Community Mobilisation for Human Sample Collection in Sensitive Communities: Experiences from Granular Mapping of Schistosomiasis and Soil-Transmitted Helminths in Ekiti State, South West, Nigeria.

Community mobilisation is a vital process for raising awareness and increasing participation in healthcare interventions, research, and programmes that require human sample collection and mass management. In this report, we present the community mobilisation approach undertaken for the implementation of the operational mapping and assessment of granular schistosomiasis and soil-transmitted helminths in Ekiti State, Nigeria. The mobilisation was conducted in 177 communities/wards of the 16 local government areas.

An automated slide scanning system for membrane filter imaging in diagnosis of urogenital schistosomiasis.

Traditionally, automated slide scanning involves capturing a rectangular grid of field-of-view (FoV) images which can be stitched together to create whole slide images, while the autofocusing algorithm captures a focal stack of images to determine the best in-focus image. However, these methods can be time-consuming due to the need for X-, Y- and Z-axis movements of the digital microscope while capturing multiple FoV images. In this paper, we propose a solution to minimise these redundancies by presenting an optimal procedure for automated slide scanning of circular membrane filters on a glass slide.

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.

Two-stage automated diagnosis framework for urogenital schistosomiasis in microscopy images from low-resource settings.

Purpose: Automated diagnosis of urogenital schistosomiasis using digital microscopy images of urine slides is an essential step toward the elimination of schistosomiasis as a disease of public health concern in Sub-Saharan African countries. We create a robust image dataset of urine samples obtained from field settings and develop a two-stage diagnosis framework for urogenital schistosomiasis.

Approach: Urine samples obtained from field settings were captured using the Schistoscope device, and eggs present in the images were manually annotated by experts to create the SH dataset.

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 communities in Abuja, Nigeria.

Schistoscope: An Automated Microscope with Artificial Intelligence for Detection of Eggs in Resource-Limited Settings.

For many parasitic diseases, the microscopic examination of clinical samples such as urine and stool still serves as the diagnostic reference standard, primarily because microscopes are accessible and cost-effective. However, conventional microscopy is laborious, requires highly skilled personnel, and is highly subjective. Requirements for skilled operators, coupled with the cost and maintenance needs of the microscopes, which is hardly done in endemic countries, presents grossly limited access to the diagnosis of parasitic diseases in resource-limited settings.