01901nas a2200133   4500000000100000008004100001260004200042653002000084653001600104100001800120245007500138856007300213520148100286       2020                            d  bDelft University of TechnologyaDelft10aschistosomiasis10aDiagnostics1 aJujjavarapu S00aAutomating the Diagnosis and Quantification of Urinary Schistosomiasis  uhttp://resolver.tudelft.nl/uuid:b213e477-343c-4a47-8d7c-8b931c15b3e93 aSchistosomiasis is a neglected tropical disease (NTD) that affects around a quarter-billion people worldwide. Most of the infected people live in tropical regions, especially in sub-Saharan Africa, where there is limited access to diagnostic and other relevant medical facilities. The current reference standard diagnostic procedure - conventional microscopy - is a relatively inexpensive procedure to use on a large scale, but it still requires trained operators and an initial financial investment which are hard to procure and maintain in remote areas with inadequate facilities. Moreover, the diagnostic sensitivity of the procedure is modest and varies over a wide range. In this work, we present the development of an inexpensive diagnostic instrument for urinary schistosomiasis that is automated to scan, analyse and diagnose the disease, and quantify the level of infection. We explore the design of the device with an open-source philosophy in mind, to enable makerspaces and other interested parties to reproduce the device locally. The device is manufacturable for as little as €200. It adheres to the standard sample preparation and diagnosis procedure established by the World Health Organisation (WHO), and images the relevant biomarkers to an adequate resolution for automated detection, diagnosis, and quantification for epidemiological surveillance. We believe this device can be an essential means for point-of-care diagnosis in resource-limited settings.