The potential role of artificial intelligence in the clinical management of Hansen's disease (leprosy).

Missed and delayed diagnoses of Hansen's disease (HD) are making the battle against it even more complex, increasing its transmission and significantly impacting those affected and their families. This strains public health systems and raises the risk of lifelong impairments and disabilities. Worryingly, the three countries most affected by HD witnessed a growth in new cases in 2022, jeopardizing the World Health Organization's targets to interrupt transmission. Artificial intelligence (AI) can help address these challenges by offering the potential for rapid case detection, customized treatment, and solutions for accessibility challenges-especially in regions with a shortage of trained healthcare professionals. This perspective article explores how AI can significantly impact the clinical management of HD, focusing on therapeutic strategies. AI can help classify cases, ensure multidrug therapy compliance, monitor geographical treatment coverage, and detect adverse drug reactions and antimicrobial resistance. In addition, AI can assist in the early detection of nerve damage, which aids in disability prevention and planning rehabilitation. Incorporating AI into mental health counseling is also a promising contribution to combating the stigma associated with HD. By revolutionizing therapeutic approaches, AI offers a holistic solution to reduce the burden of HD and improve patient outcomes.

The current status of neglected tropical diseases in Japan: A scoping review.

Little attention has been paid to neglected tropical diseases (NTDs) in high-income countries and no literature provides an overview of NTDs in Japan. This scoping review aims to synthesize the latest evidence and information to understand epidemiology of and public health response to NTDs in Japan. Using three academic databases, we retrieved articles that mentioned NTDs in Japan, written in English or Japanese, and published between 2010 and 2020. Websites of key public health institutions and medical societies were also explored. From these sources of information, we extracted data that were relevant to answering our research questions. Our findings revealed the transmission of alveolar echinococcosis, Buruli ulcer, Chagas disease, dengue, foodborne trematodiases, mycetoma, scabies, and soil-transmitted helminthiasis as well as occurrence of snakebites within Japan. Other NTDs, such as chikungunya, cystic echinococcosis, cysticercosis, leishmaniasis, leprosy, lymphatic filariasis, rabies, and schistosomiasis, have been imported into the country. Government agencies tend to organize surveillance and control programs only for the NTDs targeted by the Infectious Disease Control Law, namely, echinococcosis, rabies, dengue, and chikungunya. At least one laboratory offers diagnostic testing for each NTD except for dracunculiasis, human African trypanosomiasis, onchocerciasis, and yaws. No medicine is approved for treatment of Chagas disease and fascioliasis and only off-label use drugs are available for cysticercosis, opisthorchiasis, human African trypanosomiasis, onchocerciasis, schistosomiasis, and yaws. Based on these findings, we developed disease-specific recommendations. In addition, three policy issues are discussed, such as lack of legal frameworks to organize responses to some NTDs, overreliance on researchers to procure some NTD products, and unaffordability of unapproved NTD medicines. Japan should recognize the presence of NTDs within the country and need to address them as a national effort. The implications of our findings extend beyond Japan, emphasizing the need to study, recognize, and address NTDs even in high-income countries.

An mHealth App (eSkinHealth) for Detecting and Managing Skin Diseases in Resource-Limited Settings: Mixed Methods Pilot Study.

