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This study investigated non-revenue water (NRW) dynamics in Rwanda from 1 July 2014, to 30 June 2023, utilizing panel data and cross-sectional datasets. It aimed to assess progress towards achieving the government's target of 25% NRW. Through panel data analysis and machine learning models, it examined water supply variations, NRW levels, and associated risks across fiscal years and regions. The observed average NRW of 41.24% underscores the need for targeted interventions to meet the set target. Regional disparities, exemplified by Kigali City's water network's 38.61% average NRW compared to Nyagatare's 55.31%, emphasize the importance of tailored strategies. Machine learning models indicated low and inconsistent progress across networks. Notably, no single water supply managed to meet the target in more than 20% of the 36 quarters studied. Comparison with existing literature highlighted excessive NRW in Rwanda, aligning with global trends. Achieving the 25% NRW target requires region-specific approaches, necessitating infrastructure improvements, leak detection, and capacity building. The positive correlation between water loss risk and household access to improved water sources accentuated the complexity in NRW reduction efforts. This study contributes to understanding NRW dynamics and informs sustainable water management strategies tailored to Rwanda's context. HIGHLIGHTS Need for balancing NRW reduction and access to improved water sources.; NRW is a region-specific issue.; WASAC is progressing slowly in the attainment of the target NRW of 25%.; Need to leverage panel data analysis and machine learning algorithms to understand NRW.; Most instances of 25% NRW or below were uncertain (due to issues of overlaps identified in all NRW classes), thus the need for a specific investigation on them.;

This study in Rwanda offers a comprehensive analysis of water quality, reliability, and cost-effectiveness, departing from previous research by utilizing panel data analysis for a nuanced understanding of spatiotemporal dynamics. Unlike earlier studies focusing on specific aspects, this research adopts a holistic approach, examining factors crucial for water supply, quality, and cost, thus providing an integrated view of Rwanda's water sector. By analyzing data from various sources, including the Water and Sanitation Corporation (WASAC), the study evaluates the reliability, quality, and cost-effectiveness of drinking water. It identifies cost-effective water treatment plants and studies determinants such as production cost, raw water quality, and supply between 2017 and 2022, introducing novel metrics such as performance scores and a drinking water quality index. Despite an increase in lost water, WASAC notably improves water supply, resulting in a higher water access rate by 2022. The study highlights the influence of factors such as performance scores and raw water quality on water supply and quality. It emphasizes continuous monitoring, targeted interventions, and community engagement for sustainable water service delivery. The findings provide actionable insights for policymakers, stakeholders, and practitioners, aiming to enhance water management strategies and improve water access in Rwanda. HIGHLIGHTS Panel data analysis offers nuanced spatiotemporal insights departing from cross-sectional methods.; Holistic approach examines water supply, quality, and cost, unlike prior single-focus studies.; Innovative metrics introduced include performance score and water quality index.; Practical insights help identify cost-effective water treatment plants and key determinants.; Sustainability focus emphasizes continuous monitoring and community engagement.;

In various surveys, presence of measurement errors has led to misleading results in estimation of various population parameters. This study indicates the effects of measurement errors on estimates of population total and population variance when samples are drawn using systematic sampling technique from a stratified population. A finite population was generated through simulation. The population was then stratified into four strata followed by generation of ten samples in each of them using systematic sampling technique. In each stratum a sample was picked at random. The findings of this work indicated that systematic errors affected the accuracy of the estimates by overestimating both the population total and the population variance. Random errors only added variability to the data but their effect on the estimates of the population total and population variance was not that profound.

