Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 2615-2617, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-2615-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 2615-2617, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-2615-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  02 May 2018

02 May 2018

SPATIO-TEMPORAL ANALYSIS TO PREDICT ENVIRONMENTAL INFLUENCE ON MALARIA

S. Baig and M. S. Sarfraz S. Baig and M. S. Sarfraz
  • Department of Computer Science, University of Gujrat, Gujrat Pakistan

Keywords: Malaria, Prediction, Moran’s I, Spatial Analysis and Environmental Influence

Abstract. Malaria is a vector borne disease which is a major cause of morbidity and mortality. It is one of the major diseases in the category of infectious diseases. The survival and bionomics of malaria is affected by environmental factors such as climatic, demographic and land-use/land-cover etc. Currently, a very few under developing countries are using Geo-informatics approaches to control this disease. Gujrat a district of Pakistan, is still under threat of malaria disease. Current research is carried on malaria incidents obtained from District Executive Officer of Health Gujrat. The objective of this study was to explore the spatio-temporal patterns of malaria in district Gujrat and to identify the areas being affected by Malaria. Furthermore, it has been also analyzed the relationship between malaria incident and environmental factors in highly favorable zones. Data is analyzed based on spatial and temporal patterns using (Moran’s I). Moreover cluster and hot spots analysis were performed on the incident data. This study shows positive correlation with rainfall, vegetation index, population density and water bodies; while it shows positive and negative correlation with temperature in different seasons. However, variation between amount of vegetation and water bodies were observed. Finding of this research can help the decision makers to take preventive measures and reduce the morbidity and mortality related with malaria in Gujrat, Pakistan.