BACKGROUND: In sub-Saharan Africa, the disease burden from skin diseases, including skin-related neglected tropical diseases (skin NTDs), is extremely high. These diseases often are overlooked due to limited access to health care stemming from, for example, remote geographical locations and a lack of experts. To address these gaps, we developed a mobile health app, eSkinHealth, which is a field-adapted platform to serve as a portable electronic patient chart and for teledermatology. OBJECTIVE: The purpose of the study is to evaluate the usability and effectiveness of the app in rural Côte d'Ivoire for diagnosing and managing skin NTDs and other skin diseases. METHODS: A 2-arm trial with local health care providers and patients with skin diseases was implemented over a 3-month period. The providers were assigned to an intervention receiving the eSkinHealth app or control with usual care. Four nurses and 8 community health care workers participated in each arm. The training was provided on the use of the app to the intervention arm only, while both arms were trained on skin diseases. For the usability study, we evaluated our approach with the System Usability Scale (SUS) and in-depth interviews. For the effectiveness study, our primary outcome was to evaluate the detection and management of 5 skin NTDs as our targeted diseases, namely, Buruli ulcer, leprosy, lymphatic filariasis, scabies, and yaws, using the eSkinHealth app. Procedures of our methods were reviewed and approved by the institutional review board of the Ministry of Health and by Tulane University. RESULTS: The mean age of our participants (providers) was 40.5 and 42.5 years for the intervention and control arms, respectively, and all were male (n=24). The average SUS scores taken from the intervention arm at baseline, the midpoint (6 weeks), and the end of study (12 weeks) were 72.3 (SD 11.5), 72.3 (SD 12.4), and 86.3 (SD 10.8), respectively. All participants interviewed, including 4 dermatologists and program managers, were satisfied with the app. Especially community health care workers felt empowered by being equipped with the tool. A total of 79 cases of skin NTDs were reported in the intervention arm as compared to 17 cases in the control arm (P=.002). Besides the skin NTDs, more skin diseases and conditions were reported from the control than from the intervention arm (P<.001). However, 100 cases (66%) were not given any particular diagnosis in the control arm and were documented only as a "dermatosis." In the intervention arm, 151 cases (72.9%) were diagnosed within the eSkinHealth platform, and the remaining were diagnosed on-site by dermatologists. CONCLUSIONS: The study provided evidence for the usability and effectiveness of the eSkinHealth app embedded into our surveillance approach to improve the detection and management of skin NTDs and other skin diseases in Côte d'Ivoire and, furthermore, is expected to contribute to knowledge on mobile health approaches in the control of skin diseases in resource-limited settings. TRIAL REGISTRATION: ClinicalTrials.gov NCT05300399; https://clinicaltrials.gov/ct2/show/NCT05300399.

Deep learning for AI-based diagnosis of skin-related neglected tropical diseases: A pilot study.

BACKGROUND: Deep learning, which is a part of a broader concept of artificial intelligence (AI) and/or machine learning has achieved remarkable success in vision tasks. While there is growing interest in the use of this technology in diagnostic support for skin-related neglected tropical diseases (skin NTDs), there have been limited studies in this area and fewer focused on dark skin. In this study, we aimed to develop deep learning based AI models with clinical images we collected for five skin NTDs, namely, Buruli ulcer, leprosy, mycetoma, scabies, and yaws, to understand how diagnostic accuracy can or cannot be improved using different models and training patterns. METHODOLOGY: This study used photographs collected prospectively in Côte d'Ivoire and Ghana through our ongoing studies with use of digital health tools for clinical data documentation and for teledermatology. Our dataset included a total of 1,709 images from 506 patients. Two convolutional neural networks, ResNet-50 and VGG-16 models were adopted to examine the performance of different deep learning architectures and validate their feasibility in diagnosis of the targeted skin NTDs. PRINCIPAL FINDINGS: The two models were able to correctly predict over 70% of the diagnoses, and there was a consistent performance improvement with more training samples. The ResNet-50 model performed better than the VGG-16 model. A model trained with PCR confirmed cases of Buruli ulcer yielded 1-3% increase in prediction accuracy across all diseases, except, for mycetoma, over a model which training sets included unconfirmed cases. CONCLUSIONS: Our approach was to have the deep learning model distinguish between multiple pathologies simultaneously-which is close to real-world practice. The more images used for training, the more accurate the diagnosis became. The percentages of correct diagnosis increased with PCR-positive cases of Buruli ulcer. This demonstrated that it may be better to input images from the more accurately diagnosed cases in the training models also for achieving better accuracy in the generated AI models. However, the increase was marginal which may be an indication that the accuracy of clinical diagnosis alone is reliable to an extent for Buruli ulcer. Diagnostic tests also have their flaws, and they are not always reliable. One hope for AI is that it will objectively resolve this gap between diagnostic tests and clinical diagnoses with the addition of another tool. While there are still challenges to be overcome, there is a potential for AI to address the unmet needs where access to medical care is limited, like for those affected by skin NTDs.