This study in Rwanda offers a comprehensive analysis of water quality, reliability, and cost-effectiveness, departing from previous research by utilizing panel data analysis for a nuanced understanding of spatiotemporal dynamics. Unlike earlier studies focusing on specific aspects, this research adopts a holistic approach, examining factors crucial for water supply, quality, and cost, thus providing an integrated view of Rwanda's water sector. By analyzing data from various sources, including the Water and Sanitation Corporation (WASAC), the study evaluates the reliability, quality, and cost-effectiveness of drinking water. It identifies cost-effective water treatment plants and studies determinants such as production cost, raw water quality, and supply between 2017 and 2022, introducing novel metrics such as performance scores and a drinking water quality index. Despite an increase in lost water, WASAC notably improves water supply, resulting in a higher water access rate by 2022. The study highlights the influence of factors such as performance scores and raw water quality on water supply and quality. It emphasizes continuous monitoring, targeted interventions, and community engagement for sustainable water service delivery. The findings provide actionable insights for policymakers, stakeholders, and practitioners, aiming to enhance water management strategies and improve water access in Rwanda. [ABSTRACT FROM AUTHOR]

Aim/Purpose The amount of information published has increased dramatically due to the information explosion. The issue of managing information as it expands at this rate lies in the development of information extraction technology that can turn unstructured data into organized data that is understandable and controllable by computers Background The primary goal of named entity recognition (NER) is to extract named entities from amorphous materials and place them in pre-defined semantic classes. Methodology In our work, we analyze various machine learning algorithms and implement KNN which has been widely used in machine learning and remains one of the most popular methods to classify data. Contribution To the researchers' best knowledge, no published study has presented Named entity recognition for the Kikuyu language using a machine learning algorithm. This research will fill this gap by recognizing entities in the Kikuyu language. Findings An evaluation was done by testing precision, recall, and F-measure. The experiment results demonstrate that using K-NN is effective in classification performance. Recommendations for Researchers With enough training data, researchers could perform an experiment and check the learning curve with accuracy that compares to state of art NER. Impact on Society NER helps recognize important textual components including names of individuals, places, and monetary value among others. When dealing with enormous datasets, it is critical to sort unstructured data and to find vital information by identifying the major entities in a text. Future Research Future studies may be done using unsupervised and semi-supervised learning algorithms for other resource-scarce languages. [ABSTRACT FROM AUTHOR]

Background:  The COVID-19 pandemic relies on real-time polymerase chain reaction (qRT-PCR) for the detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), to facilitate roll-out of patient care and infection control measures. There are several qRT-PCR assays with little evidence on their comparability. We report alterations to the developers' recommendations to sustain the testing capability in a resource-limited setting. Methods:  We used a SARS-CoV-2 positive control RNA sample to generate several 10-fold dilution series that were used for optimization and comparison of the performance of the four qRT-PCR assays: i) Charité Berlin primer-probe set, ii) European Virus Archive - GLOBAL (EVAg) primer-probe set, iii) DAAN premixed commercial kit and iv) Beijing Genomics Institute (BGI) premixed commercial kit. We adjusted the manufacturer- and protocol-recommended reaction component volumes for these assays and assessed the impact on cycle threshold (Ct) values. Results:  The Berlin and EVAg E gene and RdRp assays reported mean Ct values within range of each other across the different titrations and with less than 5% difference. The DAAN premixed kit produced comparable Ct values across the titrations, while the BGI kit improved in performance following a reduction of the reaction components. Conclusion:  We achieved a 2.6-fold and 4-fold increase in the number of tests per kit for the commercial kits and the primer-probe sets, respectively. All the assays had optimal performance when the primers and probes were used at 0.375X, except for the Berlin N gene assay. The DAAN kit was a reliable assay for primary screening of SARS-CoV-2 whereas the BGI kit's performance was dependent on the volumes and concentrations of both the reaction buffer and enzyme mix. Our recommendation for SARS-CoV-2 diagnostic testing in resource-limited settings is to optimize the assays available to establish the lowest volume and suitable concentration of reagents required to produce valid results., Competing Interests: No competing interests were disclosed., (Copyright: © 2022 Mohammed KS et al.)

