Determining target populations for leprosy prophylactic interventions: a hotspot analysis in Indonesia

Taal, Anneke T.; Blok, David J.; Handito, Agus; Wibowo, Satrio; Sumarsono, Sumarsono; Wardana, Ariq kusuna; Pontororing, Gysje J.; Sarı, Dilek; Brakel, Wim H. van; Richardus, Jan Hendrik; Prakoeswa, Cita Rosita Sigit

doi:10.1186/s12879-022-07103-0

Cited by 8 publications

(6 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…There are experiences of effective interventions related to the active detection of cases based on the selection and training of local personnel in areas that are difficult to access [ 46 ]. Likewise, there are also those based on innovative technologies to identify “hot spots” (areas with a high density of cases) [ 47 , 48 ] or to predict new cases from household contacts [ 49 ]. Therefore, in order to ensure universal healthcare coverage for people affected by leprosy living in remote areas, effective evidence-based interventions involving community participation would be necessary.…”

Section: Discussionmentioning

confidence: 99%

Community intervention programmes with people affected by leprosy: Listening to the voice of professionals

2022

View full text Add to dashboard Cite

Background Community participation and implementing interventions based on the community are key strategies to eliminate leprosy. Health professionals have an essential role as they are a necessary source of information because of their knowledge and experience, as well as their comprehensive perspective of contexts included in the programmes. This study has the aim of analysing the perceptions on the development of programmes with people affected by leprosy from the perspective of professionals that work at different organisations in endemic contexts. Methodology A qualitative study was carried out with the written response to an open question questionnaire which was sent by email. The script content was related to positive aspects and difficulties in daily work, participation from the community in activities, contribution to gender equality and programme sustainability. 27 health professionals were interviewed, 14 women and 13 men, all of which belonged to 16 organisations in India and Brazil. Once the content of the interviews was analysed, two main topics emerged: barriers perceived by professionals and proposals to improve the sustainability of the programmes. Principal finding Professionals identify barriers related to social stigma, inequalities, gender inequalities, difficulty managing the disease, limited services, lack of resources and lack of community participation. Furthermore, some necessary recommendations were taken into account to improve programme development related to: Eliminating stigma, reaching gender equality, developing adequate and effective services, guaranteeing adequate and quality resources and achieving compassion among professionals. Conclusions Although introducing community programmes with people affected by leprosy has a long history in countries such as India and Brazil, there are still several barriers that can hinder their development. Based on the specific needs of the contexts, recommendations are suggested that, with the involvement of all parties and with sensitive approaches towards human rights and gender, they could help to guarantee universal health coverage and the sustainability of said programmes.

show abstract

Section: Discussionmentioning

confidence: 99%

Community intervention programmes with people affected by leprosy: Listening to the voice of professionals

2022

View full text Add to dashboard Cite

show abstract

“…3 Indonesia has the highest prevalence of leprosy in the world, with approximately 15,000 new cases reported each year. 4,5 Although effective treatment has been available since 1960, early detection of the illness is still the most e cacious means of preventing the spread of the disease and reducing the possibility of delayed diagnoses and the resulting disabilities. 6,7 Early diagnosis is essential as leprosy presents with a diverse range of clinical and histopathological manifestations resulting from the host's varying degrees of cellular immune response to M. leprae.…”

Section: Introductionmentioning

confidence: 99%

Utilization of Mice as Hansen Disease Models for Comprehensive Analysis of Pathogenesis, Immunological Responses, and Therapeutic Interventions: A Systematic Review Protocol

Prakoeswa,

Asaduddin,

Pramuningtyas

et al. 2023

Preprint

View full text Add to dashboard Cite

Leprosy is resulted from chronic infection by Mycobacterium leprae. Leprosy affects the skin, peripheral nerves, and upper respiratory tract. Leprosy is a global health concern and Indonesia has the highest prevalence of leprosy in the world. The disease is characterized by a cytokine response, which is associated with increased inflammatory activity in both limited and multibacillary forms. Therefore, in vitro and in vivo studies are necessary to understand the disease and develop more effective treatments. This systematic search was conducted in several international databases including Scopus, PubMed, ScienceDirect, and Epistemonikos. A search strategy that combined keywords based on Medical Subject Headings (MeSH) and free text, including mice, leprosis, bacterial examination and histopathology. The search was performed using a systematic search strategy. We performed data extraction independently using predefined sheets that included the following information: first author name, year of publication, sample size and characteristics, duration of follow up, exposure method, intervention grouping, and outcomes (bacterial examination, histopathological evaluation, and other inflammatory markers). The results of the risk of bias assessment were displayed in the form of traffic-light plot and summary plot graphs, illustrating the results of a low, high, or unclear risk of biased assessment. The data was analyzed qualitatively.

show abstract

“…With Kulldorff's Spatial and Space Time Scan Statistics (SaTScan) [20], a space-time local clustering technique that can adjust for heterogeneous background population densities and confounding variables [21], the most likely cluster(s) of disease are identified controlled for gender, age, type of leprosy and deformity, and over a period of time [22][23][24]. Non-statistical spatial methods such as the Kernel Density Estimation which estimates the probability density function of a random variable, are applied to visualize clusters or so-called hotspots of disease and disability [14,25,26].…”

Section: Introductionmentioning

confidence: 99%

Identifying clusters of leprosy patients in India: A comparison of methods

et al. 2022

View full text Add to dashboard Cite

Background Preventive interventions with post-exposure prophylaxis (PEP) are needed in leprosy high-endemic areas to interrupt the transmission of Mycobacterium leprae. Program managers intend to use Geographic Information Systems (GIS) to target preventive interventions considering efficient use of public health resources. Statistical GIS analyses are commonly used to identify clusters of disease without accounting for the local context. Therefore, we propose a contextualized spatial approach that includes expert consultation to identify clusters and compare it with a standard statistical approach. Methodology/Principal findings We included all leprosy patients registered from 2014 to 2020 at the Health Centers in Fatehpur and Chandauli districts, Uttar Pradesh State, India (n = 3,855). Our contextualized spatial approach included expert consultation determining criteria and definition for the identification of clusters using Density Based Spatial Clustering Algorithm with Noise, followed by creating cluster maps considering natural boundaries and the local context. We compared this approach with the commonly used Anselin Local Moran’s I statistic to identify high-risk villages. In the contextualized approach, 374 clusters were identified in Chandauli and 512 in Fatehpur. In total, 75% and 57% of all cases were captured by the identified clusters in Chandauli and Fatehpur, respectively. If 100 individuals per case were targeted for PEP, 33% and 11% of the total cluster population would receive PEP, respectively. In the statistical approach, more clusters in Chandauli and fewer clusters in Fatehpur (508 and 193) and lower proportions of cases in clusters (66% and 43%) were identified, and lower proportions of population targeted for PEP was calculated compared to the contextualized approach (11% and 11%). Conclusion A contextualized spatial approach could identify clusters in high-endemic districts more precisely than a standard statistical approach. Therefore, it can be a useful alternative to detect preventive intervention targets in high-endemic areas.

show abstract

Determining target populations for leprosy prophylactic interventions: a hotspot analysis in Indonesia

Cited by 8 publications

References 32 publications

Community intervention programmes with people affected by leprosy: Listening to the voice of professionals

Community intervention programmes with people affected by leprosy: Listening to the voice of professionals

Utilization of Mice as Hansen Disease Models for Comprehensive Analysis of Pathogenesis, Immunological Responses, and Therapeutic Interventions: A Systematic Review Protocol

Identifying clusters of leprosy patients in India: A comparison of methods

Contact Info

Product

Resources

About