Browsing by Author "Chacky, Frank"

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    Estimating the hole surface area of insecticide-treated nets using image analysis, manual hole counting and exact hole measurements
    (BMC, 2025-03-14) Mbuba, Emmanuel; Mañas‑Chavernas, Natalia; Moore, Sarah; Ruzige, Philipo; Kobe, Dickson; Moore, Jason; Philipo, Rose; Kisoka, Noela; Pontiggia, Gianpaolo; Chacky, Frank; Mwalimu, Charles; Cattin, Philippe; Wolleb, Julia; Sandkuehler, Robin; Ross, Amanda
    Background The physical integrity of insecticidal‑treated nets (ITNs) is important for creating a barrier against host seeking mosquitoes and, therefore, influences people’s perception of the net’s effectiveness and their willingness to use it. Monitoring the physical integrity of ITNs over time provides information for replenishment schedules and purchasing decisions. Currently, the assessment of physical integrity of ITNs is conducted by manually counting holes and estimating their size to class the net as functional or not. This approach is laborious to routinely conduct during field surveys of ITNs. Automated image analysis may provide a rapid assessment of the physical integrity of ITNs but it is not known if the images can capture sufficient information. As a first step, this study aimed to assess the agreement between estimated hole surface areas derived from (1) manually segmented images, (2) manual hole counting compared to (3) ground truth obtained by calibrated close‑up shots of individual holes. Methods The physical integrity of 75 ITNs purposely selected from an ongoing study was assessed by manual hole counting, image analysis and ground truth. For the image analysis, a graphical user interface was developed and used for the segmentation of holes visible in photographs taken from each side of the net. The hole surface area was then computed from this data. The agreement between the estimates from image analysis and manual hole counting was compared to the ground truth using the Bland–Altman method. Results There was substantial agreement between the manually segmented image analysis estimates and the ground truth hole surface areas. The overall bias was small, with a mean ratio of the hole surface area from image analysis to the ground truth of 0.70, and the 95% limits of agreement ranging from 0.35 to 1.38. Manual hole counting underestimated the hole surface area compared to the ground truth, particularly among nets with holes above 10 cm in diameter. Conclusion Images coupled with manual segmentation contain sufficient information to calculate hole surface area. This lays the groundwork for incorporating automatic hole detection, and then assessing whether this method will offer a fast and objective method for routine assessment of physical integrity of ITNs. While the WHO
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    Potential Opportunities and Challenges of Deploying Next Generation Sequencing and CRISPR-Cas Systems to Support Diagnostics and Surveillance Towards Malaria Control and Elimination in Africa
    (Frontiers, 2022-07-13) Lyimo, Beatus; Popkin-Hall, Zachary; Giesbrecht, David; Mandara, Celine; Madebe, Rashid; Bakari, Catherine; Pereus, Dativa; Seth, Misago; Ngamba, Ramadhan; Mbwambo, Ruth; MacInnis, Bronwyn; Mbwambo, Daniel; Garimo, Issa; Chacky, Frank; Aaron, Sijenunu; Lusasi, Abdallah; Molteni, Fabrizio; Njau, Ritha; Cunningham, Jane; Lazaro, Samwel; Mohamed, Ally; Juliano, Jonathan; Bailey, Jeffrey; Ishengoma, Deus
    Recent developments in molecular biology and genomics have revolutionized biology and medicine mainly in the developed world. The application of next generation sequencing (NGS) and CRISPR-Cas tools is now poised to support endemic countries in the detection, monitoring and control of endemic diseases and future epidemics, as well as with emerging and re-emerging pathogens. Most low and middle income countries (LMICs) with the highest burden of infectious diseases still largely lack the capacity to generate and perform bioinformatic analysis of genomic data. These countries have also not deployed tools based on CRISPR-Cas technologies. For LMICs including Tanzania, it is critical to focus not only on the process of generation and analysis of data generated using such tools, but also on the utilization of the findings for policy and decision making. Here we discuss the promise and challenges of NGS and CRISPR-Cas in the context of malaria as Africa moves towards malaria elimination. These innovative tools are urgently needed to strengthen the current diagnostic and surveillance systems. We discuss ongoing efforts to deploy these tools for malaria detection and molecular surveillance highlighting potential opportunities presented by these innovative technologies as well as challenges in adopting them. Their deployment will also offer an opportunity to broadly build in-country capacity in pathogen genomics and bioinformatics, and to effectively engage with multiple stakeholders as well as policy makers, overcoming current workforce and infrastructure challenges. Overall, these ongoing initiatives will build the malaria molecular surveillance capacity of African researchers and their institutions, and allow them to generate genomics data and perform bioinformatics analysis in-country in order to provide critical information that will be used for real-time policy and decision-making to support malaria elimination on the continent.