Background. International recommendations for the control of the coronavirus disease 2019 (COVID-19) pandemic emphasize the central role of laboratory testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent, at scale. The availability of testing reagents, laboratory equipment and qualified staff are important bottlenecks to achieving this. Elsewhere, pooled testing (i.e. combining multiple samples in the same reaction) has been suggested to increase testing capacities in the pandemic period. Methods. We discuss our experience with SARS-CoV-2 pooled testing using real-time reverse transcription polymerase chain reaction (RT-PCR) on the Kenyan Coast. Results. In mid-May, 2020, our RT-PCR testing capacity for SARS-CoV-2 was improved by ~100% as a result of adoption of a six-sample pooled testing strategy. This was accompanied with a concomitant saving of ~50% of SARS-CoV-2 laboratory test kits at both the RNA extraction and RT-PCR stages. However, pooled testing came with a slight decline of test sensitivity. The RT-PCR cycle threshold value (ΔCt) was ~1.59 higher for samples tested in pools compared to samples tested singly. Conclusions. Pooled testing is a useful strategy to increase SARS-CoV-2 laboratory testing capacity especially in low-income settings., Competing Interests: No competing interests were disclosed., (Copyright: © 2021 Agoti CN et al.)

Background. International recommendations for the control of the coronavirus disease 2019 (COVID-19) pandemic emphasize the central role of laboratory testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent, at scale. The availability of testing reagents, laboratory equipment and qualified staff are important bottlenecks to achieving this. Elsewhere, pooled testing (i.e. combining multiple samples in the same reaction) has been suggested to increase testing capacities in the pandemic period. Methods. We discuss our experience with SARS-CoV-2 pooled testing using real-time reverse transcription polymerase chain reaction (RT-PCR) on the Kenyan Coast. Results. In mid-May, 2020, our RT-PCR testing capacity for SARS-CoV-2 was improved by ~100% as a result of adoption of a six-sample pooled testing strategy. This was accompanied with a concomitant saving of ~50% of SARS-CoV-2 laboratory test kits at both the RNA extraction and RT-PCR stages. However, pooled testing came with a slight decline of test sensitivity. The RT-PCR cycle threshold value (ΔCt) was ~1.59 higher for samples tested in pools compared to samples tested singly. Conclusions. Pooled testing is a useful strategy to increase SARS-CoV-2 laboratory testing capacity especially in low-income settings., Competing Interests: No competing interests were disclosed., (Copyright: © 2020 Agoti CN et al.)

Background: The global COVID-19 outbreak relies on a quantitative real-time polymerase chain reaction (qRT-PCR) for the detection of severe acute respiratory syndrome coronavirus (SARS-CoV-2), to facilitate the roll-out of patient care and infection control measures. There are several qRT-PCR assays with little evidence on their comparability. We report alterations to the developers' recommendations to sustain the testing capability in our setting, where the supply of testing reagents is limited. Methods: Standards generated from a serially-diluted positive control and previously identified positive/negative samples were used to determine the optimal volumes of the qRT-PCR reagents and to evaluate the validity and performance of four assays: Charité Berlin and European Virus Archive - GLOBAL (EVAg) primer-probe sets, and DAAN and Beijing Genomics Institute (BGI) premixed commercial kits. A multiplex and singleplex RT-PCR kit was used with the two primer-probe sets and the recommended assay volumes of the two premixed kits were altered. Results: In comparison to the multiplex RT-PCR kit, the singleplex RT-PCR kit combined with the primer-probe sets yielded consistent cycle threshold (Ct) values across the different titrations tested. The DAAN premixed kit produced comparable Ct values across the titrations, while the BGI kit showed incomparable Ct values and inconsistent results between batches using the manufacturer's recommended volumes. Conclusion: We achieved a 2.5-fold and 4-fold increase in the number of tests/kit for the premixed kits and the primer-probe sets, respectively. The primer-probe set assays were reliable and consistent, and we preferred a combination of an EVAg and a Berlin target. Any inconclusive result was repeated by different individuals following the same protocol. DAAN was a consistent and reliable assay even at lower concentrations from the stated recommendations. BGI in contrast, required dilution to improve its performance and was hence an assay that was used in combination with EVAg or Berlin targets., Competing Interests: No competing interests were disclosed., (Copyright: © 2020 Mohammed KS et al.)