Performance evaluation of the AiDx multi-diagnostic automated microscope for the detection of schistosomiasis in Abuja, Nigeria

In this research, we report on the performance of automated optical digital detection and quantification of Schistosoma haematobium provided by AiDx NTDx multi-diagnostic Assist microscope. Our study was community-based, and a convenient sampling method was used in 17 communities in Abuja Nigeria, based on the disease prevalence information extracted from the baseline database on schistosomiasis, NTD Division, of the Federal Ministry of Health. At baseline, samples from 869 participants were evaluated of which 358 (34.1%) tested S. haematobium positive by the reference diagnostic standard. Registered images from the fully automated (autofocusing, scanning, image registration and processing, AI image analysis and automatic parasite count) AiDx assist microscope were analyzed. The Semi automated (autofocusing, scanning, image registration & processing and manual parasite count) and the fully automated AiDx Assist showed comparable sensitivities and specificities of [90.3%, 98%] and [89%, 99%] respectively. Overall, estimated egg counts of the semi-automated & fully automated AiDx Assist correlated significantly with the egg counts of conventional microscopy (r = 0.93, p ≤ 0.001 and r = 0.89, p ≤ 0.001 respectively). The AiDx Assist device performance is consistent with requirement of the World Health Organization diagnostic target product profile for monitoring, evaluation, and surveillance of Schistosomiasis elimination Programs.Design for SustainabilityTeam Michel Verhaege

Image-Based Awareness Campaign and Community Mobilization in the Control of Schistosomiasis

Community awareness and participation in mass screening is critical for schistosomiasis control. This study assessed the impact of sharing anonymized image-based positive test results on the uptake of screening during community mobilization outreach. We conducted an observational study to compare the population response to standard and image-based strategies in 14 communitiesin Abuja, Nigeria. Six hundred and ninety-one (341 females, 350 males) individuals participated in this study. We analyzed the response ratio, relative increase, and sample collection time. The potential treatment uptake and change in social behavior were determined based on a semi-structured questionnaire. The mean response ratio of the image-based strategy was 89.7% representing asignificantly higher ratio than the 27.8%, which was observed under the standard mobilization approach (p ≤ 0.001). The image-based method was associated with 100% of the participants agreeing to provide urine samples, 94% willing to be treated, 89% claiming to have been invited to participate in the study by a friend, and 91% desiring to change a predisposing behavioral habit. These findings indicate that image-based community awareness campaigns may increase the population’s perception about schistosomiasis transmission and treatment. This raises new possibilities for local resource mobilization to expand services in reaching the last mile in schistosomiasis control.Design for Sustainabilit