A global call for action to tackle skin-related neglected tropical diseases (skin NTDs) through integration: An ambitious step change.

On 8 June 2022, the World Health Organization (WHO) released pivotal guidance, "Ending the neglect to attain the Sustainable Development Goals: A strategic framework for integrated control and management of skin-related neglected tropical diseases." Skin-related neglected tropical diseases, or skin NTDs, comprise a group of NTDs that produce signs and symptoms on the skin and include at least 9 diseases or disease groups. Moving away from disease-specific approaches, it is anticipated that synergies will be identified and integrated building on this shared feature, where possible, to achieve a greater health impact. This paper intends to draw attention to the prospects created by this scheme. The framework is a key basis for a proposal produced by WHO dedicated to skin NTD integration and describes the practical opportunities for this evolving strategy. It underlines the wider health benefits that will follow, thus working towards Universal Health Coverage and skin health for all.

Deep learning for AI-based diagnosis of skin-related neglected tropical diseases: a pilot study.

Background: Deep learning, which is a part of a broader concept of artificial intelligence (AI) and/or machine learning has achieved remarkable success in vision tasks. While there is growing interest in the use of this technology in diagnostic support for skin-related neglected tropical diseases (skin NTDs), there have been limited studies in this area and fewer focused on dark skin. In this study, we aimed to develop deep learning based AI models with clinical images we collected for five skin NTDs, namely, Buruli ulcer, leprosy, mycetoma, scabies, and yaws, to understand how diagnostic accuracy can or cannot be improved using different models and training patterns. Methodology: This study used photographs collected prospectively in Côte d'Ivoire and Ghana through our ongoing studies with use of digital health tools for clinical data documentation and for teledermatology. Our dataset included a total of 1,709 images from 506 patients. Two convolutional neural networks, ResNet-50 and VGG-16 models were adopted to examine the performance of different deep learning architectures and validate their feasibility in diagnosis of the targeted skin NTDs. Principal findings: The two models were able to correctly predict over 70% of the diagnoses, and there was a consistent performance improvement with more training samples. The ResNet-50 model performed better than the VGG-16 model. Model trained with PCR confirmed cases of Buruli ulcer yielded 1-3% increase in prediction accuracy over training sets including unconfirmed cases. Conclusions: Our approach was to have the deep learning model distinguish between multiple pathologies simultaneously - which is close to real-world practice. The more images used for training, the more accurate the diagnosis became. The percentages of correct diagnosis increased with PCR-positive cases of Buruli ulcer. This demonstrated that it may be better to input images from the more accurately diagnosed cases in the training models also for achieving better accuracy in the generated AI models. However, the increase was marginal which may be an indication that the accuracy of clinical diagnosis alone is reliable to an extent for Buruli ulcer. Diagnostic tests also have its flaws, and they are not always reliable. One hope for AI is that it will objectively resolve this gap between diagnostic tests and clinical diagnoses with addition of another tool. While there are still challenges to be overcome, there is a potential for AI to address the unmet needs where access to medical care is limited, like for those affected by skin NTDs. AUTHOR SUMMARY: The diagnosis of skin diseases depends in large part, though not exclusively on visual inspection. The diagnosis and management of these diseases is thus particularly amenable to teledermatology approaches. The widespread availability of cell phone technology and electronic information transfer provides new potential for access to health care in low-income countries, yet there are limited efforts targeting these neglected populations with dark skin and consequently limited availability of tools. In this study, we leveraged a collection of skin images gathered through a system of teledermatology in the West African countries of Côte d'Ivoire and Ghana, and applied deep learning, a form of artificial intelligence (AI) - to see if deep learning models can distinguish between different diseases and support their diagnosis. Skin-related neglected tropical diseases, or skin NTDs, prevail in these regions and were our target conditions: Buruli ulcer, leprosy, mycetoma, scabies, and yaws. The accuracy of prediction depended on the number of images that were fed into the model for training with marginal improvement using laboratory confirmed cases in training. Using more images and greater efforts in this area, it is possible that AI can help address the unmet needs where access to medical care is limited.

