The week's pick
Random Articles
Reseach Article
The Impact of Socio-demographic Factors on the Prevalence of Hepatitis B in Sokoto, Nigeria: An Association Rule Mining Approach
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 185 - Number 45 |
| Year of Publication: 2023 |
| Authors: Rufai Ahmad, Fatimah Jumare, Mahmood Umar |
10.5120/ijca2023923264
|
Rufai Ahmad, Fatimah Jumare, Mahmood Umar . The Impact of Socio-demographic Factors on the Prevalence of Hepatitis B in Sokoto, Nigeria: An Association Rule Mining Approach. International Journal of Computer Applications. 185, 45 ( Nov 2023), 24-28. DOI=10.5120/ijca2023923264
Abstract
The hepatitis B virus (HBV) is a dangerous liver infection that results in hepatitis. Despite efforts to create awareness of the disease and the development of vaccines to prevent people from being infected, the prevalence of HBV in developing countries is still very high. This study aimed to apply apriori algorithm to investigate the relationship between socio-demographic factors and HBV status among patients visiting various hospitals within the metropolis of Sokoto state, Nigeria. Using data from 423 patients, we found that younger participants aged 26-35 have the highest positive cases. The rules generated from the apriori algorithm suggest low awareness of both HBV and the HBV vaccines. However, having some knowledge about HBV and the vaccine tends to be associated with negative HBV status. These findings have implications for healthcare bodies in that they could inform how to devise strategies for treatment and awareness campaigns to reduce the spread of the disease.
References
- WHO, “Hepatitis B,” 2023. https://www.who.int/news-room/fact-sheets/detail/hepatitis-b#:~:text=WHO estimates that 296 million,carcinoma (primary liver cancer). (accessed Oct. 07, 2023).
- Hepatitis B Foundation, “Hepatitis B Facts and Figures,” 2022. https://www.hepb.org/what-is-hepatitis-b/what-is-hepb/facts-and-figures/ (accessed Jan. 15, 2022).
- Punch, “World Hepatitis Day 2021: Nigeria dallies as world races to end disease by 2030,” 2021. https://www.premiumtimesng.com/news/headlines/476145-world-hepatitis-day-2021-nigeria-dallies-as-world-races-to-end-disease-by-2030.html (accessed Jan. 15, 2022).
- N. Fessehaye, A. Berhane, and H. Ahimed, “Prevalence of hepatitis B virus infection and associated seromarkers among pregnant women in Eritrea,” J. Hum. Virol. Retrovirology, vol. 6, no. 1, pp. 30–38, 2018.
- C. Strong, K. Hur, F. Kim, J. Pan, S. Tran, and H.-S. Juon, “Sociodemographic characteristics, knowledge and prevalence of viral hepatitis infection among Vietnamese Americans at community screenings,” J. Immigr. Minor. Heal., vol. 17, no. 1, pp. 298–301, 2015.
- M. Aminu, “HEPATITIS B INFECTION IN NIGERIA: A REVIEW,” 2014.
- S. Tosun, O. Aygün, H. Ö. Özdemir, E. Korkmaz, and D. Özdemir, “The impact of economic and social factors on the prevalence of hepatitis B in Turkey,” BMC Public Health, vol. 18, pp. 1–9, 2018.
- Daily Trust, “Why North Fails To Close Education Gap With South,” 2020. https://dailytrust.com/why-north-fails-to-close-education-gap-with-south (accessed Jul. 08, 2021).
- A. Amzat, “Despite decades of funding, literacy level in the northern states remains low,” 2017. .
- L. Feinstein, R. Sabates, T. M. Anderson, A. Sorhaindo, and C. Hammond, “What are the effects of education on health,” in Measuring the effects of education on health and civic engagement: Proceedings of the Copenhagen symposium, 2006, pp. 171–354.
- H. M. Chung and P. Gray, “Data mining,” J. Manag. Inf. Syst., vol. 16, no. 1, pp. 11–16, 1999.
- S. Dreiseitl and L. Ohno-Machado, “Logistic regression and artificial neural network classification models: a methodology review,” J. Biomed. Inform., vol. 35, no. 5–6, pp. 352–359, 2002.
- M. Ilayaraja and T. Meyyappan, “Mining medical data to identify frequent diseases using Apriori algorithm,” in 2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering, 2013, pp. 194–199.
- M. Karaolis, J. A. Moutiris, L. Papaconstantinou, and C. S. Pattichis, “Association rule analysis for the assessment of the risk of coronary heart events,” in 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009, pp. 6238–6241.
- S. Hussain, N. A. Dahan, F. M. Ba-Alwib, and N. Ribata, “Educational data mining and analysis of students’ academic performance using WEKA,” Indones. J. Electr. Eng. Comput. Sci., vol. 9, no. 2, pp. 447–459, 2018.
- A. M. Doddi SS Ravi, David C. Torney, Srinivas, “Discovery of association rules in medical data,” Med. Inform. Internet Med., vol. 26, no. 1, pp. 25–33, 2001.
- R. Hu, “Medical data mining based on association rules,” Comput. Inf. Sci., vol. 3, no. 4, p. 104, 2010.
- K.-M. Jhang, M.-C. Chang, T.-Y. Lo, C.-W. Lin, W.-F. Wang, and H.-H. Wu, “Using the Apriori algorithm to classify the care needs of patients with different types of dementia,” Patient Prefer. Adherence, pp. 1899–1912, 2019.
- U. of Waikato, “Weka 3: Machine Learning Software in Java,” 2022. https://www.cs.waikato.ac.nz/ml/weka/ (accessed Jan. 16, 2022).
- A. E. Sadoh and A. Ofili, “Hepatitis B infection among Nigerian children admitted to a children’s emergency room,” Afr. Health Sci., vol. 14, no. 2, pp. 377–383, 2014.
- D. Ndububa et al., “Prospective cohort study of prevention of mother to child transmission of hepatitis B infection and 9 months follow-up of hepatitis B-exposed infants at Ile-Ife, Nigeria,” BMJ Open, vol. 12, no. 11, p. e063482, 2022.
- B. I. Ajuwon, I. Yujuico, K. Roper, A. Richardson, M. Sheel, and B. A. Lidbury, “Hepatitis B virus infection in Nigeria: a systematic review and meta-analysis of data published between 2010 and 2019,” BMC Infect. Dis., vol. 21, pp. 1–15, 2021.
Index Terms
Keywords