Geospatial Analysis of Malaria Prevalence among Children Under Five Years in Jigawa State, North West, Nigeria

Authors

  • Ismaila Ibrahim Yakudima Department of Geography, Aliko Dangote University of Science and Technology, Wudil, Kano, Nigeria
  • Yusuf Muhammad Adamu Department of Geography, Bayero University, Kano, Nigeria
  • Narimah Samat Department of Geography, University Sains Malaysia
  • Murtala Uba Mohammed Department of Geography, Bayero University, Kano, Nigeria
  • Ishaq Aliyu Abdulkarim Bayero University, Kano
  • Nura Ibrahim Hassan Department of Geography, Bayero University, Kano, Nigeria

DOI:

https://doi.org/10.4314/ajbr.v27i2.7

Keywords:

GIS, Jigawa, Malaria risk, weighted overlay

Abstract

Malaria is a contagious disease whose spread is influenced by a number of environmental and anthropogenic factors. It is still regarded as a serious public health concern especially in Africa south of the Sahara. The goal of this study was to use environmental and anthropogenic parameters to create malaria risk map in Jigawa state using GIS (Geographic Information System). Eleven parameters: temperature, rainfall, elevation, slope, distance to rivers, distance to stagnant water bodies, distance to wet lands, distance to roads, population density, LULC (land use/land cover) and distance to healthcare facilities were considered to produced malaria risk map for the area. Multi-Criteria Evaluation (MCE) method was used to map the malaria risk by reclassifying all the factors and assigning weights to each one based on how well-suited they were for the risk of malaria. The final malaria risk map for the area was created using the weighted overlay procedures in the ArcGis spatial analyst tool using assigned values of various risk factors. The malaria risk levels result reveals that 46.07%, 33.71%, 9.94% and 10.28% of the study area fall under low, moderate, high and very high malaria risk levels. This result shows that one-fifth of the study area was subjected to high and very high risk levels of malaria. It is suggested that effective identification and mapping of malaria-risk levels can be made using geospatial tools, to contribute for the prevention and control of this disease.

References

Abiodun GJ, Maharaj R, Witbooi P, Okosun KO. (2016). Modelling the influence of temperature and rainfall on the population dynamics of Anopheles arabiensis. Malar J, 15:364.

Adhina. AH., Permata, A., Mustofa, D., Wulandari, D. E., Ratnasari, I. D., Ekafitri, N. A., ... & Widayani, P. (2018). Application of Remote Sensing and GIS for Malaria Disease Susceptibility Area Mapping in Padang Cermin Sub-District, District of Pesawaran, Lampung Province. In IOP Conference Series: Earth and Environmental Science (Vol. 165, No. 1, p. 012012). IOP Publishing.

Afrane, Y. A., Zhou, G., Lawson, B. W., Githeko, A. K., & Yan, G. (2007). Life-table analysis of Anopheles arabiensis in western Kenya highlands: Effects of land covers on larval and adult survivorship. American Journal of Tropical Medicine and Hygiene, 77(4): 660–666.

Ahmed, A. (2014). GIS and remote sensing for malaria risk mapping, Ethiopia. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(8): 155-161

Akinbobola A., and Ikiroma I.A. (2018) Determining Malaria Hotspot Using Climatic Variables and Geospatial Technique in Central Urban Area of Ibadan, Southwest, Nigeria. J Climatol Weather Forecasting 6: 225.

Alemu, A., Abebe, G., Tsegaye, W., & Golassa, L. (2011). Climatic variables and malaria transmission dynamics in Jimma town, South West Ethiopia. Parasites & vectors, 4(1), 1-11.

Alimi, T.O., Fuller, D.O., Herrera, S.V., Arevalo-Herrera, M., Quinones, M.L., Stoler, J.B., Beier, J.C. (2016). A multi-criteria decision analysis approach to assessing malaria risk in northern South America. BMC Public Health 16. http://dx.doi.org/10.1186/ s12889-12016-12902-12887

Ashenafi, M. (2003) Design and water management of irrigation system to control breeding of Anopheles mosquitoes. Case study: Hara irrigation project, Arba Minch, Ethiopia. Unpublished M Sc thesis Wageningen University, Wageningen. The Netherlands.