Hansen's disease (leprosy) in Japan, 1947-2020: an epidemiologic study during the declining phase to elimination.

OBJECTIVES: Leprosy, or Hansen's disease was a major public health problem in Japan in the early 20th century. Today, the number of new cases has decreased significantly. We aimed to investigate the trends of leprosy in Japan over the past 73 years and the challenges faced in recent years. METHODS: We assessed the data on newly registered cases of leprosy from 1947 to 2020. RESULTS: A total of 10,796 newly registered cases of leprosy were reported during the study period, of which 7573 were registered in mainland Japan, 2962 in Okinawa, and 250 were of foreign origin. Most autochthonous cases were born before 1950 in mainland Japan and before 1975 in Okinawa. The number of nonautochthonous cases surpassed that of autochthonous cases in 1992. Nonautochthonous cases originated from 26 countries, particularly Brazil and the Philippines. Three cases of antimicrobial resistance have been detected among nonautochthonous cases since 2004. CONCLUSION: Our data suggest that ongoing transmission of leprosy likely ceased in the 1940s in mainland Japan and in the 1970s in Okinawa. With the recent rise of nonautochthonous cases with globalization, continuous surveillance and efforts to maintain leprosy services within the country are necessary even after reaching the state of elimination.

The Early Detection and Case Management of Skin Diseases With an mHealth App (eSkinHealth): Protocol for a Mixed Methods Pilot Study in Côte d'Ivoire.

BACKGROUND: There is a high prevalence of skin diseases sub-Saharan Africa, including skin neglected tropical diseases (NTDs) that could lead to lifelong disabilities and deformities if not diagnosed and treated early. To achieve early detection and early treatment of these skin diseases, we developed a mobile health app, eSkinHealth. OBJECTIVE: This paper outlines a protocol for evaluating the effect of our eSkinHealth app in the early detection and effective management of skin diseases in Côte d'Ivoire. METHODS: A mixed methods pilot trial will be conducted in Côte d'Ivoire and will consist of 3 phases: (1) the development and improvement of the eSkinHealth app, (2) a pilot trial to evaluate the usability of the eSkinHealth app for local medical staff in Côte d'Ivoire, and (3) a pilot trial to evaluate the effectiveness of early detection and case management of targeted skin NTDs (Buruli ulcer, leprosy, yaws, and lymphatic filariasis) with the eSkinHealth app in Côte d'Ivoire. The pilot study will be implemented as a 2-arm trial with local health care providers and patients with skin NTDs over a 3-month follow-up period. The local health care providers will be assigned to an intervention group receiving the eSkinHealth app to be used in their daily practices or a control group. Training will be provided on the use and implementation of the app and the diagnostic pipeline to the intervention group only, while both groups will receive training on skin diseases. Our primary outcome is to evaluate the early detection and effective management of skin diseases using the eSkinHealth app in Côte d'Ivoire by the number of cases diagnosed and managed. Additionally, we will evaluate the eSkinHealth app with validated questionnaires and in-depth interviews. Procedures of our methods have been reviewed and approved by the Institutional Review Board of the Ministry of Health, Côte d'Ivoire and by Tulane University in 2021. RESULTS: This study was funded in 2021. We started the enrollment of patients in February 2022, and data collection is currently underway. We expect the first results to be submitted for publication in 2023. CONCLUSIONS: Our eSkinHealth app is a field-adapted platform that could provide both direct diagnostic and management assistance to health workers in remote settings. The study will provide evidence for the usability and the effectiveness of the eSkinHealth app to improve the early detection and case management of skin NTDs in Côte d'Ivoire and, furthermore, is expected to contribute to knowledge on mobile health approaches in the control of skin NTDs. TRIAL REGISTRATION: ClinicalTrials.gov NCT05300399; https://clinicaltrials.gov/ct2/show/study/NCT05300399. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39867.

