Mapping Malaria Risk in the New Juaben Municipality of Ghana Using GIS and Remote Sensing Techniques

Bernard Kumi-Boateng

Abstract


Malaria is a life-threatening parasitic disease which is caused by the bites of an infected female Anopheles mosquito and is an issue of grave public health concern. The control of malaria requires effective surveillance systems that will enable efficient malaria response in endemic regions to prevent outbreaks of the disease and to track progress. The objective of this study was to identify mosquito prone areas and develop a malaria risk map for New Juaben Municipality (NJMA) in the Eastern Region of Ghana. Geographic Information System (GIS), Satellite Remote Sensing (SRS) and Analytical Hierarchy Process (AHP) were integrated to develop the malaria risk map which would help in the identification of potential habitats for mosquitoes based on environmental factors that make a place suitable for mosquito breeding. The environmental factors considered were: vegetation, land surface temperature, distance to streams, elevation, slope and topographic wetness index. Mosquito prone areas within the study area were identified and classified into four classes (Very Low, Low, High and Very High) of which the most dominant class was “Low” (56.46 %). A malaria risk map for the study area was then developed and classified into five classes (Very Low, Low, Moderate, High, Very High) of which the most dominant class was “Moderate” (30.17 %). The “High”, “Very High” and “Moderate” areas, together, constitute 56.07 % which is significant. Any efficient malaria response in NJMA should be focused in these areas. This work could be replicated in all the municipalities and districts in Ghana to help prevent outbreak and track the progress of malaria.

 

Keywords: Malaria, GIS, Remote Sensing, Analytical Hierarchy Process, Weighted Overlay


Keywords


Malaria, GIS, Remote Sensing, Analytical Hierarchy Process, Weighted Overlay

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References


Adeola, A. M., Botai, J. O., Olwoch J. M., Rautenbach, H. W., Kalumba, A. M., Tsela, P. L., Adisa, M. O., Wasswa, N. F., Mmtoni, P. and Ssentongo, A. (2015), “Application of Geographical Information System and Remote Sensing in Malaria Research and Control in South Africa: A Review”, Southern African Journal of Infectious Diseases, pp 1-8.

Ahmed, A. (2014), “GIS and Remote Sensing for Malaria Risk Mapping, Ethiopia”, ISPRS Technical Commission VIII Symposium, Hyderabad, India, pp. 156-161.

Anon. (2012), The Composite Budget of New Juaben Municipal Assembly for the 2012 Fiscal Year, Republic of Ghana, 103 pp.

Anon. (2016a), “Malaria Facts”, www.who.int/media centre/factsheets/fs094/en/. Accessed: October 11, 2016.

Anon. (2016b), “Malaria”, https://www.cdc.gov/mal aria/about/faqs.html. Accessed: October 11, 2016.

Anon. (2017b), “Malaria Prevention”, http://www. kebaafrica.org/malaria-prevention-2/. Accessed: February 27, 2017.

Ashenafi, M. (2013), “Design and Water Management of Irrigation Systems to Control Breeding of Anopheles Mosquitoes – A Case Study: Hara Irrigation Project, Arba Minch, Ethiopia”, Unpublished MSc Thesis, Wagenngen University, Wageningen, The Netherlands, pp. 88

Birkman, J. (2007), “Risk and Vulnerability Indicators at Different Scales: Applicability, Usefulness and Policy Implications”, Environmental Hazards, No.7, pp. 20-31.

Chikodzi, D. (2013), "Spatial Modelling of Malaria Risk Zones Using Environmental, Anthropogenic Variables and Geographical Information Systems Techniques", Journal of Geosciences and Geomatics, Vol. 1, No. 1, pp. 8-14.

Chirebvu, E., Chimbari, M. J. and Ngwenya N. B. (2014), “Assessment of Risk Factors Associated with Malaria Transmission in Tubu Village, Northern Botswana”, Malaria Research and Treatment, Vol 2014, Article ID 403069, pp. 1-10.

Cohen, M. J., Ernst, C. K., Lindblade, A. K., Vululu, M. J., John, C. C. and Wilson, L, M (2008), “Topography-derived Wetness Indices are Associated with Household-level Malaria Risk in Two Communities in the Westrn Kenyan Highlands”, Malaria Journal, pp. 8-14.

Denke, P. M., Lloyd, J. E. and Littlefield, J. (1996), “Elevation Distribution of Mosquitoes in a Mountainous Area of Southeastern Wyoming”, Journal of American Mosquito Control Association, Vol 12, No. 1, pp 8-16.

Hearn, G. J. and Griffiths, J. S. (2011), “Landslide Hazard Mapping Assessment”, Land Surface Evaluation for Engineering Practice, The Geological Society Engineering Geology Special Publications No. 18, London, J. S. Griffiths (ed), pp. 43-52.

Kasera, M. O. K. (2016), “Fine Resolution of Malaria Risk Factors and Potential Malaria Risk Prediction – A Case Study of Homa Bay County, Kenya”, MSc Thesis, University of Twente, Enschede, The Netherlands, 78 pp.

Kumi-Boateng, B., Stemn, E., and Mireku-Gyimah, D. (2015), “Modelling of Malaria Risk Areas in Ghana Using Environmental and Anthropogenic Variables – A Spatial Multi-Criteria Approach”, Ghana Mining Journal, Vol. 15, No. 2, pp. 1-10.

Laurie, P (2003), “Disaster Development and Community planning, and public participation: How To Achieve Sustainable Hazard Mitigation, Natural Hazards, 28 (2-3), pp. 211-288.

Moore, I. D., Gessler, P.E., Nielsen, G. A. and Petersen, G. A. (1993), “Terrain Attributes: Estimation Methods and Scale Effects”, In Jakeman, A. J., Beck, M. B and McAleer, M., Modelling Change in Environmental Systems, London: Willey, pp. 189-214.

Saaty, T.L. (1980), The Analytic Hierarchy Process, New York: McGraw Hill, pp. 287.

Saxena, R., Nagpal, B. N., Srivastava, A., Gupta, S.K. and Dash, A. P. (2009), “Application of Spatial Technology in Malaria Research and Control: Some New Insights”, Indian Journal of Medical Research, pp. 125-132.

Sorensen, R., Zinko, U. and Seibert, J. (2006), “On the Calculation of the Topographic Wetness Index: Evaluation of Different Methods Based on Field Observations”, Hydrology and Earth System Sciences, No. 10, pp. 101-112.

Texier, G., Machault, V., Barragti, M., Boutin, J. and Rogier, C (2013), “Environmental Determinant of Malaria Cases Among Travellers”, Malaria Journal, pp 1-11.

Wimberly, C. M., Chuang, T., Henebry, M. G., Liu, Y., Midekisa, A., Seminiguse, P. and Senay, G. (2012), “A Computer System for Forecasting Malaria Epidemic Risk Using Remotely Sensed Environmental Data”, iEMSs 2012, International Congress on Environmental Modelling and Software Managing Resources of a Limited Planet, Sixth Biennial Meeting, Seppelt, R, Voinov, A. A. and Bankamp, D. (Eds.), Leipzig, Germany, 8 pp.

Yazoume, Y., Sankoh, O., Kouyate, B. and Sauerborn, R. (2008), “Environmental Factors and Malaria Transmission Risk Modelling in a Holoendemic Area of Burkina Faso”, BioMed Central, Ashgate Publishing Company, USA, 149 pp.


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