Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach

Ashenafi Senbeta Bedane; Tejitu Kanko Tanto; Tilahun Ferede Asena

doi:doi:10.11648/j.ajtas.20160502.15

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Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach

Ashenafi Senbeta Bedane, Tejitu Kanko Tanto, Tilahun Ferede Asena

Published in American Journal of Theoretical and Applied Statistics (Volume 5, Issue 2)

Received: 19 February 2016 Accepted: 29 February 2016 Published: 18 March 2016

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Abstract

Malaria is one of the major mortality and morbidity incidences in the country. The main aim of the study is to determine the malaria distribution along months of year 2003 to 2012 at Kucha district. The risks of morbidity and mortality associated with malaria are characterized by its distribution in a period of time through month of year. The time series analysis of malaria prevalence in the Kucha district was tested through test of randomness using turning point approach. A time series analysis trend analysis and box-Jenkins models were employed to the data obtained from health centers of Kucha districts. Autocorrelation Function and Partial Autocorrelation Function were adopted to identify the appropriate box-Jenkins models. Autoregressive Integrated Moving Average models were adopted for final data analysis with differencing to attain stationary data. The quadratic trend was found best fit for malaria data and it shows a decreasing trend along a period of month of year 2010 to 2012. Based on the results of model diagnostic checking ARIMA model was found to be significantly fit the data for malaria prevalence forecast. As a result malaria distribution shows seasonal variation in the district especially in the month September to January and July to August. The highest malaria prevalence was observed in December months of each year while, low rate of malaria prevalence was observed in July months of each year.A study recommends that health professionals should pay special attention on December months of each year by suggesting precaution action for those people living in the district.

Published in	American Journal of Theoretical and Applied Statistics (Volume 5, Issue 2)
DOI	10.11648/j.ajtas.20160502.15
Page(s)	70-79
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), 2016. Published by Science Publishing Group

Keywords

Arba Minch, Ethiopia, Gamo Gofa Zone, Kucha District, Malaria Distribution, Time Series Analysis

References

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APA Style

Ashenafi Senbeta Bedane, Tejitu Kanko Tanto, Tilahun Ferede Asena. (2016). Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach. American Journal of Theoretical and Applied Statistics, 5(2), 70-79. https://doi.org/10.11648/j.ajtas.20160502.15

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ACS Style

Ashenafi Senbeta Bedane; Tejitu Kanko Tanto; Tilahun Ferede Asena. Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach. Am. J. Theor. Appl. Stat. 2016, 5(2), 70-79. doi: 10.11648/j.ajtas.20160502.15

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AMA Style

Ashenafi Senbeta Bedane, Tejitu Kanko Tanto, Tilahun Ferede Asena. Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach. Am J Theor Appl Stat. 2016;5(2):70-79. doi: 10.11648/j.ajtas.20160502.15

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@article{10.11648/j.ajtas.20160502.15,
  author = {Ashenafi Senbeta Bedane and Tejitu Kanko Tanto and Tilahun Ferede Asena},
  title = {Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {5},
  number = {2},
  pages = {70-79},
  doi = {10.11648/j.ajtas.20160502.15},
  url = {https://doi.org/10.11648/j.ajtas.20160502.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20160502.15},
  abstract = {Malaria is one of the major mortality and morbidity incidences in the country. The main aim of the study is to determine the malaria distribution along months of year 2003 to 2012 at Kucha district. The risks of morbidity and mortality associated with malaria are characterized by its distribution in a period of time through month of year. The time series analysis of malaria prevalence in the Kucha district was tested through test of randomness using turning point approach. A time series analysis trend analysis and box-Jenkins models were employed to the data obtained from health centers of Kucha districts. Autocorrelation Function and Partial Autocorrelation Function were adopted to identify the appropriate box-Jenkins models. Autoregressive Integrated Moving Average models were adopted for final data analysis with differencing to attain stationary data. The quadratic trend was found best fit for malaria data and it shows a decreasing trend along a period of month of year 2010 to 2012. Based on the results of model diagnostic checking ARIMA model was found to be significantly fit the data for malaria prevalence forecast. As a result malaria distribution shows seasonal variation in the district especially in the month September to January and July to August. The highest malaria prevalence was observed in December months of each year while, low rate of malaria prevalence was observed in July months of each year.A study recommends that health professionals should pay special attention on December months of each year by suggesting precaution action for those people living in the district.},
 year = {2016}
}

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TY  - JOUR
T1  - Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach
AU  - Ashenafi Senbeta Bedane
AU  - Tejitu Kanko Tanto
AU  - Tilahun Ferede Asena
Y1  - 2016/03/18
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DO  - 10.11648/j.ajtas.20160502.15
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 70
EP  - 79
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20160502.15
AB  - Malaria is one of the major mortality and morbidity incidences in the country. The main aim of the study is to determine the malaria distribution along months of year 2003 to 2012 at Kucha district. The risks of morbidity and mortality associated with malaria are characterized by its distribution in a period of time through month of year. The time series analysis of malaria prevalence in the Kucha district was tested through test of randomness using turning point approach. A time series analysis trend analysis and box-Jenkins models were employed to the data obtained from health centers of Kucha districts. Autocorrelation Function and Partial Autocorrelation Function were adopted to identify the appropriate box-Jenkins models. Autoregressive Integrated Moving Average models were adopted for final data analysis with differencing to attain stationary data. The quadratic trend was found best fit for malaria data and it shows a decreasing trend along a period of month of year 2010 to 2012. Based on the results of model diagnostic checking ARIMA model was found to be significantly fit the data for malaria prevalence forecast. As a result malaria distribution shows seasonal variation in the district especially in the month September to January and July to August. The highest malaria prevalence was observed in December months of each year while, low rate of malaria prevalence was observed in July months of each year.A study recommends that health professionals should pay special attention on December months of each year by suggesting precaution action for those people living in the district.
VL  - 5
IS  - 2
ER  -

