide targeted interventions [9]. The Department of Health Services Nepal (DoHS) annual report for several years has recommended strengthening early case detection by focusing on pocket areas of high endemic areas, but it has not been widely implemented in control programs. Challenges include inaccurate reporting and underreporting of cases (per DoHS), as well as difficulties accessing past data to pinpoint these areas [2].

Dadeldhura district has hosted the main leprosy diagnoses and treatment facilities in the Far West Hill areas for over sixty years and remains crucial for leprosy work in the region (Fig. 1). Long-term records have been maintained, yet there has been minimal focus on contact tracing or active case finding. Identifying high-risk (pocket) areas could enable community-level case finding, helping improve detection rates, early treatment, and understanding of the region’s leprosy situation, especially in remote and difficult-to-reach areas.

Figure 1: Map of Nepal showing the region covered in the leprosy case data collection, with the green area highlighting Dadeldhura district.

MATERIALS AND METHODS

Approval of the proposed research study and protocols was obtained from the Centre for International Relations, Tribhuvan University and the Nepal Health Research Council (Reg. No 262/2021). Updates and good standing were maintained during the study period from April 2021 to April 2024.

A retrospective compilation of data was initiated with the approval of the Dadeldhura Hospital in Amarghadi 5, Dadeldhura, Far West Province. Registers and records for diagnosed and treated leprosy patients had been maintained, from which the data was gathered. All newly diagnosed leprosy patients from April 14, 2010, to April 14, 2021 (ten years), were included in the data. Data, including name, age, sex, complete address, date of entry, type of leprosy, disability grading, and ending status, was collected, and descriptive statistics were applied. Only de-identified data was used for research purposes. However, the totality of the data was shared with the Leprosy Program Supervisor from Dadeldhura Hospital, who initially provided the records/registers. All other privacy of the data was maintained among the research team.

Because of the change in administrative addresses during the time frame of the data, old addresses (under the Village Development Committee) were transcribed into the current administrative addresses (Wards, Municipalities) using the briefing document produced by the Nepalese government. When all address data had been transcribed, location data was compiled to locate which areas had larger amounts of leprosy patients, which could denote the pocket areas.

Specific wards with more than four cases were noted, and villages with multiple cases each were also identified. The research team then consulted and chose one of these village pocket areas to use for the second contact tracing phase of the research.

For the second phase, a protocol was established for a house-to-house, village-level survey. This included informed consent, age and sex information, general health survey questions that could potentially identify leprosy signs and symptoms, and a system for referral for full leprosy screening of any potential suspects identified.

Preliminary visits were made to the survey area, including consultation and seeking permission from the local health post, local ward office, village volunteer health workers (VHW), and village leaders. The survey was then conducted over three days in November 2023. The survey team included three health workers who had had significant training and experience with leprosy. Assistance was given by three local VHWs to help in obtaining access to the village residents. The residents and VHWs were informed that it was a “general health survey” with no reference to leprosy to maintain privacy and avoid stigma. Survey forms were filled, and a notation was made of any referrals and reasons for such. Data was collected through house-to-house surveys and interviews with attendees of meetings conducted for the survey.

General non-identifiable data was compiled for those surveyed, and any potential leprosy suspects and/or previously treated leprosy patients were identified. Suspects were also given a referral paper to the Dadeldhura Hospital for examination, and their names and phone numbers were forwarded to the Leprosy Program Supervisor for potential follow-up of their case. No other data was shared outside of the research team.

RESULTS

Data was collected from the hospital records for 224 patients over ten years. The patients came from the seven districts in the Far West Province’s hill areas and some from the Terai region or India (Table 1). The latter were recorded but not factored into the analysis for pocket areas. The number of cases was also identified by the municipality. There were cases from all the districts, but the largest number were from Dadeldhura District (n = 52).

Table 1: Distribution of the leprosy cases by district and municipality (Palika).

The leprosy cases presenting at the hospital included 200 (89.4%) multibacillary (MB) cases, 17 (7.5%) paucibacillary (PB) cases and 7 (3.1%) restart cases. Among the study population, 140 (63%) were male and 84 (37%) were females. The cases were also classified by age group and disability grading (Tables 2 and 3). The mean age was 45.4 years. Only 2.7% of the cases were children and the highest number of the cases overall (56%) were sixty years old and older. The majority of those with disability had G2D, as seen in 103 (46%) of the cases. Only one of the children had G2D.

	Table 2: Distribution of the leprosy cases by age group.
	Table 3: Distribution of leprosy by disability grade.

An analysis conducted to identify areas with higher concentrations of leprosy cases, revealing potential “pocket areas” for targeted intervention revealed Ajaimeru, Ward 5 of Dadeldhura District to have the maximum number of leprosy cases per ward, which was 8 (3.57%), and Daulardi, Sigash, Ward 2 of Baitadi District to have highest cases within any village (n = 5; 2.23%). Together, three villages were designated as key pocket areas (Tables 4 and 5).