Bhattacharya S, Sharma C, Dhiman RC, Mitra AP. (2006) Climate change and malaria in India. Current Science, 90(3):369-375.

Ceccato, P., Connor, S.J., Jeanne, I., Thompson, M.C. (2005) Application of geographic information system and Remote sensing technologies for assessing and monitoring malaria risk. Parassitologia 47: 81-97

Chikodzi, D. (2013). Spatial modelling of malaria risk zones using environmental, anthropogenic variables and geographical information systems techniques. Journal of Geosciences and Geomatics, 1(1), 8-14.

Dlamini, S.; Sabelo, N.; Franke, J.; Vounatsu, P. (2015) Assessing the relationship between environmental factors and malaria vector breeding sites in Swaziland using multi-scale remotely sensed data. Geospat. Health, 10: 302.

Eniyew, S. (2018). Modelling of malaria hotspot sites using geospatial technology in the north-western highlands of Ethiopia. Int J Mosq Res 5: 59–70.

Federal Ministry of Health {FMoH} and National Malaria Elimination Programme {NMEP} (2014) National Malaria Strategic Plan 2014-2020. Abuja, Nigeria. Federal Republic of Nigeria

Federal Republic of Nigeria Official Gazette, 2007 No.24 Vol. 94 Lagos, Nigeria

Ferrao, J. L., Niquisse, S., Mendes, J. M., & Painho, M. (2018). Mapping and modelling malaria risk areas using climate, socio-demographic and clinical variables in Chimoio, Mozambique. International Journal of Environmental Research and Public Health, 15(4), 795.

Franke, J., Gebreslasie, M., Bauwens, I., Deleu, J., Siegert, F. (2015) Earth observation in support of malaria control and epidemiology: MALAREO monitoring approaches. Geospatial Health, 10:335

Fuller, D.O., Troyob, A., Alimi T.O. and Beier, J.C. (2014) Participatory risk mapping of malaria vector exposure in northern South America using environmental and population data. Applied Geography, 48:1-7

Gebre, S. L., Temam, N., & Regassa, A. (2020). Spatial analysis and mapping of malaria risk areas using multi-criteria decision making in Didessa District, South West Ethiopia. Cogent Environmental Science, 6(1), 1860451.

Gurmu, A.D. (2009) Vulnerability analysis and malaria risk mapping in Awassa and Wondogenet Woredas. Unpublished M Sc thesis, Addis Ababa University, Ethiopia

Guthmann, J.P, Llanos-Cuentas, A., Palacios, A., Hall, A.J. (2002) Environmental factors as Determinants of Malaria Risk. A descriptive study on the Northern coast Peru. Tropical Medicine and International Health, 7(6):51-525

Haque, U., Hashizume, M., Glass, G. E., Dewan, A. M., Overgaard, H. J., & Yamamoto, T. (2010). The role of climate variability in the spread of malaria in Bangladeshi highlands. PloS one, 5(12), e14341.

Hay, S. I., Battle, K. E., Pigott, D. M., Smith, D. L., Moyes, C. L., Bhatt, S., ... & Gething, P. W. (2013). Global mapping of infectious disease. Philosophical Transactions of the Royal Society B: Biological Sciences, 368(1614), 20120250.

Jigawa State Ministry of Health {JSMoH} (2010) Strategic Health Plan (2010-2015). Jigawa State Government

Kalluri S, Gilruth P, Rogers D, Szczur M (2007) Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: A review. PLoS Pathog 3(10): e116. doi:10.1371/journal.ppat.0030116

Katsayal, U.A, and Obamiro, K.O. (2007) In-vivo Antiplasmodial activity and phytochemical screening of ethanolic extract of the leaves of Cissampelos Mucronata. Nigerian Journal of Pharmaceutical Sciences, 6(2): 111-115