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Author Information

Ashenafi Senbeta Bedane

School of Mathematical and Statistical Sciences, Department of Statistics, Hawassa University, Hawassa, Ethiopia
Tejitu Kanko Tanto

Department of Statistics, College of Natural and Computational Sciences, Dilla University, Dilla, Ethiopia
Tilahun Ferede Asena

Department of Statistics, College of Natural and Computational Sciences, Arba Minch University, Arba Minch, Ethiopia

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APA Style

Ashenafi Senbeta Bedane, Tejitu Kanko Tanto, Tilahun Ferede Asena. (2016). Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach. American Journal of Theoretical and Applied Statistics, 5(2), 70-79. https://doi.org/10.11648/j.ajtas.20160502.15

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ACS Style

Ashenafi Senbeta Bedane; Tejitu Kanko Tanto; Tilahun Ferede Asena. Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach. Am. J. Theor. Appl. Stat. 2016, 5(2), 70-79. doi: 10.11648/j.ajtas.20160502.15

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AMA Style

Ashenafi Senbeta Bedane, Tejitu Kanko Tanto, Tilahun Ferede Asena. Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach. Am J Theor Appl Stat. 2016;5(2):70-79. doi: 10.11648/j.ajtas.20160502.15

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@article{10.11648/j.ajtas.20160502.15,
  author = {Ashenafi Senbeta Bedane and Tejitu Kanko Tanto and Tilahun Ferede Asena},
  title = {Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {5},
  number = {2},
  pages = {70-79},
  doi = {10.11648/j.ajtas.20160502.15},
  url = {https://doi.org/10.11648/j.ajtas.20160502.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20160502.15},
  abstract = {Malaria is one of the major mortality and morbidity incidences in the country. The main aim of the study is to determine the malaria distribution along months of year 2003 to 2012 at Kucha district. The risks of morbidity and mortality associated with malaria are characterized by its distribution in a period of time through month of year. The time series analysis of malaria prevalence in the Kucha district was tested through test of randomness using turning point approach. A time series analysis trend analysis and box-Jenkins models were employed to the data obtained from health centers of Kucha districts. Autocorrelation Function and Partial Autocorrelation Function were adopted to identify the appropriate box-Jenkins models. Autoregressive Integrated Moving Average models were adopted for final data analysis with differencing to attain stationary data. The quadratic trend was found best fit for malaria data and it shows a decreasing trend along a period of month of year 2010 to 2012. Based on the results of model diagnostic checking ARIMA model was found to be significantly fit the data for malaria prevalence forecast. As a result malaria distribution shows seasonal variation in the district especially in the month September to January and July to August. The highest malaria prevalence was observed in December months of each year while, low rate of malaria prevalence was observed in July months of each year.A study recommends that health professionals should pay special attention on December months of each year by suggesting precaution action for those people living in the district.},
 year = {2016}
}

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TY  - JOUR
T1  - Malaria Distribution in Kucha District of Gamo Gofa Zone, Ethiopia: A Time Series Approach
AU  - Ashenafi Senbeta Bedane
AU  - Tejitu Kanko Tanto
AU  - Tilahun Ferede Asena
Y1  - 2016/03/18
PY  - 2016
N1  - https://doi.org/10.11648/j.ajtas.20160502.15
DO  - 10.11648/j.ajtas.20160502.15
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 70
EP  - 79
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20160502.15
AB  - Malaria is one of the major mortality and morbidity incidences in the country. The main aim of the study is to determine the malaria distribution along months of year 2003 to 2012 at Kucha district. The risks of morbidity and mortality associated with malaria are characterized by its distribution in a period of time through month of year. The time series analysis of malaria prevalence in the Kucha district was tested through test of randomness using turning point approach. A time series analysis trend analysis and box-Jenkins models were employed to the data obtained from health centers of Kucha districts. Autocorrelation Function and Partial Autocorrelation Function were adopted to identify the appropriate box-Jenkins models. Autoregressive Integrated Moving Average models were adopted for final data analysis with differencing to attain stationary data. The quadratic trend was found best fit for malaria data and it shows a decreasing trend along a period of month of year 2010 to 2012. Based on the results of model diagnostic checking ARIMA model was found to be significantly fit the data for malaria prevalence forecast. As a result malaria distribution shows seasonal variation in the district especially in the month September to January and July to August. The highest malaria prevalence was observed in December months of each year while, low rate of malaria prevalence was observed in July months of each year.A study recommends that health professionals should pay special attention on December months of each year by suggesting precaution action for those people living in the district.
VL  - 5
IS  - 2
ER  -

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