Setting the malaria epidemic threshold in the Central Health Region of Burkina Faso using historical data

Setting malaria epidemic threshold

Authors

  • Jean Claude Romaric Pingdwindé Ouédraogo1,2* 1.Department of Traditional Medicine and Pharmacopoeia, and Pharmacy, Research Institute for Health Sciences (IRSS), Ouagadougou, Burkina Faso 2.School of Public Health, University of Ghana, Legon/Accra, Ghana
  • Eric Mishio Bawa2 2.School of Public Health, University of Ghana, Legon/Accra, Ghana
  • Issouf Yaméogo3 3.Joseph KI-ZERBO University, Ouagadougou, Burkina Faso
  • Dennis Tabiri2 2.School of Public Health, University of Ghana, Legon/Accra, Ghana
  • Terence Acheliu Longla2 2.School of Public Health, University of Ghana, Legon/Accra, Ghana
  • Youssouf Diarra2 2.School of Public Health, University of Ghana, Legon/Accra, Ghana
  • Joseph W. Jatta2 2.School of Public Health, University of Ghana, Legon/Accra, Ghana
  • Narcisse Tounaikok2 2.School of Public Health, University of Ghana, Legon/Accra, Ghana
  • Daniel N. Nebongo2 2.School of Public Health, University of Ghana, Legon/Accra, Ghana

Keywords:

malaria, threshold, epidemic, mean, median, cumulative sum

Abstract

Introduction: Malaria has been endemic in Burkina Faso. Setting epidemic thresholds is then crucial for early detection and responses. We compared three methods for epidemic detection in the Central Health Region of Burkina Faso using historical data between 2013-2016.

Methodology: Monthly malaria data from 2013 to 2015 were used as the baseline to set the thresholds. Three methods were applied: quartiles, mean + 2 Standard Deviation (SD), and cumulative sum (C-sum). The median and third quartile, as well
as the mean and the mean + 2 SD were calculated per month, for the baseline period, and plotted in a graph with the monthly malaria cases of 2016. For each month, the number of cases of the previous and following months between 2013-2015 was summed up and divided by 9. These monthly average numbers were refined with the 1.96 SD and plotted with the 2016 monthly malaria cases. Any time that the 2016 line crossed the quartiles, the mean and the C-sum thresholds, an unexpected increase in malaria cases was caught.
Results: Cases were higher every month of 2016 compared to the corresponding months of the previous three years. The Quartiles method detected the whole 2016 year as unusual. Using the mean + 2SD method, malaria cases raised unusually in
2016, except for August, whereas the C-sum + 1.96 SD method did not detect outbreaks in July.
Conclusions: Not dependent on extreme values, the quartiles method seems more reliable to capture an abnormal rise in malaria cases. This increase in cases would be due to the free healthcare policy for children and pregnant women launched in 2016. Abnormal rise should always be investigated before confirming an epidemic.

Published

2024-04-25

How to Cite

Ouédraogo1,2* , J. C. R. P. ., Bawa2 , E. M. ., Yaméogo3 , I. ., Tabiri2 , D. ., Longla2 , T. A. ., Diarra2 , Y. ., Jatta2 , J. W. ., Tounaikok2 , N. ., & Nebongo2, D. N. . (2024). Setting the malaria epidemic threshold in the Central Health Region of Burkina Faso using historical data: Setting malaria epidemic threshold. Sciences De La Santé, 45(2), 27–42. Retrieved from https://revuesciences-techniquesburkina.org/index.php/sciences_de_la_sante/article/view/1160

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