In 2020, American Leprosy Missions partnered with Novartis to offer a $20,000 prize and a $15,000 prize. We received fifty abstracts from 19 countries, yielding the five finalists below. The finalists’ projects were introduced and awards announced during the virtual NTD NGO Network Conference, September 8-10, 2020.
Read about the 2020 winners here.
2020 Finalists and Proposals
Dr. Arie de Kruijff, Dr. Suwash Baral and Dr. Deanna Hagge - The Leprosy Mission
Professor Janis Spigulis - University of Latvia, Institute of Atomic Physics and Spectroscopy - Latvia
Proposal: Applying spectral imaging to leprosy diagnosis.
Although an effective cure for leprosy is available, a major bottleneck for control programs is early and accurate diagnosis and classification. A field-friendly tool is needed to assess suspect leprosy lesions with rapid and accurate results. Building on similar work done for skin melanoma, this project will find spectral chromophore patterns of skin affected by leprosy in comparison with healthy skin of the same person. The spectral data will be correlated to clinical diagnosis, classification and biopsy data from the same lesions. The identified sensitive spectral bands associated with leprosy will further be used to design and assemble a specific cellphone add-on and spectral image processing software to establish the sensitivity and specificity of such a mobile instrument. Applied to leprosy, this would allow for field staff to have a cost-effective hand-held device to be used to screen suspect lesions and receive either a definite diagnosis or a probability-score factor.
Laura Braun and Kai Reimer - Imperial College London - United Kingdom
Proposal: Capta: An automated diagnostic tool for detecting parasitic worm infections. View video here.
Parasitic worm infections (soil-transmitted helminths and schistosomiasis) are a major health burden in humans and livestock. Early diagnosis can prevent significant health damage, but current diagnostic tools are labor intensive, lack quality control or require expensive equipment. The aim of Capta is to develop a smart, automated diagnostic tool for all parasitic worm infections. This consists of a portable digital microscope that connects to any smart device. The application uses image recognition to identify different worm eggs, allowing for a quick and accurate diagnosis. Capta could therefore enable more targeted drug distribution and help reduce the burden of disease.
Monica Staniek - Liverpool School of Tropical Medicine - United Kingdom
Proposal: Tracking a sandfly: Evaluating light-weight molecular tagging (SmartWater®) as a novel insect marking technique. View video here.
Leishmaniasis is the world’s most important NTD, resulting in 70,000 deaths reported yearly. Technologies targeting parasite-transmitting female sandflies are critical tools for leishmaniasis control programs. Although insecticide spraying has successfully reduced cases of leishmaniasis in India and Bangladesh, in some regions, particularly Brazil, sandflies are learning to avoid insecticide-treated areas (behavioral resistance) and dispersing to untreated ones. As the current techniques used to mark and track sandflies for targeted control interventions are too heavy or toxic for sandflies, new marking strategies are needed to understand flight behavior and sandfly dispersal patterns. A forensic marking technology, SmartWater®, has recently been repurposed for insect monitoring. This cost-effective technique uses a robust form of light-weight nanotechnology to label insects with a fluorescent tag. This study will assess the flight behavior and survival of SmartWater®-treated, insectary-reared Brazilian sandflies. This could lead to rapid improvements in existing insect control strategies and ultimately help in the reduction of the leishmaniasis burden in Brazil.
Arnauld Efon Ekangouo and Dr. Hugues Nana Djeunga - Centre for Research on Filariasis and other Tropical Diseases - Cameroon
Proposal: Cell-free DNA: A promising biomarker for onchocerciasis elimination mapping? View video here.
Onchocerciasis diagnosis remains a challenge for monitoring and evaluating the performance of control programs. Molecular diagnostic tools could be a viable alternative to current tools, such as microscopic examination of skin biopsies, which significantly lose sensitivity especially after multiple rounds of mass drug administration, remain invasive and present some risks of blood-borne infections. However, molecular assays are expensive and time-consuming. This study seeks to explore the potential of an innovative diagnostic approach based on molecular detection of O. volvulus cell-free DNA (cfDNA) in saliva and urine. In standard molecular diagnostic, DNA extraction accounts for half of the costs and three- quarters of performing time. The key point of this solution is the “cell-free” nature of targeted DNA. This trait involves the suppression of the “DNA extraction” process, resulting in direct amplification-detection of the target, thus leading to substantial time-saving and cost affordability.
Marcelo Tavora Mira - Pontifical Catholic University of Parana - Brazil
Proposal: Prediction of the occurrence of leprosy reactions based on Bayesian networks. View video here.
Leprosy reversal reactions (LRR) are episodes of extreme immune response activation that require immediate diagnosis and treatment. Intense basic and clinical research has led to the identification of several clinical and molecular risk factors for the occurrence of LRR; however, means for systematic combination of these data in a system applicable in disease control programs are still limited. This project uses artificial intelligence and Bayesian network methods that are capable of predicting the risk of leprosy patients to develop LRR, integrating clinical, demographic and genetic data. Initial results are promising; the challenge now is to implement the system as an open-access, easy-to-use tool for healthcare professionals, in order to (i) provide a system capable of identifying newly diagnosed patients with leprosy and at risk of developing LRR as candidates for priority monitoring, and (ii) prospectively validate our results in different populations.