Kimbi, H, K., Sumbele, I. U. M., Nweboh, M., Anchang-Kimbi, J. K., Lum, E., Nana, Y., Ndip, L. M.,Njom, H. and Lehman, L. (2013) Malaria and haematologic parameters of pupils at different altitudes along the slope of mont Cameroun: a cross-sectional study. Malaria Journal, 12:193

Lemessa, A. (2011) Geographic Information System and Remote Sensing Based Malaria Risk Mapping in Fentale Woreda, East Shoa Zone, Ethiopia. Unpublished M Sc thesis, Addis Ababa University, Ethiopia

Madobi, Z.H. (2019) Prevalence and Risk Factors of Malaria in Kano Metropolis, Nigeria. Nigerian Journal of Basic and Applied Science, 27(2): 76-87

Mihiretie, A. Assessment of Malaria Risk Using GIS and Multi Criteria: The Case Study of East Gojjam Zone, Ethiopia. International Journal of Environment and Geoinformatics, 9(1): 74-78.

Minale, A. S., & Alemu, K. (2018). Mapping malaria risk using geographic information systems and remote sensing: The case of Bahir Dar City, Ethiopia. Geospatial health, 13:660

Moha, A., Maru, M., & Lika, T. (2020). Assessment of malaria hazard, vulnerability, and risks in Dire Dawa City Administration of eastern Ethiopia using GIS and remote sensing. Applied Geomatics, 12(1): 15-22.

Mohammed, M. A. (2018). Malaria prone area analysis and mapping using geospatial tools: The case of Amibara and Gewane Woreda, afar region, Ethiopia. Journal of Geography and Regional Planning, 11(6): 80-94.

Mulefu, F. O., Mutua, F. N. and Boitt, M. (2016) Malaria risk and vulnerability assessment GIS approach: case study of Busia county, Kenya. IOSR Journal of Environmental Science, Taxiocology and Food Technology, 10(4): 104-112

National Malaria Elimination Programme {NMEP}, National Population Commission, {NPopC}, National Bureau of Statistics {NBS} and ICF International (2016) Nigeria Indicator Survey 2015. Abuja, Nigeria, and Rockville, Maryland, USA: NMEP, NPopC, and ICF International

Nicole, M.; Wayant, N.M.; Maldonado, D.; Rojas de Arias, A.; Cousiño, B.; Goodwin, D.G. (2010) Correlation between normalized difference vegetation index and malaria in a subtropical rain forest undergoing rapid anthropogenic alteration. Geospat. Health, 4: 179–190.

Njar, G.N., Akpama, W.A., Iwara, A.I., Ita, E..A. and Lasisi, C.J. (2013) Mapping risk prone zones of malaria vector species in Cross Rivers State, Nigeria. J. Med. Sci. 13(2): 76-85

Olofin, E.A. (2008) The physical setting. In Olofin, E.A., Nabegu, A.B. and Dambazau, A.M. (eds). Wudil within Kano region: a geographical synthesis. A publication of the department of Geography, Kano University of Science and Technology Wudil. Adamu Joji Publishers Kano City. Pp 5-42

Paajmans, K.P.; Blandford, S.; Bell, A.S.; Blandford, J.I.; Read, A.F.; Thomas, M.B. (2010) Influence of climate on malaria transmission depends on daily temperature variation. Proc. Nat. Acad. Sci. USA, 107: 15135.

Praveen, K.R., Mahendra, S.N. and Mohhamed, O (2012) Application of multiple linear regression model through GIS Remote Sensing for malaria mapping in Varanasi district, India. Health Science Journal, 6 (4): 731-749

Rincón-Romero, M. E., & Londoño, J. E. (2009). Mapping malaria risk using environmental and anthropic variables. Revista Brasileira de Epidemiologia, 12: 338-354.

Roll Back Malaria, (2015) “Climate change and Malaria,” http://www.google.com.gh/search?q=climate+change+and+malaria+ 2015.pdf&client=ms-opera-mini-android&channel=new&gws rd=cr&ei=tUzUVrytJ8uIaMHmiMAF.

