INTERNATIONAL JOURNAL OF MEDICAL EVALUATION AND PHYSICAL REPORT (IJMEPR )
E-ISSN 2579-0498
P-ISSN 2695-2181
VOL. 8 NO. 6 2024
DOI: 10.56201/ijmepr.v8.no6.2024.pg123.130
Kate, Ijeoma Ndupu, Prof. Adelani Tijani, Dr. Daniel Ekpah and Mrs Chioma Nkwocha
The study assessed Knowledge and Utilization of Information Technology for Disease Surveillance among public health practitioners in Obio-Akpor LGA Port Harcourt. A sample of 267 health workers was used for the study. Descriptive research design was used for the study. The study used four research questions with one hypothesis. One research instrument was used to collect the data. The instrument was subjected to a reliability testing using test- retest method. The data collected was Pearson Product Moment Correlation and reliability coefficient of 0.89 was obtained showing that the instrument is reliable. The research questions were answered using descriptive statistics of percentage, mean and charts while the hypothesis was tested using Pearson Product Moment. The results revealed that; 15.5% of the respondents were between the age of 20 – 30years, 35.3% were between 31 – 40years, 27.4% were between 41 – 50years while 19.8% were between 51years and above, 61.4% of the respondents had B.Sc., 22.5% had M.Sc. while 16.1% had PhD. The study further revealed that the Information Technology tools used for Disease Surveillance among public health practitioners in Obio- Akpor LGA were mobile app, web-based surveillance system amongst others, the level of knowledge of information technology tools and systems for disease surveillance among public health practitioners in Obio-Akpo LGA was moderate at 53.1%, the level of utilization of information technology tools in Disease Surveillance among public health practitioners in Obio-Akpor LGA was moderate at 53.8% and that the challenges militating against the use of Information Technology tools used for Disease Surveillance among public health practitioners in Obio-Akpor LGA include, network issues, low budgets, lack of trainings among others. The study concluded that Knowledge and Utilization of Information Technology for Disease Surveillance among public health practitioners in Obio-Akpor
Bragazzi, N., Dai, H., Damiani, G., Behzadifar, M., Martini, M., & Wu, J. (2020). How big
data and artificial intelligence can help better manage the covid-19 pandemic.
International Journal of Environmental Research and Public Health, 17(9), 3176.
https://doi.org/10.3390/ijerph17093176.
Carneiro, H. and Mylonakis, E. (2019). Google trends: a web?based tool for real?time
surveillance of disease outbreaks. Clinical Infectious Diseases, 49(10), 1557-1564.
https://doi.org/10.1086/630200
Isere, E., Fatiregun, A., & Ajayi, I. (2015). An overview of disease surveillance and
notification system in nigeria and the roles of clinicians in disease outbreak
prevention
and
control.
Nigerian
Medical
Journal,
56(3),
https://doi.org/10.4103/0300-1652.160347.
Keller, M., Blench, M., Tolentino, H., Freifeld, C., Mandl, K., Mawudeku, A., … &
Brownstein, J. (2009). Use of unstructured event-based reports for global infectious
disease
surveillance.
Emerging
Infectious
Diseases,
15(5),
689-695.
https://doi.org/10.3201/eid1505.081114.
Masiira, B., Nakiire, L., Kihembo, C., Katushabe, E., Natseri, N., Nabukenya, I., … &
Nsubuga, P. (2019). Evaluation of integrated disease surveillance and response (idsr)
core and support functions after the revitalisation of idsr in uganda from 2012 to 2016.
BMC Public Health, 19(1). https://doi.org/10.1186/s12889-018-6336-2.
Oyebanji, O., Abba, F., Akande, O., Aniaku, E., Abubakar, A., Aderinola, O., & Ihekweazu, C.
(2021). Building local capacity for emergency coordination: establishment of
subnational public health emergency operations centres in nigeria. BMJ Global
Health, 6(10), e007203. https://doi.org/10.1136/bmjgh-2021-007203.
Reynolds, E., Martel, L., Bah, M., Bah, M., Bah, M., Barry, B., … & MacDonald, P. (2022).
Implementation of dhis2 for disease surveillance in guinea: 2015–2020. Frontiers in
Public Health, 9. https://doi.org/10.3389/fpubh.2021.761196.
Rouleau, G., Gagnon, M.P., & Côté J. (2015). Impacts of information and communication
Secginli, S., Erdogan, S. and Monsen, K.A. (2014) Attitudes of health professionals
Settings. CIN: Computers, Informatics, Nursing; 39(12):p 883-889.
Sheikhali, S., Abdallat, M., Mabdalla, S., Qaseer, B., Khorma, R., Malik, M., … & Haskew,
J. (2016). Design and implementation of a national public health surveillance system
in
jordan.
International
Journal
of
Medical
Informatics,
88,
58-61.
https://doi.org/10.1016/j.ijmedinf.2016.01.003.
Silenou, B., Verset, C., Kaburi, B., Leuci, O., Ghozzi, S., Duboudin, C., … & Krause, G.
(2022). A novel tool for real-time estimation of epidemiological parameters of
communicable diseases using contact-tracing data: development and deployment.
Jmir Public Health and Surveillance, 8(5), e34438. https://doi.org/10.2196/34438
Siniscalchi, A. and Evans, B. (2015). Ebola, enterovirus, mers, novel flu, and other challenges
for public health surveillance practitioners. Online Journal of Public Health
Informatics, 7(1). https://doi.org/10.5210/ojphi.v7i1.5718
WHO. (2019). Recommendations on digital interventions for health system strengthening:
web supplement 2: summary of findings and GRADE tables no. WHO/RHR/19.7.