Nutritional status and wound healing in patients with Mycobacterium ulcerans disease (Buruli ulcer): a pilot study from rural Côte d'Ivoire

Background: Buruli ulcer (BU) is a neglected tropical disease caused by Mycobacterium ulcerans which manifests as deep ulceration of the skin. Wounds from any cause heal slowly if individuals are malnourished. Objectives: To assess the impact of nutritional status on wound healing, we carried out a nutritional assessment of 11 patients diagnosed with BU in rural Côte d'Ivoire, and followed them longitudinally through the wound healing process. Materials & Methods: We conducted patient interviews to collect data on their socioeconomic characteristics, food intake and perception of nutrition. We then prospectively carried out clinical observations to assess their wound healing until complete healing or the end of the study period (median follow-up period: 19 weeks). Results: The age of the patients ranged from 6 to 66 years (median: 24; interquartile range: 20.5-52). Nine patients had normal nutritional status, one had mild malnutrition and one had moderate malnutrition as assessed by their body mass index and/or mid-upper arm circumference. Three (60%) of the five patients with adequate caloric intake, but only 1/6 (17%) of the patients with an inadequate caloric intake achieved complete healing during follow-up. Low food intake from appetite loss primarily due to wound pain and odour was reported by seven patients after developing wounds. Conclusion: Our study is the first of its kind, and the findings highlight the importance of integrating nutritional interventions into wound management protocols, and properly assessing and controlling wound pain in patients with BU.

Evaluation of the Usability of a Mobile Application on Neglected Skin Diseases in Côte d'Ivoire: A Pilot Study.

This study investigated the usability of a mobile phone-based system, "eSkinHealth", for healthcare providers in Côte d'Ivoire. The eSkinHealth can be used both online and offline to address the poor Internet connectivity of these rural settings. Data recorded in the mobile application were synchronized with an online database, and specialists in Abidjan, Côte d'Ivoire and in Japan advised local healthcare providers on difficult cases. In this pilot study, 21 healthcare providers used the eSkinHealth and completed questionnaires assessing the usability. The average score of a system usability scale for eSkinHealth was 84.2 (SD 11.7), which can be interpreted as excellent. The average registration for patient information (e.g., name, sex, age, area of residence) was 8.6 (SD 15.5). Further studies with more targeted areas and participants are needed to evaluate the usability of eSkinHealth in rural Côte d'Ivoire.

Methods and Approaches for Buruli Ulcer Surveillance in Africa: Lessons Learnt and Future Directions.

Over 95% of the global burden of Buruli ulcer disease (BU) caused by Mycobacterium ulcerans occurs in equatorial Africa. National and sub-national programs have implemented various approaches to improve detection and reporting of incident cases over recent decades. Regional incidence rates are currently in decline; however, surveillance targets outlined in 2012 by WHO have been missed and detection bias may contribute to these trends. In light of the new 2030 NTD roadmap and disease-specific targets, BU programs are required to strengthen case detection and begin a transition towards integration with other skin-NTDs. This transition comes with new opportunities to enhance existing BU surveillance systems and develop novel approaches for implementation and evaluation.In this review, we present a breakdown and assessment of the methods and approaches that have been the pillars of BU surveillance systems in Africa: (1) Passive case detection, (2) Data systems, (3) Clinical training, (4) Active case finding, (5) Burden estimation, and (6) Laboratory confirmation pathways. We discuss successes, challenges, and relevant case studies before highlighting opportunities for future development and evaluation including novel data collection tools, risk-based surveillance, and integrated skin-NTD surveillance. We draw on both experience and available literature to critically evaluate methods of BU surveillance in Africa and highlight new approaches to help achieve 2030 roadmap targets.