Romero, M., Leiba, E., Carrion-Nessi, F.S., Diana, C., Nobrega, F., Kaid-Bay, S., et al. (2021) Malaria in pregnancy complications in Southern Venezuala. Malaria Journal, 20:186

Rumisha, S. F., Shayo, E. H., & Mboera, L. E. (2019). Spatio-temporal prevalence of malaria and anaemia in relation to agro-ecosystems in Mvomero district, Tanzania. Malaria Journal, 18(1): 1-14.

Rutherford, M. E., Mulholland, K., & Hill, P. C. (2010). How access to health care relates to under-five mortality in sub-Saharan Africa: Systematic review. Tropical Medicine and International Health, 15(5), 508–519.

Saxena, R., Nagpal, B.N., Srivastava, A., Gupta, S.K. and Dash, A.P. (2008) Application of spatial technology in malaria research and control: some new insights. Indian J. Med. Res. 130: 125-132

Simeon, M. (2014) Geographic Information System and Remote Sensing Based Malaria Risk Mapping Using Environmental Factors: A Case of Arba Minch Zuria Woreda, Southern Nations Nationalities and Peoples’ Regional State. Unpublished M Sc thesis Addis Ababa, University, Ethiopia

Tiruneh, A (2010) GIS and Remote Sensing Based Assessment of Malaria Risk Mapping for Boricha Woreda, Ethiopia. Unpublished M Sc thesis, Addis Ababa University, Ethiopia

Van Der Hoek, W., Konradsen, F., Amerasinghe, P. H., Perera, D., Piyaratne, M. K., & Amerasinghe, F. P. (2003). Towards a risk map of malaria for Sri Lanka: the importance of house location relative to vector breeding sites. International journal of epidemiology, 32(2): 280-285.

WHO. (2003). World Health Report. Shaping the future. Geneva: World Health Organisation.

WHO (2017) World Malaria Report, 2016: Country profiles. Geneva, Switzerland.

WHO (2021) World Malaria Report, 2021. Geneva, Switzerland.

Wolfarth, B. R., Filizola, N., Tadei, W. P. and Durieux, L. (2013) Epidemiological analysis of malaria and its relationships with hydrological variables in four municipalities of the State of Amazonas, Brazil. Hydrological Sciences Journal 58 (7): 1495-1504

Wondim, Y. K., Alemayehu, E. B., & Abebe, W. B. (2017). Malaria hazard and risk mapping using GIS based spatial multicriteria evaluation technique (SMCET) in Tekeze Basin Development Corridor, Amhara region, Ethiopia. J Environ Earth Sci, 7(5), 76-87.

Worku, T. (2016) Geographic Information System and Remote Sensing Based Malaria Risk Mapping: A Case of shone town administration, Southern Nations Nationalities and Peoples’ Regional State. Unpublished M Sc thesis Addis Ababa University, Ethiopia

Zeng, W., Cui, X., Liu, X., Cui, H., & Wang, P. (2006, July). Remote sensing and GIS for identifying and monitoring the environmental factors associated with vector-borne disease: An overview. In 2006 IEEE International Symposium on Geoscience and Remote Sensing (pp. 1443-1446). IEEE.

Zhang, Q., Sun, J., Zhang, Z., Geng, Q., Lai, S., Hu, W., ... & Li, Z. (2016). Risk assessment of malaria in land border regions of China in the context of malaria elimination. Malaria Journal, 15(1), 1-9.

Zhao, X., Thanapongtharm, W., Lawawirojwong, S., Wei, C., Tang, Y., Zhou, Y., & Kaewkungwal, J. (2020). Malaria risk map using spatial multi-criteria decision analysis along Yunnan border during the pre-elimination period. The American Journal of Tropical Medicine and Hygiene, 103(2), 793.

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Published

2024-05-31

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Original Articles

How to Cite

Geospatial Analysis of Malaria Prevalence among Children Under Five Years in Jigawa State, North West, Nigeria. (2024). African Journal of Biomedical Research, 27(2), 243-251. https://doi.org/10.4314/ajbr.v27i2.7

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