Table of Contents
Malaria Research and Treatment
Volume 2018, Article ID 6124321, 11 pages
https://doi.org/10.1155/2018/6124321
Research Article

Modelling Trends of Climatic Variability and Malaria in Ghana Using Vector Autoregression

1Department of Mathematics and Statistics, University of Energy and Natural Resources, P.O. Box 214, Sunyani, Ghana
2Office of Deputy Vice Chancellor, Catholic University of Eastern Africa, P.O. Box 62157-00200, Nairobi, Kenya

Correspondence should be addressed to Sylvia Ankamah; hg.ude.rneu@hamakna.aivlys

Received 11 July 2017; Accepted 19 April 2018; Published 29 May 2018

Academic Editor: Sasithon Pukrittayakamee

Copyright © 2018 Sylvia Ankamah et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. W. Baah-Boateng and E. Osei-Assibey, “2010 Annual millennium development goals report,” Final Draft Report, 2012. View at Google Scholar
  2. E. T. Ngarakana-Gwasira, C. P. Bhunu, M. Masocha, and E. Mashonjowa, “Assessing the role of climate change in malaria transmission in Africa,” Malaria Research and Treatment, vol. 2016, pp. 1–7, 2016. View at Publisher · View at Google Scholar
  3. A. Arab, M. C. Jackson, and C. Kongoli, “Modelling the effects of weather and climate on malaria distributions in West Africa,” Malaria Journal, vol. 13, no. 1, p. 126, 2014. View at Publisher · View at Google Scholar
  4. World Health Organisation (WHO), “World Malaria Report,” http://www.who.int/malaria/publications/world-malaria-report-2015/wmr2015-without-profiles.pdf?ua=1, 2015.
  5. World Health Organisation (WHO), “World Malaria Report,” Regional Profiles, 2015, http://www.who.int/malaria/publications/world-malaria-report-2015/wmr2015-profiles.pdf?ua=1. View at Google Scholar
  6. GHS, Annual report of Ghana Health Services, Accra: Ghana Health Services (GHS), Accra, 2011, http://www.ghanahealthservice.org/ghs-item-details.php?cid=5&;scid=52&;iid=94.
  7. “National Malaria Control Programme: 2015 Annual Report,” http://www.ghanahealthservice.org/downloads/NMCP_2015_ANNUAL_REPORT.pdf. 2016.
  8. D. J. Rogers and S. E. Randolph, “The global spread of malaria in a future, warmer world,” Science, vol. 289, no. 5485, pp. 1763–1766, 2000. View at Publisher · View at Google Scholar
  9. A. Haines, R. S. Kovats, D. Campbell-Lendrum, C. Corvalßn, and C. Corvalán, “Climate change and human health: impacts, vulnerability and public health,” in Public Health, vol. 120, pp. 585–596, URL http, 2006, http://ac.els-cdn.com/S0033350606000059/1-s2.0-S0033350606000059-main.pdf?_tid=ba1891d0-4231-11e7-b4a3-00000aacb361&;acdnat=1495816880_a52e8c8277b2bbce10a4c2fcfec484d9. View at Google Scholar
  10. A. K. Githeko, S. W. Lindsay, U. E. Confalonieri, and J. A. Patz, “Climate change and vector-borne diseases: a regional analysis,” Bulletin of the World Health Organization, vol. 78, no. 9, pp. 1136–1147, 2000. View at Google Scholar · View at Scopus
  11. M. P. J. Palut and O. F. Canziani, “Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change,” http://www.ipcc.ch/publications_and_data/publications_ipcc_fourth_assessment_report_wg2_report_impacts_adaptation_and_vulnerability.htm, 2007.
  12. S. Adu-Prah and E. K. Tetteh, “Spatiotemporal analysis of climate variability impacts on malaria prevalence in Ghana,” Applied Geography, vol. 60, pp. 266–273, 2015. View at Publisher · View at Google Scholar · View at Scopus
  13. L. Sena, W. Deressa, and A. Ali, “Correlation of climate variability and malaria: a retrospective comparative study, Southwest Ethiopia,” Ethiopian Journal of Health Sciences, vol. 25, no. 2, p. 129, 2015. View at Publisher · View at Google Scholar
  14. V. E. Weli and S. I. Efe, “Climate and epidemiology of malaria in port harcourt region, Nigeria,” American Journal of Climate Change, vol. 04, no. 01, pp. 40–47, 2015. View at Publisher · View at Google Scholar
