Trend Analysis Forecast of Malaria Cases in Private Hospitals in Nigeria

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Published: Jun 30, 2022
Keywords:
Trend Analysis Forecast Malaria Cases Private Hospital Trend Models

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NKPORDEE, Lekia
Ignatius Ajuru University of Education, Rumuolumeni, Port Harcourt - Nigeria.
https://orcid.org/0000-0002-8750-066X
OGOLO, Ibinabo Magnus
Rivers State College of Health Science and Management Technology, Rumueme, Port Harcourt, Nigeria.
https://orcid.org/0000-0003-4182-9408

Abstract

The comparative examination of trend models was investigated in this paper. On malaria cases in private hospitals in Nigeria. Four time series trend models were fitted using monthly data from 2015 to 2021: linear trend model, quadratic trend model, exponential trend model, and s-curve trend model. The s-curve trend model was determined to have the least MAD and matched the data the best. The s-curve trend model was used to produce a six-month projection of malaria cases in Nigerian private hospitals, which revealed that malaria cases in the hospitals would idecline during the following six months, from January to June 2022.

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How to Cite
Nkpordee, L., & Ogolo, I. M. (2022). Trend Analysis Forecast of Malaria Cases in Private Hospitals in Nigeria. African Journal of Advances in Science and Technology Research, 4(1), 125–134. Retrieved from https://publications.afropolitanjournals.com/index.php/ajastr/article/view/172
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Vol. 4 No. 1 (2022): JUNE ISSUE
Section
Articles
Author Biographies

NKPORDEE, Lekia, Ignatius Ajuru University of Education, Rumuolumeni, Port Harcourt - Nigeria.

Department 0f Mathematics/Statistics,

Ignatius Ajuru University of Education, Rumuolumeni,

Port Harcourt, Rivers State, Nigeria.

OGOLO, Ibinabo Magnus, Rivers State College of Health Science and Management Technology, Rumueme, Port Harcourt, Nigeria.

School of Foundation Studies,

Rivers State College of Health Science and Management Technology,

Rumueme, Port Harcourt, Nigeria.

References

Briet O. J.T., Vounatsou P. & Amerasinghe, P. H., (2008). Malaria seasonality and rainfall seasonality in Sri Lanka are correlated in space. Geospatial Health, 2(2), 183-190

Brown, V., Issak, M.A., Rossi, M., Barboza, P. & Paugam, A. (2002). Epidemic of malaria in North Eastern Kenya. Lancet 352, 1356–1357.

Castilla, R. F. & Sawyer, D. O. (1993). Malária rates and fate: A socioeconomic study of malaria in Brazil. Social Science and Medicine, 37(9): 1137–1145.

Contreras, J., Espinola, R., Nogales, F.J., & Antonio, J. (2003). ARIMA models to predict next-day electricity prices. IEEE Transactions on power systems, 18(3), 1014-1020.

Eke, C. N., Egwim, K. C. Igbo, C. A. & Onuoha, D. O. (2015). Comparative analysis of three time series trend models on gross domestic product in Nigeria. European Journal of Business and Management, 7(3), ISSN 2222-2839

Guerrero, V.M. (2003). Combining multiple time series predictors: A useful inferential procedure. Journal of Statistical Planning and Inference, 116 (1), 249-276.

Kendall, M. G. & Stuart, A. (1966). The advanced theory of statistics: design and analysis and time-series. Charles Griffin & Co. Ltd. London, United Kindom.

Lin, H., Lu, L., Tian, L., Zhou, S., Wu, H., B, Y., Ho, S. C. & Liu, Q. (2009). Spatial and temporal distribution of falciparum malaria in China. Malaria Journal, 8:130 doi:10.1186/1475-2875-8-130

Lindsay W.S & Birley M., (2004). Rural development and malaria control in subsahara Africa”, EcoHealth, 1(2). 129-137

Nkpordee, L. & Nduka, W. (2018). Application of time series analysis on the forecasting of the outbreak of malaria epidemic in Nigeria. International Journal of Statistics and Applied Mathematics, 3(6): 98-105.

Pattanayak, S.K., Mercer D.E., Sills, E. & Yang, J. C. (2003). Taking stock of the agroforestry adoption studies. Agroforestry Systems 57 (3): 173-186.

Reeder, J.C. (2001). Towards a malaria vaccine for Papua New Guinea. PNG Med J, 44, 17-23.

Sharma, V.M., Chopra, R., Ghosh, I., & Ganesan, K. (2001). Quantitative target display: a method to screen yeast mutants conferring quantitative phenotypes by 'mutant DNA fingerprints'. Nucleic Acids Res, 29 (17): E86-6

Sudhakar, P., & Subramani, P., (2007). Literature review: insights into formulating a protective malaria medicine. Journal of Young Investigators, 16(10).

Worrall, E., Basu, S. & Hanson, K., (2003). The relationship between socio-economic status and malaria. London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.