Computational Biology and Bioinformatics

| Peer-Reviewed |

An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults

Received: 19 February 2018    Accepted: 07 March 2018    Published: 27 March 2018
Views:       Downloads:

Share This Article

Abstract

Zika virus infection is a disease that may be misdiagnosed due to the semblance it shares with other arboviral diseases such as dengue, yellow fever, and Chikungunya. Till date it has been difficult to model a computerized solution for its detection owing to the foregoing characteristics. This paper is aimed at studying the prevalence and incidence of the virus in a bid to analyze and create an informatics model for its detection, diagnosis and management. To achieve its objective, the object-based analysis was employed. Data collection involved a descriptive synthesis of the laid down diagnostic procedures by the world health organization (WHO) and the orthodox medical practices in Nigeria. The result of the analysis generated specifications including a component model and analysis use cases that would be used to implement the developed model in the second part of this paper.

DOI 10.11648/j.cbb.20180601.11
Published in Computational Biology and Bioinformatics (Volume 6, Issue 1, June 2018)
Page(s) 1-20
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Zika Virus, Dengue Virus, Automated Diagnosis, Informatics, Informatics Model

References
[1] Nigeria Centre for Disease Control (2016) Public Health Risk Assessment of Zika Virus in Nigeria and Interim recommendations. Abuja, Nigeria: Nigeria Centre for Disease Control, Nigeria, Federal Ministry of Health, National Health Promotion Policy Draft.
[2] World Health Organization (2016) "WHO Director-General summarizes the outcome of the Emergency Committee regarding clusters of microcephaly and Guillain-Barré syndrome" [online]. Available at: http://www.who.int/mediacentre/news/statements/2016/emergency-committee-Zika-microcephaly/en/ [Accessed 10 February 2016].
[3] Paixão, E. S., Barreto, F., Teixeira, M. G., Costa M. C., and Rodrigues L. C. (2016) "History, Epidemiology, and Clinical Manifestations of Zika: A Systematic Review.", American journal of Public Health, Vol. 106, Issue 4, pp 106-112. doi: 10.2105/AJPH.2016.303112.
[4] World Health Organization (2017) "Zika virus country classification scheme" [online]. Available at:http://apps.who.int/iris/bitstream/10665/254619/1/WHO-ZIKV-SUR-17.1-eng.pdf?ua=1 [Accessed 17 February 2018].
[5] Centres for Disease Control and Prevention (2016) "Country Classification Technical Guidance" [online]. Available at: https://wwwnc.cdc.gov/travel/page/Zika-country-classification [Accessed 17 February 2018].
[6] FAGBAMI, A. H. (1979) "Zika virus infections in Nigeria: virological and seroepidemiological investigations in Oyo State", Journal of Hygience, Vol. 83, No. 2, London.
[7] Olson, J. G., Ksiazek, T. G., Suhandiman, & Triwibowo (1981) "Zika virus, a cause of fever in Central Java, Indonesia", Trans R Soc Tropical Medicine Hygiene, Vol. 75, Issue 3: pp 389-393.
[8] Ramzy, A. (2016) "Experts Study Zika’s Path From First Outbreak in Pacific" [online], New york times: Available at: https://www.nytimes.com/2016/02/11/world/asia/Zika-virus-yap-island.html.
[9] Duffy M. R. et al (2009) "Zika virus outbreak on Yap Island, Federated States of Micronesia", New England Journal of Medicine, Vol. 360, Issue 24, pp 536-43. doi: 10.1056/NEJMoa0805715.
[10] Blázquez, A. and Saiz, J. (2016) "Neurological manifestations of Zika virus infection", World Journal of Virology, Vol. 5, No.4, pp 135–143. doi: 10.5501/wjv.v5.i4.135.
[11] European Centre for Disease Control (2016) "Zika virus infection from 2014 onwards"[online]. Available at: https://ecdc.europa.eu/en/Zika-virus-infection.
[12] Hennessey, M., Fischer, M., Staples, J. E. (2016) "Zika virus spreads to new areas-region of the Americas", Morbidity and Mortality Weekly Report.
[13] Salvador, F. S., and Fujita, D. M. (2016) "Entry routes for Zika virus in Brazil after 2014 World Cup: new possibilities", Travel Medicine and Infectious Disease Journal, Vol. 14, pp 49-51.
[14] Goorhuis, A., Eije KJ von, Douma, R. A. (2016) "Zika virus and the risk of imported infection in returned travelers: implications for clinical care", Travel Medicine and Infectious Disease Journal, Vol. 14, pp 13-15.
[15] Pan American Health Organization/World Health Organization (2016). "Regional Zika Epidemiological Update (Americas)" [online]. Available at http://www.paho.org/hq/index.php?option=com_content&view=article&id=11599&Itemid=41691.
[16] Zammarchi, L., Stella, G. and Mantella, A. (2016) "Zika virus infections imported to Italy: clinical, immunological and virological findings, and public health implications", Journal of Clinical Virology, Vol. 63, pp 32-35.
[17] Beltrán-Silva, S. L., Chacón-Hernández, S. S., Moreno-Palacios, E. and Pereyra-Molina, J. A. (2016) "Clinical and differential diagnosis: Dengue, Chikungunya and Zika", Rev Med Hosp Gen Méx. http://dx.doi.org/10.1016/j.hgmx.2016.09.011.
[18] Pan American Health organization /World health Organization (2017) "TOOL FOR THE DIAGNOSIS AND CARE OF PATIENTS WITH SUSPECTED ARBOVIRAL DISEASES", Pan American Sanitary Bureau, Regional Offce of the World Health Organization Washington, D. C.
[19] JDemiris, G. et al (2008) "Patient-centered Applications: Use of Information Technology to Promote Disease Management and Wellness. A White Paper by the AMIA Knowledge in Motion Working Group", Journal of the American Medical Informatics Association, Vol 15 (1): pp 8–13. doi: 10.1197/jamia. M2492.
[20] Berner, E. S.; Tonya J. L. (2007) Clinical Decision Support Systems: Theory and Practice (2nd ed.), New York: Springer Science and Business Media.
[21] Wagner E. H., Austin, B. T., Von Korff M. (1996) "Improving outcomes in chronic illness", Managed Care Quarterly, Vol. 4, No. 2, pp 12-25.
[22] Barr, V. J., Robinson, S., Marin-Link, B., Underhill, L., Dotts, A., Ravensdale, D., et al. (2003). The Expanded Chronic Care Model: An integration of concepts and strategies: from population health promotion and the Chronic Care Model. Hospital Quarterly, Vol. 7, pp 73-82. [Online]. Available at: http://blogs.usask.ca/SHORE/Chronic%20Care%20Model.pdf
[23] Riaño, D., Bohada, J. A., Collado, A, López-Vallverdú, J. A. (2013) "MPM: A knowledge-based functional model of medical practice", Journal of Biomedical Informatics, Vol. 46, Issue 3, pp 379-87. doi: 10.1016/j.jbi.2013.01.007.
[24] Maurer, D. (2016, March 20). World Health Organization launches Zika app for physicians and health workers [online]. Available at: https://www.imedicalapps.com/2016/03/world-health-organization-Zika-app/.
[25] Lee, A. S. & Liebenau, J. (1997). "Information systems and Qualitative Research", Iinternational conference on Information systems and qualitative research, pp. 1-8, London, UK: Chapman & Hall, Ltd. Available at: http://www.people.vcu.edu/~aslee/ifipwg82.pdf.
[26] Nunamaker, J. F., Chen, M., and Purdin, T. D. M. (1991). "Systems Development in Information Systems Research", Journal of Management Information Systems, Vol. 7, Issue 1, pp 89-106.
[27] Walls, J., Widmeyer, G., and El Sawy, O. (1992). "Building an Information System Design Theory for Vigilant EIS", Information Systems Research, Vol. 3, Issue 1, pp 36-59.
Author Information
  • College of Natural and Applied Sciences, Wellspring University, Benin City, Nigeria