  15. A. Omonijo, A. Matzarakis, O. Oguntoke, and C. Adeofun, “Influence of weather and climate on malaria occurrence based on Human-Biometeorological methods in Ondo State, Nigeria,” Journal of Environmental Science and Engineering, vol. 5, 2011, http://www.davidpublishing.com/davidpublishing/Upfile/10/11/2011/2011101166566993.pdf. View at Google Scholar
  16. U. Haque, M. Hashizume, G. E. Glass et al., “The role of climate variability in the spread of malaria in Bangladeshi Highlands,” PLoS ONE, vol. 5, no. 12, p. e14341, 2010. View at Publisher · View at Google Scholar
  17. E. O. Asare and L. K. Amekudzi, “Assessing climate driven malaria variability in Ghana using a regional scale dynamical model,” Climate, vol. 5, no. 1, Article ID 20, 2017. View at Publisher · View at Google Scholar · View at Scopus
  18. E. L. Darkoh, J. A. Larbi, and E. A. Lawer, “A weather-based prediction model of malaria prevalence in amenfi west district, Ghana,” Malaria Research and Treatment, vol. 2017, pp. 1–8, 2017. View at Publisher · View at Google Scholar
  19. N. A. Klutse, F. Aboagye-Antwi, K. Owusu, and Y. Ntiamoa-Baidu, “Assessment of patterns of climate variables and malaria cases in two ecological zones of Ghana,” Open Journal of Ecology, vol. 04, no. 12, pp. 764–775, 2014. View at Publisher · View at Google Scholar
  20. A. C. Krefis, N. G. Schwarz, A. Krüger et al., “Modeling the relationship between precipitation and malaria incidence in children from a holoendemic area in Ghana,” The American Journal of Tropical Medicine and Hygiene, vol. 84, no. 2, pp. 285–291, 2011. View at Publisher · View at Google Scholar · View at Scopus
  21. C. A. Sims, “Macroeconomics and reality,” Econometrica, vol. 48, no. 1, pp. 1–48, 1980. View at Publisher · View at Google Scholar
  22. C. W. J. Granger, “Investigating causal relations by econometric models and cross-spectral methods,” Econometrica, vol. 37, no. 3, pp. 424–238, 1969. View at Publisher · View at Google Scholar
  23. H. Lütkepohl, Introduction to Multiple Time Series Analysis, Springer-Verlag, Berlin, Germany, 1993. View at Publisher · View at Google Scholar · View at MathSciNet
  24. D. A. Dickey and W. A. Fuller, “Distribution of the estimators for autoregressive time series with a unit root,” Journal of the American Statistical Association, vol. 74, no. 366, pp. 427–431, 1979. View at Publisher · View at Google Scholar
  25. H. Akaike, “Canonical correlation analysis of time series and the use of an information criterion,” in System Identification Advances and Case Studies, vol. 126 of Mathematics in Science and Engineering, pp. 27–96, Elsevier, 1976. View at Publisher · View at Google Scholar
  26. E. J. Hannan and B. G. Quinn, “The determination of the order of an autoregression,” Journal of the Royal Statistical Society. Series B (Methodological), vol. 41, no. 2, pp. 190–195, 1979. View at Google Scholar
  27. H. Akaike, “Maximum likelihood identification of Gaussian autoregressive moving average models,” Biometrika, vol. 60, no. 2, p. 255, 1973. View at Publisher · View at Google Scholar
  28. G. Schwarz, “Estimating the dimension of a model,” The Annals of Statistics, vol. 6, no. 2, pp. 461–464, 1978. View at Publisher · View at Google Scholar · View at MathSciNet
  29. C. D. Lewis, Demand forecasting and inventory control: a computer aided learning approach, Routledge, 1997.
  30. K. Komen, J. Olwoch, H. Rautenbach, J. Botai, and A. Adebayo, “Long-run relative importance of temperature as the main driver to malaria transmission in limpopo province, South Africa: a simple econometric approach,” EcoHealth, vol. 12, no. 1, pp. 131–143, 2015. View at Publisher · View at Google Scholar · View at Scopus
  31. G. E. P. Box and G. C. Tiao, “Intervention analysis with applications to economic and environmental problems,” Journal of the American Statistical Association, vol. 70, no. 349, pp. 70–79, 1975. View at Publisher · View at Google Scholar · View at MathSciNet