Using the information value method in a geographic information system and remote sensing for malaria mapping: a case study from India

Praveen Kumar Rai, Mahendra Singh Nathawat, Shalini Rai


Background This paper explores the scope of malaria-susceptibility modelling to predict malaria occurrence in an area.

Objective An attempt has been made in Varanasi district, India, to evaluate the status of malaria disease and to develop a model by which malaria-prone zones could be predicted using five classes of relative malaria susceptibility, i.e. very low, low, moderate, high and very high categories.

The information value (Info Val) method was used to assess malaria occurrence and various time-were used as the independent variables. A geographical information system (GIS) is employed to investigate associations between such variables and distribution of different mosquitoes responsible for malaria transmission. Accurate prediction of risk depends on a number of variables, such as land use, NDVI, climatic factors, population, distance to health centres, ponds, streams and roads etc., all of which have an influence on malaria transmission or reporting. Climatic factors, particularly rainfall, temperature and relative humidity, are known to have a major influence on the biology of mosquitoes. To produce a malaria-susceptibility map using this method, weightings are calculated for various classes in each group. The groups are then superimposed to prepare a Malaria Susceptibility Index (MSI) map.

Results We found that 3.87% of the malaria cases were found in areas with a low malaria-susceptibility level predicted from the model, whereas 39.86% and 26.29% of malaria cases were found in predicted high and very high susceptibility level areas, respectively.

Conclusions Malaria susceptibility modelled using a GIS may have a role in predicting the risks of malaria and enable public health interventions to be better targeted.


Epidemiology; geographical mapping; malaria; public health; spatial analysis

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Kaya S, Pultz TJ, Mbogo CM, Beier JC and Mushinzimana E. The use of radar remote sensing for identifying environmental factors associated with malaria risk in coastal Kenya. International Geoscience and Remote Sensing Symposium, Toronto, ON, 2002.

Saxena R, Nagpal BN, Srivastava A, Gupta SK and Dash AP. Application of spatial technology in malaria research and control: some new insights. Indian Journal of Medical Research 2009;130(2):125–32. PMid:19797808.

Connor SJ, Flasse SP, Perryman AH and Thomson MC. The contribution of satellite derived information to malaria stratification, monitoring and early warning. World Health Organization mimeographed series, WHO/MAL/1997; 1079.

Craig MH, Snow RW and Le Sueur D. A climate-based distribution model of malaria transmission in sub-Saharan Africa. Parasitology Today 1999;15:105–11.

Omumbo JA, Hay SI, Snow RW, Tatem AJ and Rogers DJ. Modelling malaria risk in East Africa at high spatial resolution. Tropical Medicine and Internal Health 2005;10(6):557–66. PMid:15941419; PMCid:PMC3191364.

Mullner RM, Kyusuk C, Croke KG and Menash EK. Geographical information systems in public health and medicine. Journal of Medical Systems 2004;28(3):215–21. PMid:15446613.

Sudhakar S, Srinivas T, Palit A, Kar SK and Battacharya SK. Mapping of risk prone areas of kala-azar (Visceral leishmaniasis) in parts of Bihar state, India: an RS and GIS approach. Journal of Vector Borne Disease 2006;43:115–22. PMid:17024860.

Joyce K. To me it’s another tool to help understand the evidence: Public health decision-makers’ perceptions of the value of geographical information system (GIS). Health and Place 2009;15:831–40. PMid:19268622.

Rytkönen Mika JP. Not all maps are equal: GIS and spatial analysis in epidemiology. International Journal of Circumpolar Health 2004; 63:9–24. PMid:15139238.

Messina JP and Crews-Meyer KA. The Integration of remote sensing and medical geography: process and application. In: Albert DP, Gesler WM and Levergood B (Eds), Spatial Analysis, GIS, and Remote Sensing Applications in the Health Sciences. Chelsea, MI: Ann Arbor Press, 2005, 156.

Hoek W, Konradson F, Amersinghe PH, Perara D, Piyaratne MK and Amerasinghe FP. Towards a risk map of malaria in Sri Lanka: the importance of house location relative to vector breeding sites. International Journal of Epidemiology 2003;32:280–5.

Kulldorff M. Spatial scan statistics: model, calculations and applications. Scan Statistics and Applications 1999;15:303-302.

Lawson AB. Disease mapping: basic approaches in new developments. In: Maheswaran R and Cragilla M (Eds), GIS in Public Health Practice. New York: CRC Press, 2001; 31-49.

Rai PK, Nathawat MS and Onagh M. Application of multiple linear regression model through GIS & Remote Sensing for malaria mapping in Varanasi district, India. Health Science Journal 2012;6(4):731–49.

Riedel N, Vounatsou P, Miller JM, Gosoniu L, Chizema-Kawesha E, Mukonka V and Steketee RW. Geographical patterns and predictors of malaria risk in Zambia: Bayesian geostatistical modelling of the 2006 Zambia national malaria indicator survey (ZMIS). Malaria Journal 2010;9:37. PMid:20122148; PMCid:PMC2845589.

Saha AK, Gupta RP and Arora MK. GIS based landslide hazard zonation in Bhagirathi, Ganga valley, Himalayas. International Journal of Remote Sensing 2005;23:357–69.

Donald PA, Wilbert MG and Barbara L. Spatial Analysis, GIS and Remote Sensing Application in the Health Sciences. Chelsea, MI: Ann Arbor Press, 2006, 185.

Boscoe FP, Ward MH and Reynolds P. Current practices in spatial analysis of cancer data: data characteristics and data sources for geographic studies of cancer. International Journal of Health Geography 2004;97:14041–3.

Kleinschmidt I, Bagayoko M, Clarke GPY, Craig M and le Sueur D. A spatial statistical approach to malaria mapping. International Journal of Epidemiology 2000;29:355–61. PMid:10817136.

Sweeney AW. A spatial analysis of mosquito distribution. GIS Use 1997;21:20–21.



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