  • School of Computing and Information Technology, Kampala International University, Kampala, Uganda

Cite This Article
  • APA Style

    Nwankwo Wilson Nnamdi, Chinecherem Umezuruike. (2018). An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults. Computational Biology and Bioinformatics, 6(1), 1-20. https://doi.org/10.11648/j.cbb.20180601.11

    Copy | Download

    ACS Style

    Nwankwo Wilson Nnamdi; Chinecherem Umezuruike. An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults. Comput. Biol. Bioinform. 2018, 6(1), 1-20. doi: 10.11648/j.cbb.20180601.11

    Copy | Download

    AMA Style

    Nwankwo Wilson Nnamdi, Chinecherem Umezuruike. An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults. Comput Biol Bioinform. 2018;6(1):1-20. doi: 10.11648/j.cbb.20180601.11

    Copy | Download

  • @article{10.11648/j.cbb.20180601.11,
      author = {Nwankwo Wilson Nnamdi and Chinecherem Umezuruike},
      title = {An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults},
      journal = {Computational Biology and Bioinformatics},
      volume = {6},
      number = {1},
      pages = {1-20},
      doi = {10.11648/j.cbb.20180601.11},
      url = {https://doi.org/10.11648/j.cbb.20180601.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.cbb.20180601.11},
      abstract = {Zika virus infection is a disease that may be misdiagnosed due to the semblance it shares with other arboviral diseases such as dengue, yellow fever, and Chikungunya. Till date it has been difficult to model a computerized solution for its detection owing to the foregoing characteristics. This paper is aimed at studying the prevalence and incidence of the virus in a bid to analyze and create an informatics model for its detection, diagnosis and management. To achieve its objective, the object-based analysis was employed. Data collection involved a descriptive synthesis of the laid down diagnostic procedures by the world health organization (WHO) and the orthodox medical practices in Nigeria. The result of the analysis generated specifications including a component model and analysis use cases that would be used to implement the developed model in the second part of this paper.},
     year = {2018}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults
    AU  - Nwankwo Wilson Nnamdi
    AU  - Chinecherem Umezuruike
    Y1  - 2018/03/27
    PY  - 2018
    N1  - https://doi.org/10.11648/j.cbb.20180601.11
    DO  - 10.11648/j.cbb.20180601.11
    T2  - Computational Biology and Bioinformatics
    JF  - Computational Biology and Bioinformatics
    JO  - Computational Biology and Bioinformatics
    SP  - 1
    EP  - 20
    PB  - Science Publishing Group
    SN  - 2330-8281
    UR  - https://doi.org/10.11648/j.cbb.20180601.11
    AB  - Zika virus infection is a disease that may be misdiagnosed due to the semblance it shares with other arboviral diseases such as dengue, yellow fever, and Chikungunya. Till date it has been difficult to model a computerized solution for its detection owing to the foregoing characteristics. This paper is aimed at studying the prevalence and incidence of the virus in a bid to analyze and create an informatics model for its detection, diagnosis and management. To achieve its objective, the object-based analysis was employed. Data collection involved a descriptive synthesis of the laid down diagnostic procedures by the world health organization (WHO) and the orthodox medical practices in Nigeria. The result of the analysis generated specifications including a component model and analysis use cases that would be used to implement the developed model in the second part of this paper.
    VL  - 6
    IS  - 1
    ER  - 

    Copy | Download

  • Sections