A framework for scabies control.

Scabies is a neglected tropical disease (NTD) that causes a significant health burden, particularly in disadvantaged communities and where there is overcrowding. There is emerging evidence that ivermectin-based mass drug administration (MDA) can reduce the prevalence of scabies in some settings, but evidence remains limited, and there are no formal guidelines to inform control efforts. An informal World Health Organization (WHO) consultation was organized to find agreement on strategies for global control. The consultation resulted in a framework for scabies control and recommendations for mapping of disease burden, delivery of interventions, and establishing monitoring and evaluation. Key operational research priorities were identified. This framework will allow countries to set control targets for scabies as part of national NTD strategic plans and develop control strategies using MDA for high-prevalence regions and outbreak situations. As further evidence and experience are collected and strategies are refined over time, formal guidelines can be developed. The control of scabies and the reduction of the health burden of scabies and associated conditions will be vital to achieving the targets set in WHO Roadmap for NTDs for 2021 to 2030 and the Sustainable Development Goals.

Efficacy of chemoprophylaxis and immunoprophylaxis in leprosy prevention: a systematic review and network meta-analysis of randomized controlled trials.

BACKGROUND: Vaccination and single-dose rifampin are the main proven effective intervention types for preventing leprosy among contacts of Mycobacterium leprae endemic areas. Currently, no high-quality evidence is available regarding the best prophylactic intervention. OBJECTIVES: Our primary study aim is to detect the most effective prophylactic intervention for the prevention of leprosy. METHODS: In May 2019, 12 databases were searched systematically. Updated search terms were developed in March 2020 to complete an updated search. All randomized controlled trials (RCTs) comparing the different types of chemoprophylactic and immunoprophylactic interventions in leprosy prevention were included. Our participants were contacts of patients with leprosy or people residing in leprosy endemic communities. We searched for different types of chemoprophylactic and immunoprophylactic interventions used in leprosy prevention. We used network meta-analysis and meta-analysis. Quality assessment was performed using Cochrane Risk of Bias for included RCTs, in which all included RCTs were rated to be low to moderate risk. We registered our protocol in Prospero with ID CRD42019143207. RESULTS: Among 11 included studies (326 264 patients) from original and updated search terms, eight were eligible for network meta-analysis (NMA) while four were eligible for MA. Findings suggest that Bacillus Calmette-Guérin (BCG) vaccination was the most effective intervention compared to placebo (risk ratios (RRs) 0.49 (0.30, 0.80), p 0.77), followed by combined BCG vaccination and single-dose rifampicin (SDR) with similarly low values (RR 48%, p 0.77). BCG revaccination was the least effective intervention compared to placebo (RR 1.08 (0.36, 3.22), p 0.26). CONCLUSION: Compared to placebo, the BCG vaccine was the most effective prophylactic intervention. The combination of BCG vaccination + SDR had nearly the same efficacy as BCG vaccination alone, while BCG revaccination was the least effective. Thus, vaccination proved to be a more effective treatment than SDR alone. A well-designed multicenter RCT is warranted to evaluate the safety of these vaccines.

Tinea Capitis Caused by Microsporum audouninii: A Report of Two Cases from Côte D'Ivoire, West Africa.

We report here two cases of tinea capitis caused by Microsporum (M.) audouinii in Côte d'Ivoire, West Africa. The patients were a three-year-old boy and a six-year-old girl who presented with scaly patches on the scalp. The causative fungus was isolated using an adhesive tape-sampling method and cultured on Sabouraud dextrose agar plates. It was identified as M. audouinii both by its macroscopic and microscopic features, confirmed by DNA sequencing. These are the first documented cases of M. audouinii infections confirmed with DNA sequencing to be reported from Côte d'Ivoire. The practicality of the tape-sampling method makes it possible to carry out epidemiological surveys evaluating the distribution of these dermatophytic infections in remote, resource-limited settings.