	Table 4: Wards with four or more cases of leprosy.
	Table 5: Case distribution by village (key pocket areas).

The village of Daulardi, the largest in Ward No. 2 (Sigash Rural Municipality, Baitadi District) was chosen to do the village-level contact tracing survey. Inquiries about population brought a wide variety of answers, ranging from 1,800 to 2,500 people. The three VHWs assigned to the village shared their data of a total of 180 households and a population of 1148. However, during the survey, an additional 25 households were also represented, with an additional 123 people currently reported in the household. In their data, the VHWs reported 49.7% females and 50.4% males. Surveys were completed for 185 people from 84 different households. Participants included 109 (59%) females and 76 (41%) males. Of the 185 surveyed, four possible suspects and one suspect were identified. Two released-from-treatment (RFT) cases were among the participants. One of the cases was not part of the original data from the hospital. It was known that one case was deceased, and another two (from one family) had migrated away from the area.

Among other issues, many cases of preventable skin issues (for example, scabies), a large number of vision-related problems, some nutritional deficiencies, and a significant number of people with complaints of neurological issues post-disease or trauma, were also noted.

DISCUSSION

This study revealed a significantly varied distribution of leprosy cases across different geographical areas in Far West Nepal. The high number of cases in Dadeldhura District, along with the three identified pocket-area villages, which are located near the hospital, indicates that improved health-seeking behaviors may be associated with better access to healthcare. This easier accessibility likely motivates more people in these areas to pursue diagnosis and treatment, leading to increased case detection. The case distribution by the clinical type (WHO classification) found in this study was comparable to the national data of Nepal, which was 73.5% MB and 34% PB among the new cases [2].

In our survey, only about a third of the cases were female, which aligned with the new national diagnosis rate for females (36.63% in 2020/21) and the global rate (39.7% in 2022) [2,10]. This consistent trend of fewer female diagnoses may suggest potential barriers to healthcare access for women. Similar to the findings of this survey, the detection rate of new child cases in Nepal was 4.65% in 2014, which mirrored the global rate of 4.65% in 2022 [2,10]. However, considering the data spanned ten years, underdiagnosis of new child cases in Nepal’s rural Far West region should be suspected.

In our study, a significant 46% of the cases had G2D. In contrast, Nepal reported only 4.37% of new cases with G2D in 2020, and globally, 6.3% of new cases had G2D in 2022 [2,10]. Although the overall number of new cases decreased in later years, the percentage of G2D cases remained high, especially in 2017–2019. This suggests that many individuals are living with untreated deformities, and a significant number develop new G2D, likely due to delays in diagnosis. This also points to the possibility of hidden cases in Nepal’s Far West Hill areas.

The study successfully identified three villages as “pocket areas” for leprosy cases in the region. Similar studies in India and China have also highlighted pocket areas or hot spots where leprosy transmission remains significantly higher than the average [11,12]. This pattern is also observed in Nepal, where certain provinces, such as Madesh and Lumbini, show higher prevalence rates [3]. During active contact tracing, four possible suspects and one confirmed suspect were identified out of the 185 individuals in this study. An active case detection study in Lamkichuha Municipality, Kailali district, Nepal (examining 21,471 people from 4,526 families) identified 195 suspect cases and three confirmed new cases [13]. Similarly, a study in a hotspot district of Ethiopia showed a significant increase in the new detection rate (from 28.3/100,000 to 48.3/100,000) after implementing active case detection and household contact tracing, emphasizing the effectiveness of focusing on specific pocket areas for active case detection [14].

The contact tracing survey was conducted within Sigash Rural Municipality, which had a population of 23,479 according to the 2021 census, comprising 11,153 males and 12,326 females across 3,435 families [15]. Census data for Ward 2 or Daulardi Village was unavailable locally or online. According to the 2011 census, 74% of the population was of Chettri caste, 42% were children aged 0–14, and 5.8% were absent from their households (living outside the area during the census) [16]. Despite the large potential study population, accessibility issues, misconceptions, reluctance to participate, miscommunication, and sociocultural stigmatization of leprosy limited the survey, resulting in only about 25% of the population being included. The study was also limited in that, although some pocket areas were identified, it likely did not capture all leprosy cases in the region, as many cases were probably diagnosed outside the Dadeldhura Hospital and were missing from the dataset.

CONCLUSION

This study highlighted the ongoing challenge of leprosy in Nepal, particularly in the Far West region, where certain areas, identified as pocket areas, have higher concentrations of cases. The findings underscored the importance of proactive case detection strategies, such as contact tracing, to improve early diagnosis and treatment. Active case detection in targeted areas had proven effective in identifying new cases, suggesting that focusing on these high-risk areas could significantly enhance leprosy control efforts in Nepal.