Factorial Analysis to Categories Spread and Effect of Ebola Virus from Various Countries
by Venu Paritala * 
, Harsha Thummala
Department of BioTechnology Vignan’s Foundation for Science, Technology & Research, Guntur, A.P, India
* Author to whom correspondence should be addressed.
Journal of Engineering Research and Sciences, Volume 1, Issue 6, Page # 1-6, 2022; DOI: 10.55708/js0106001
Keywords: Ebola Virus, Factorial analysis, Correlation, Cases
Received: 19 February 2022, Revised: 22 March 2022, Accepted: 23 March 2022, Published Online: 04 June 2022
APA Style
Paritala, V., & Thummala, H. (2022). Factorial Analysis to Categories Spread and Effect of Ebola Virus from Various Countries. Journal of Engineering Research and Sciences, 1(6), 1–6. https://doi.org/10.55708/js0106001
Chicago/Turabian Style
Paritala, Venu, and Harsha Thummala. “Factorial Analysis to Categories Spread and Effect of Ebola Virus from Various Countries.” Journal of Engineering Research and Sciences 1, no. 6 (June 1, 2022): 1–6. https://doi.org/10.55708/js0106001.
IEEE Style
V. Paritala and H. Thummala, “Factorial Analysis to Categories Spread and Effect of Ebola Virus from Various Countries,” Journal of Engineering Research and Sciences, vol. 1, no. 6, pp. 1–6, Jun. 2022, doi: 10.55708/js0106001.
The main objective of this research analyze and correlates the number of cases and death rates reported on the Ebola virus in many countries. Ebola virus is one of the most lethal diseases to infect humans. This approach Proceeding uses the Factorial analysis technique in the Ebola Virus dataset. This method takes the largest common variance from all criteria and combines it into a single score. The analysis is applied to reported and categorize the most effective way countries using the counts of cases and deaths. To this investigate get it, and communicate data in a way of graphic factual properties. The analytic results on the Ebola virus dataset are not accessible anywhere. The Analysis was done by R Studio.
- Kourtis AP, Appelgren K, Chevalier MS, McElroy A. Ebola Virus Disease: Focus on Children. Pediatr Infect Dis J. 2015 Aug;34(8):893-7. doi: 10.1097/INF.0000000000000707
- Burke RM, Midgley CM, Dratch A, et al. Active Monitoring of Persons Exposed to Patients with Confirmed COVID-19 — United States, January–February 2020. MMWR Morb Mortal Wkly Rep 2020;69:245–6. https://doi.org/10.15585/mmwr. mm6909e1.
- Hunter DJ. Covid-19 and the stiff upper lip—the pandemic response in the united kingdom. N Engl J Med 2020.
- Razai MS, Doerholt K, Ladhani S, Oakeshott P. Coronavirus disease 2019 (covid-19): a guide for UK GPs. BMJ. 2020 Mar 5;368:m800. doi: 10.1136/bmj.m800.
- Lillie PJ, Samson A, Li A, Adams K, Capstick R, Barlow GD, Easom N, Hamilton E, Moss PJ, Evans A, Ivan M, Phe Incident Team, Taha Y, Duncan CJA, Schmid ML, The Airborne Hcid Network. Novel coronavirus disease (Covid-19): The first two patients in the UK with person to person transmission. J Infect. 2020 May;80(5):578-606. doi: 10.1016/j.jinf.2020.02.020. Epub 2020 Feb 28. PMID: 32119884; PMCID: PMC7127394.
- Ahmad, F., Jhajj, A. K., Stewart, D. E., Burghardt, M., & Bierman, A. S. (2014). Single item measures of self-rated mental health: A scoping review. BMC Health Services Research, 14(1), 398. https://doi.org/10.1186/1472-6963- 14-398.
- Ahorsu, D. K., Lin, C. Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2020). The fear of COVID-19 Scale: Development and initial validation. International Journal of Mental Health and Addiction. https://doi.org/ 10.1007/s11469-020-00270-8.
- Arbuckle, J. L. (2014). IBM SPSS AMOS 23 user’s guide. IBM.
- Arpaci, I., Karatas¸, K., & Baloglu, M. (2020). The development and initial tests for the psychometric properties of the COVID-19 Phobia Scale (C19P-S). Personality and Individual Differences, 164, 110108. https://doi.org/10. 1016/j.paid.2020110108.
- Ming H, Abuja N, Kriegman D: Face detection using mixtures of linear subspaces. Proceedings Fourth International Conference on Automatic Face and Gesture Recognition 2000, 4:70-76.
- Aguilar O, West M: Bayesian dynamic factor models and portfolio allocation. Journal of Business and Economic Statistics 2000, 18:338-357.
- Mohammad Reza Mahmoudi, Dumitru Baleanu, Shahab S. Band,Amir Mosavi, Factor analysis approach to classify COVID-19 datasets in several regions.
- Murat Yıldırım & Abdurrahim Güler (2020): Factor analysis of the COVID-19 Perceived Risk Scale: A preliminary study, Death Studies.
- Ressing M, Blettner M, Klug SJ. Data analysis of epidemiological studies: part 11 of a series on evaluation of scientific publications. Dtsch Arztebl Int. 2010 Mar;107(11):187-92. doi: 10.3238/arztebl.2010.0187. Epub 2010 Mar 19. PMID: 20386677; PMCID: PMC2853157.
- Jacob ST, Crozier I, Fischer WA 2nd, et al. Ebola virus disease. Nat Rev Dis Primers. 2020;6 (1):13. Published 2020 Feb 20. DOI: 10.1038/s41572-020-0147-3.
- Zhe Zhang, Dan Li, Xiaotong Wang,Yunpeng Wang, Jingyi Lin, Shen Jiang, Zheng Wu, Yingying He, Xin Gao, Zhuo Zhu, Yanlong Xiao, Zhangyi Qu, Yang Li. (2022) Rapid detection of viruses: Based on silver nanoparticles modified with bromine ions and acetonitrile. Chemical Engineering Journal 438, 135589.
- Luo Y, Wu J, Lu J, Xu X, Long W, Yan G, Tang M, Zou L, Xu D, Zhuo P, Si Q, Zheng X. Investigation of COVID-19-related symptoms based on factor analysis. Ann Palliat Med. 2020 Jul;9(4):1851-1858. doi: 10.21037/apm-20-1113. Epub 2020 Jun 22. PMID: 32576016.
- Cori A, Donnelly CA, Dorigatti I, et al. Key data for outbreak evaluation: building on the Ebola experience. Philos Trans R Soc Lond B Biol Sci. 2017;372(1721):20160371. doi:10.1098/rstb.2016.0371.
- Feldmann, H., Jones, S., Klenk, HD. et al. Ebola virus: from discovery to vaccine. Nat Rev Immunol 3, 677–685 (2003). https://doi.org/10.1038/nri1154.
