Towards 2030 target for hepatitis B and C viruses elimination: Assessing the validity of predonation rapid diagnostic tests versus enzyme-linked immunosorbent assay in state hospitals in Kaduna, Nigeria

Ibrahim, Ismaila Nda; Mamman, Aisha Indo; Balogun, Muhammad Shakir; Babadoko, Aliyu; Hassan, Abdulaziz; Augustine, Benjamin; Suleiman, Abubakar; Kusfa, Ibrahim Usman

doi:10.4103/nmj.nmj_93_18

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…We also detected antibodies to the hepatitis C virus in 1.73% of the study population. Recent studies conducted in various parts of Nigeria reported hepatitis C sero-prevalence rates that ranged from 0.5% to 3.0%, with an average of 1.73% [ 28 29 30 31 ]. This perfect concordance is again evidence of the high quality and reliability of the NAIIS study.…”

Section: Discussionmentioning

confidence: 99%

The Burden of HIV, Hepatitis B and Hepatitis C by Armed Conflict Setting: The Nigeria AIDS Indicator and Impact Survey, 2018

Aliyu

Ehoche

et al. 2021

Annals of Global Health

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Background: Against a background of security challenges, Nigeria conducted recently the largest population-based HIV survey in the world to ascertain the burden of the HIV disease in the country. Objective: We evaluated the main outcomes of the survey and the level of success using participation/response indicators. Methods: The survey was conducted from July–December 2018 by over 6,000 field staff across Nigeria in six consecutive webs, using two-stage cluster sampling. We estimated the prevalence of HIV, hepatitis B and hepatitis C in the entire country and by conflict zone status. Adjusted odds ratios (OR) and 95% confidence intervals (CI) from survey logistic regression models were used to compare the likelihood of test positivity for the three infections between zones. Findings: A total of 186,405 adults were interviewed from 97,250 households in 3,848 census enumeration areas. The overall HIV, hepatitis B and hepatitis C positivity rates were 1.55%, 7.63% and 1.73%, respectively. The prevalence of HIV, hepatitis B and C infection was significantly greater in conflict than non-conflict zones (HIV: 1.75% versus 1.0%; hepatitis B: 9.9% versus 7.3%; and hepatitis C: 3.2% versus 0.3%; p < 0.01 in all cases). Individuals living in conflict zones were about three times as likely to test positive for HIV (OR = 2.80, 95% CI = 2.08, 3.60) and nearly six times as likely to test positive for hepatitis C (OR = 5.90, 95% CI = 2.17, 16.67). Conclusion: Large population-based surveys are feasible, even in armed conflict settings. The burden of HIV, hepatitis B and hepatitis C was significantly higher in areas of conflict in Nigeria, highlighting the need for reinforced public health control measures in these settings in order to attain UNAIDS’ 95-95-95 targets of controlling the HIV epidemic in sub-Saharan Africa by 2030.

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Section: Discussionmentioning

confidence: 99%

The Burden of HIV, Hepatitis B and Hepatitis C by Armed Conflict Setting: The Nigeria AIDS Indicator and Impact Survey, 2018

Aliyu

Ehoche

et al. 2021

Annals of Global Health

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“…AUC was chosen as the evaluation method because it is more suitable for assessing the value of prediction performance using both balanced and unbalanced data sets [41]. Here is the formula for AUC as shown in (9).…”

Section: 𝑃𝑟𝑒𝑐𝑖𝑠𝑖𝑜𝑛 =mentioning

confidence: 99%

“…Although RDTs have advantages in speed and ease of use, they often have lower sensitivity and specificity compared to more sophisticated laboratory diagnostic methods. Therefore, RDT results usually require further confirmation using more accurate diagnostic procedures [9]. In addition to RDTs, detection can also be done with the help of artificial intelligence technologies, such as machine learning.…”

Section: Introductionmentioning

confidence: 99%

Implementation of C5.0 Algorithm using Chi-Square Feature Selection for Early Detection of Hepatitis C Disease

MAHMUD,

BUDİMAN,

INDRİANİ

et al. 2024

j.electron.electromedical.eng.med.inform

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Hepatitis C, a significant global health challenge, affects 71 million people worldwide, with severe complications such as cirrhosis and hepatocellular carcinoma. Despite its prevalence and availability in rapid diagnostic tests (RDTs), the need for accurate early detection methods remains critical. This research aims to enhance hepatitis C virus classification accuracy by integrating the C5.0 algorithm with Chi-Square feature selection, addressing the limitations of current diagnostic approaches and potentially reducing diagnostic errors. This research explores the development of a machine learning model for hepatitis C prediction, utilizing a publicly available dataset from Kaggle. It encompasses preprocessing techniques such as label encoding, handling missing values, normalization, feature selection, model development, and evaluation to ensure the model's efficacy and accuracy in diagnosing hepatitis C. The findings of this study reveal that implementing Chi-Square feature selection significantly enhances the effectiveness of machine learning algorithms. Specifically, the combination of the C5.0 algorithm and Chi-Square feature selection yielded a remarkable accuracy of 96.75%, surpassing previous research benchmarks. This highlights the potent synergy between advanced feature selection techniques and machine learning algorithms in improving diagnostic precision. The study conclusively demonstrates that machine learning is an effective tool for detecting hepatitis C, showcasing the potential to enhance diagnostic accuracy significantly. As a future recommendation, adopting AutoML is suggested to periodically automate the selection of the optimal algorithm, promising further improvements in detection capabilities.

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Towards 2030 target for hepatitis B and C viruses elimination: Assessing the validity of predonation rapid diagnostic tests versus enzyme-linked immunosorbent assay in state hospitals in Kaduna, Nigeria

Cited by 2 publications

References 17 publications

The Burden of HIV, Hepatitis B and Hepatitis C by Armed Conflict Setting: The Nigeria AIDS Indicator and Impact Survey, 2018

The Burden of HIV, Hepatitis B and Hepatitis C by Armed Conflict Setting: The Nigeria AIDS Indicator and Impact Survey, 2018

Implementation of C5.0 Algorithm using Chi-Square Feature Selection for Early Detection of Hepatitis C Disease

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